Archives of Mining Sciences 51, Issue 3 (2006) 311–346 ”Our

Archives of Mining Sciences 51, Issue 3 (2006) 311–346 ”Our

311
Archives of Mining Sciences 51, Issue 3 (2006) 311–346
DOMINIK STAŚKO*, MACIEJ KALISKI**
AN EVALUATION MODEL OF ENERGY SAFETY IN POLAND IN VIEW OF ENERGY
FORECASTS FOR 2005-2020
MODEL OCENY BEZPIECZEŃSTWA ENERGETYCZNEGO POLSKI W ASPEKCIE PROGNOZ
ENERGETYCZNYCH NA LATA 2005-2020
”Our methods are modified by our knowledge,
just like our knowledge is being transformed
in compliance with our methods”
[Isaac Levi]
The presented subject is part of a sequence of complex energy safety issues covering the present state
and perspectives of providing Poland with energy raw minerals. An attempt was made to theoretically
analyze factors determining the growth or decrease of energy safety level, with an evaluation model of
energy safety model as an outcome. This model was based on the multicriterial analysis method. The input
data for the analysis came from scenarios described in governmental documents:
• „Assumptions of Poland’s energy by the year 2020” (Survival, Reference, Progress Plus Scenarios).
• „Poland’s energy policy by the year 2025” (Treaty, Coal Basic, Gas Basic, Efficiency Variants).
The eighth scenario was the author’s variant, which according to the Authors enables maximization
of the assumed partial evaluation parameters.
The analysis of the model indicated a multiaspect character of the energy safety problems A vast range
of quantitative and qualitative factors had to be accounted for. As a result of the analysis a quantitative
analysis of specific scenarios was presented under the angle of providing energy safety for Poland.
Keywords: energy safety, energy forecasts, multicriterial analysis
Podjęty temat ma na celu próbę przedstawienia złożoności problemów, które należy uwzględnić
w ocenie bezpieczeństwa energetycznego. Bezpieczeństwo energetyczne jest pochodną bilansu energetycznego oraz zjawisk, które towarzyszą jego tworzeniu, dlatego też w artykule przedstawiono podstawowe
*
CARPATIAN GAS COMPANY, GAS COMPANY IN KRAKÓW, POLAND; AGH UNIVERSITY OF SCIENCES AND TECHNOLOGY, AL. MICKIEWICZA 30, 30-059 KRAKÓW, POLAND
** AGH UNIVERSITY OF SCIENCES AND TECHNOLOGY, AL. MICKIEWICZA 30, 30-059 KRAKÓW, POLAND
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informacje z zakresu kształtowania się bilansu paliwowo-energetycznego Polski w latach 1950-2003.
Dokonano również analizy znaczenia poszczególnych nośników energii dla gospodarki krajowej w perspektywie roku 2020. Analiza ta objęła prognozy zapotrzebowania na energie pierwotną określone w dokumencie „Założenia polityki energetycznej Polski do 2020 roku” oraz „Polityce energetycznej Polski do
2025 roku”. Projekcje zapotrzebowania zestawiono ze sobą celem zbadania różnic w prognozowanych
bilansach energetycznych Polski. Wykazane rozbieżności dotyczą przede wszystkim początkowych lat
ujętych w prognozach (lata 2005-2010) co jednoznacznie wskazuje na dużą dezaktualizacje przyjętego
modelu zapotrzebowania określonego w „Założeniach polityki energetycznej Polski do 2020 roku”.
Jak wykazano, perspektywy bilansu energetycznego mimo istotnej modyfikacji (w stosunku do
stanu obecnego) związane będą nadal z dominacja paliw stałych. Determinantą takiego stanu rzeczy
jest bogata baza surowcowa oraz rozbudowana infrastruktura wydobywcza i przetwórcza. Tym niemniej
w świetle przeprowadzonej analizy, w horyzoncie następnych piętnastu lat rysuje się niezależnie od
przyjętej prognozy i scenariusza, rosnące znaczenie paliw węglowodorowych oraz szeroko pojętej
energetyki odnawialnej.
W artykule dokonano semantycznej analizy pojęcia bezpieczeństwa energetycznego formułowanego
w sposób odmienny m.in. w wspomnianych dokumentach. Wykazano, iż zróżnicowanie przedstawianej
definicji bezpieczeństwa energetycznego wynika z trudności ujęcia wielopłaszczyznowości zagadnienia
w jedną zwartą regułę.
Nieostrość i wieloaspektowość bezpieczeństwa energetycznego przejawia się w fakcie, iż można go
odnosić do bezpieczeństwa lokalnego jak i międzynarodowego można również rozpatrywać zagadnienie
w szeregu kryteriów o przeciwstawnym charakterze np. ekonomicznym, środowiskowym czy społecznym.
Wszystko to sprawia, iż analiza bezpieczeństwa energetycznego obarczona jest problemem subiektywności
oceny. Ocena ta uzależniona jest każdorazowo od ważności poszczególnych komponentów określających
fragmentarycznie badane zagadnienie. Istotność oraz dobór komponentów bezpieczeństwa energetycznego
określana jest zazwyczaj w sposób autorytatywny na bazie dostępnych przesłanek przez decydenta lub
decydentów. W praktyce sprowadza się to zazwyczaj do określenia wybranych wskaźników oceny cząstkowej na bazie, których w sposób intuicyjny formułuje się ogólną ocenę bezpieczeństwa energetycznego.
Na powyższą analizę nakłada się również konieczność rozpatrywania czynników, których spełnienie jest
wzajemnie sprzeczne.
Analizę taką cechuje brak powtarzalności oceny, z uwagi na różny i często nie usystematyzowany
proces określania bezpieczeństwa energetycznego. Końcowa ocena częstokroć sprowadza się do stwierdzenia czy i w jakim stopniu bezpieczeństwo energetyczne jest zagrożone. Jest to istotny mankament nie
tylko w trakcie procesu oceny, ale również w przypadku potrzeby monitorowania stanu bezpieczeństwa
energetycznego.
Biorąc pod uwagę powyższe uwarunkowania z wiązane z trudnościami określenia bezpieczeństwa
energetycznego zaproponowano model jego oceny oparty na analizie wielokryterialnej. Wykorzystanie
analizy wielokryterialnej do budowy modelu oceny bezpieczeństwa energetycznego zostało podyktowane
koniecznością rozpatrywania szeregu czynników takich jak samowystarczalność, wskaźnik dywersyfikacji,
wielkość zapasów, sytuacja polityczna, koszty środowiskowe, itp. których łączne rozpatrywanie wymaga
poszukiwania rozwiązania będącego kompromisem miedzy kilkoma funkcjami celu.
Brak możliwości mierzenia i monitorowania wszystkiego i związane z tym koszty, narzucają konieczność przyjęcia listy wskaźników oceny cząstkowej w śród których obok wskaźników ilościowych znaczna
część zajmują wskaźniki natury jakościowej. Zasadniczym zadaniem wskaźników jest zobrazowanie
stopnia realizacji przyjętych celów zawartych w definicjach bezpieczeństwa energetycznego. Dlatego
też w pracy zaproponowano zestaw wskaźników oceny cząstkowej stanowiący pewne instrumentarium
przeprowadzonej analizy. Dokonano podziału i weryfikacji przyjętych wskaźników ze względu na główne
czynniki opisujące kształt bezpieczeństwa energetycznego oraz poziom ich istotności. Zaproponowano
również kila systemów nadawania wag poszczególnym wskaźnikom wraz z preferowaną w analizie
bezpieczeństwa metodą AHP.
Końcowy etap pracy obejmuje przedstawienie przykładu analizy bezpieczeństwa energetycznego
przeprowadzonego za pomocą zaproponowanej metodologii. Podstawą analizy stały się scenariusze rozwoju sytuacji energetycznej zawarte w przytoczonych wcześniej dokumentach tj. scenariusze przetrwania,
odniesienia, postępu plus, traktatowy, podstawowy węglowy, podstawowy gazowy i efektywności. Jako
ósmy przedstawiono scenariusz autorski cechujący się maksymalizacją wskaźników pod kątem zwiększenia
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bezpieczeństwa energetycznego. Przeprowadzona analiza dotyczyła nośników energii pierwotnej a więc
węgla kamiennego, ropy naftowej gazu ziemnego oraz energii odnawialnej wg prognoz dla roku 2020.
Otrzymane wyniki odzwierciedlają stopień realizacji celów zapisanych w definicji bezpieczeństwa
energetycznego. Przedstawione wielkości wskaźnika końcowej oceny stanowią pewną hierarchizacje scenariuszy rozwoju sytuacji energetycznej pod kątem poziomu bezpieczeństwa energetycznego uwzględniając
m.in. imperatyw pewności dostaw, aspekty ekonomiczne, środowiskowe oraz polityczne.
Zaproponowana w pracy metodyka oceny bezpieczeństwa energetycznego nie zwalnia co prawda
decydenta z odpowiedzialności za przeprowadzoną analizę, czyni jednak proces oceny bardziej komfortowym, racjonalnym, przez co zarówno czas podejmowania decyzji jak i ich jakość mogą ulec wyraźnej
poprawie.
Słowa kluczowe: bezpieczeństwo energetyczne, prognozy energetyczne, analiza wielokryterialna
Introduction
Energy safety has been formulated and evaluated a number of times and yet belongs
to the most imprecise notions functioning in power industry. The relative character of the
notion causes that energy safety or its lack may not be confirmed in reality. Therefore,
in the Authors’ opinion, it is vital to elaborate and discuss methods of determining the
level of energy safety. As a consequence, the process of energy safety evaluation should
be systemized through establishing criteria of its assessment and the way in which its
values are to be determined. This should enable viewing all possible factors interfering
with the energy safety as well as some categorization and minimization of influence of
informal evaluations on the analyzed phenomenon.
1. An outline of history of Poland’s energy consumption
The Poland’s fuel balance over the last decades has been significantly modified
owing to the reduced solid fuel consumption with the concurrent increasing demand
for hydrocarbon fuels. Primary energy consumption in the years 1950 to 1988 systematically increased to reach in 1988 its unprecedented maximum of 128.6 Mtoe* (Ney,
2002) (fig. 1).
Social and economic changes of 1989, introduction of market economy, real energy
prices, economic recession followed by the restructuring processes resulted in reduced
primary energy consumption. The consumption in 2003 was 91.9 Mtoe, therefore reached
a level of the 1970s (Staśko, 2006).
Along with the change of fuel consumption, it was also the structure of the power
energy balance which started to change. This was caused by a low demand for coal and
growing demand for hydrocarbon fuels. Owing to the insufficient resources and production power, this type of fuel had to be also imported (Rychlicki & Siemek, 2002).
* Mtoe – Million Tons of Oil Equivalent (1 Mtoe = 41,9 PJ = 1015 kcal)
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140,0
126,6
123,6
120,0
100,7
consumption [Mtoe]
100,0
99,1
91,1
90,5
94,1
86,7
84,8
80,0
64,4
64,8
59,7
60,0
54,5
50,6
49,1
46,4
40,0
28,6
27,8
20,0
16,2
2,3
0,9 0,7
0,1
0,0
1950
1960
7,6
5,9 5,2
1,3
1970
6,6 8,8
14,8
14,2
9,7
1,4
1980
13,5
12,7
8,9
1,3
1988
1,3
1990
13,4
12,8
9,0
4,2
1995
18,4
12,1
10,0
17,7
12,4
12,2
4,3
2000
2,7
2003
year
Hard coal
Lignite
Oil
Natural gas
Renewable energy
Total
Fig. 1. Structure of primary energy consumption in Poland from 1950 to 2003 (own study)
Rys. 1. Struktura zużycia energii pierwotnej w latach 1950-2003
The share of coal (fig. 2) decreased from 64% in 1990 to 52% in 2003. The share of
lignite in the analogous period was stable and was about 13%. The share of oil significantly increased to a level of about 19%, with a concurrent increase of the share of natural
gas to 8.8% in 1990 and 12.9% in 2003, respectively. Recently no significant increase
of the share of the renewables has been observed (Staśko, 2006).
Contrary to the EU average, the Poland’s balance of primary energy consumption is
dominated by solid fuels, despite the increase of the share of hydrocarbon fuels. This
situation was caused by the fact that the developed exploitation base could make use of
rich resources and the existing structure of electrical energy and heat generation (mainly
in coal-fed power plants and electrical energy and power plants).
2. Power energy forecasts
The changing demand for energy, especially in a long time horizon, depends on, e.g.
dynamics of economic growth and level of energy consumption GNP, reflecting changes
in the economy structure and efficiency of energy use. The structure of the energy balance is conditioned by the needs of society and abilities to satisfy them. The latter, in
315
100
0,1
1,9 0,7
share in energy balance [%]
90
0,1
1,2
4,2
1,6
1,6
1,2
1
1,3
6,2
7
7,6
8,8
8,9
80
13,1
11,7
5,4
11,2
6,9
12,6
13,4
70
4,3
4,7
2,9
9,1
10,9
12,9
20,2
18,8
13,3
13,1
50,9
52,2
2000
2003
13,5
12,9
60
50
97,3
92,9
40
76,4
73,3
68,5
30
63,9
60,2
20
10
0
1950
1960
1970
1980
1988
1990
1995
year
Hard coal
Lignite
Oil
Natural gas
Renewable energy
Fig. 2. Structure of primary consumption (%) in Poland from 1950 to 2003 (own study)
Rys. 2. Struktura procentowa zużycia energii pierwotnej w latach 1950-2003
turn, depends on the new discoveries, wellbeing of national economy and citizens, as
well as preferences of the consumers.
Over the last years a number of forecasts for the Poland’s energy balance were made.
Some of them were described in such official ministerial documents as:
▪ „Assumptions of Poland’s energy by the year 2020” approved of the Cabinet on
17 October 1995,
▪ „Assumptions of Poland’s energy by the year 2020” approved of the Cabinet on
22 February 2000,
▪ „Evaluation of realization and correction of assumptions of Poland’s energy policy
by the year 2020” with attachments, approved of by the Cabinet on 2 April 2002,
▪ „Poland’s energy policy by the year 2025” approved of by the Cabinet on 4 January
2005.
Each of the forecasts in these documents was made in different time and on the basis
of different political and economic conditions, e.g. differences in approach to the forecast GNP, population, undertaken pro-efficiency activities, energy prices, etc (Kaliski
i Staśko, 2005).
Three variants of economic development were presented in the „Assumptions of
Poland’s energy by the year 2020”:
• Survival Variant, a warning scenario, realized in the conditions of weak World’s
development, hindered by political instabilities; the mineral economy structure stabilizes in Poland at that time, and the average annual increase of GNP is ca. 2,3%.
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• Reference Variant, in the condition of political stability and development of international environment, without rapid changes; concurrent deep structural changes
take place in Poland, and the annual increase of GNP is ca. 4,0%.
• Progress Plus Variant, realized in favorable conditions of international environment
and deep restructuring of Polish economy, when the rate of GNP increase could
be maintained at ca. 5,5%.
The newest document „Poland’s energy policy by the year 2025” assumes four variants of fuel and energy demand:
• Treaty Variant, taking into account the Accession Treaty, e.g. 7,5% electrical energy consumption from renewable energy sources in 2010 and reduction of total
emissions from large combustion objects to standards defined in the treaty.
• Coal (basic) Variant, meeting requirements imposed on reduction of emission
from large objects from 2012 to the year 2020.
• Gas (basic) Variant, assuming maintained coal deliveries to electrical power plants
with a simultaneous increase of gas share in covering additional energy needs.
• Efficiency Variant, assuming additional improvement of power efficiency in the
energy generation, distribution and use areas, owing to active policy of the State.
According to the above scenarios, the demand for energy depends on the rate of economic development, which is to be on average 5,3% over 20 years. Another important
factor having an influence on the demand for energy is population. It decreased from
38,1 mln in 2005 to 36,6 mln in 2025, i.e. by about 4%.
Diversification of macroeconomic assumptions as well as model changes significantly influence the predicted magnitude and type of demand, thus generating proportions
of the planned energy balance. Figures referring to the balance of energy carriers are
expressed differently in various literature sources, making the comparisons difficult.
Therefore, recalculation of demand expressed in real values (mln tons, mld m3) to more
universal units, e.g. Mtoe (impossible to compare actual fuels balance) can be only
approximated.
By comparing scenarios (fig. 3 to fig. 7) discussed in „Assumptions of Poland’s energy
by the year 2020” (survival, reference and progress plus scenarios) and in „Poland’s
energy policy by the year 2025” – working materials of 4 December 2004 (treaty, coal
(basic), gas (basic) and efficiency scenarios) it was possible to imagine feasible space
of differences in the predicted primary energy demand in Poland.
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120,00
100,00
demand [Mtoe]
80,00
5,30
5,50
13,74
15,00
20,40
20,20
5,80
13,16
5,20
5,20
5,20
5,20
11,80
11,80
11,70
11,60
20,70
20,70
20,70
20,70
43,70
44,30
44,10
43,80
22,20
60,00
40,00
55,74
54,78
51,30
20,00
13,83
13,83
13,74
10,70
10,52
10,78
10,78
TREATY
BASIC COAL
BASIC GAS
EFFICIENCY
0,00
SURVIVAL*
REFERENCE* PROGRESS PLUS*
scenario
Lignite
Hard coal
Natural gas
Oil
Renewable energy
Fig. 3. Demand for specific energy carriers in 2005 – scenarios (own study): * – scenarios Assumptions
of Poland’s energy by the year 2020”; the remaining scenarios „Poland’s energy policy by the year 2025”
Rys. 3. Zapotrzebowanie na poszczególne nośniki energii w roku 2005 według scenariuszy: * – scenariusze „Założenia polityki energetycznej Polski do 2020 roku”; pozostałe scenariusze „Polityka energetyczna Polski do 2025 roku”
120,00
5,50
6,00
6,30
16,50
18,40
15,40
20,40
23,50
100,00
demand [Mtoe]
80,00
7,90
7,90
15,80
15,30
15,10
23,10
23,10
22,70
45,30
45,60
45,20
10,09
10,95
11,13
10,78
TREATY
BASIC COAL
BASIC GAS
EFFICIENCY
15,80
20,20
23,10
60,00
40,00
7,90
8,00
52,74
50,58
50,76
42,00
20,00
13,91
13,95
13,91
0,00
SURVIVAL*
REFERENCE* PROGRESS PLUS*
scenario
Lignite
Hard coal
Oil
Natural gas
Renewable energy
Fig. 4. Demand for specific energy carriers in 2010 – scenarios (own study): * – scenarios Assumptions
of Poland’s energy by the year 2020”; the remaining scenarios „Poland’s energy policy by the year 2025”
Rys. 4. Zapotrzebowanie na poszczególne nośniki energii w roku 2010 według scenariuszy: * – scenariusze „Założenia polityki energetycznej Polski do 2020 roku”; pozostałe scenariusze „Polityka energetyczna Polski do 2025 roku”
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120,00
100,00
5,70
6,50
19,19
20,95
6,90
8,90
18,52
18,40
demand [Mtoe]
80,00
20,80
21,40
8,80
8,80
19,10
20,60
26,50
26,50
26,00
44,50
42,30
41,30
9,00
19,60
25,30
26,50
60,00
40,00
51,60
50,34
50,70
41,80
20,00
13,68
13,70
13,70
10,95
11,04
11,39
10,87
TREATY
BASIC COAL
BASIC GAS
EFFICIENCY
0,00
SURVIVAL*
REFERENCE* PROGRESS PLUS*
scenario
Lignite
Hard coal
Natural gas
Oil
Renewable energy
Fig. 5. Demand for specific energy carriers in 2015 according to scenarios (own study): * – scenarios
Assumptions of Poland’s energy by the year 2020”; the remaining scenarios „Poland’s energy policy by
the year 2025”
Rys. 5. Zapotrzebowanie na poszczególne nośniki energii w roku 2015 według scenariuszy: * – scenariusze „Założenia polityki energetycznej Polski do 2020 roku”; pozostałe scenariusze „Polityka energetyczna Polski do 2025 roku”
140,00
120,00
7,70
5,90
demand [Mtoe]
100,00
7,10
9,90
9,80
21,79
24,55
21,10
22,30
80,00
9,90
9,90
23,13
21,20
20,10
27,90
26,10
23,80
30,40
30,40
30,40
29,50
42,30
41,60
60,00
40,00
50,10
49,14
49,44
48,70
46,50
20,00
13,58
13,58
13,58
10,70
10,52
10,70
10,09
TREATY
BASIC COAL
BASIC GAS
EFFICIENCY
0,00
SURVIVAL*
REFERENCE* PROGRESS PLUS*
scenario
Lignite
Hard coal
Oil
Natural gas
Renewable energy
Fig. 6. Demand for specific energy carriers in 2020 – scenarios (own study): * – scenarios Assumptions
of Poland’s energy by the year 2020”; the remaining scenarios „Poland’s energy policy by the year 2025”
Rys. 6. Zapotrzebowanie na poszczególne nośniki energii w roku 2020 według scenariuszy: * – scenariusze „Założenia polityki energetycznej Polski do 2020 roku”; pozostałe scenariusze „Polityka energetyczna Polski do 2025 roku”
319
Demand [Mtoe]
120
110
Consumption
Range [Mtoe]
Maximum
difference of
forecasts
[Mtoe]
112.2 – 121.8
9.6
100
108 – 114.7
6.7
101.5 – 109.7
90
18.2
93.3 – 106.4
13.1
80
2005
SURVIVAL*
2010
REFERENCE*
PROGRES PLUS*
year
TREATY
2015
BASIC COAL
2020
BASIC GAS
EFFICIENCY
Fig. 7. Forecasts of primary energy consumption from 2005 to 2020 (own study): * – scenarios Assumptions
of Poland’s energy by the year 2020”; the remaining scenarios „Poland’s energy policy by the year 2025”
Rys. 7. Projekcje zużycia energii pierwotnej w latach 2005-2020: * – scenariusze „Założenia polityki
energetycznej Polski do 2020 roku”; pozostałe scenariusze „Polityka energetyczna Polski do 2025 roku”
The indicated differences in predicted demand for energy (fig. 7) are connected with
the nature of forecasts, the construction of which requires certain assumptions and generalizations. The economic and political situation in Poland and over the World changes,
therefore the assumed market models obviously differ from actual, losing their validity
with time. The actual conditions will most probably differ from the forecasts made for
the coming 15 years, thus deciding about the reliability of a given prediction. This is
indirectly confirmed by differences in the demand, which are 14%, 18%, 6%, 9% for the
years 2005, 2010, 2015 and 2020, respectively (Kaliski & Staśko, 2005) (fig. 7).
The comparison of predicted demands for energy carriers by the year 2020 creates
bases for a thesis that Polish economy will continue being dominated by solid fuels,
despite the visible changes in the structure of primary fuels consumption in favor of
natural gas and oil, typical of the past years.
3. The notion of „energy safety”
”Safety” and ”security” belong to the most commonly used notions for defining
numerous areas related with human activity. Safety, security (Latin ”sine cura = securitas” sine – without, cura – care, attention, worry; securitas – free of care, secure, free
of worries or endangerments) – is a notion giving a sense of stability. Understanding of
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the notion, as given in the Dictionary, (lack of endangerments) does not, however, fully
correspond with the actual situation. Man’s existence and all forms of his activity are
related with a variety of endangerments, and the point is how to successfully overcome
or omit them (Klimek, 2004).
Obviously, safety belongs to the most important tasks of the Government, one of the
basic existential purposes and development priorities. A number of safety-types can be
distinguished. Energy safety is an element of the general safety, additionally defined in
a spatial, time and organizational dimension (fig. 8).
SPATIAL CRITERION
- local
- subregional
- regional
- beyond-regional
- global (World’s)
ECOLOGICAL
ENERGY
SOCIAL
SUBJECT
CRITERIA
ECONOMIC
POLITICAL
TIME CRITERION
MILITARY
ORGANIZATION
CRITERION
- unilateral
- balance of forces
- co-operative
- mass
- short term
- average term
- longterm
Fig. 8. Division of safety according to exemplary criteria (Staśko, 2006)
Rys. 8. Podział bezpieczeństwa wg przykładowych kryteriów
Being an element of a complex economic-political-environmental structure, energy
safety is in focus of the analysis. Energy safety as an element of State’s policy and
transformed economy, can be viewed in the international, internal and local perspective
(Kolenda, Siemek, 1999).
The importance of energy safety stems out from the specific role of energy minerals
in the World. On one hand, it is conditioned by the civilization level and technological
development; on the other one, however, it depends on the renewability of resources and
their geopolitical distribution, conditioning the accessibility of minerals and stability of
deliveries (Rychlicki & Siemek, 2004).
321
The transport of energy minerals creates a situation where safety of deliveries is
conditioned by efficiency of means of transportation and generally the transport of
energy minerals itself. Hence, power energy minerals have to be treated as a strategic
product having a political and economic meaning, and so an element of general security
of Poland (Skarżyński, 2004).
In this context, a question should be posed of what the energy safety is and with
what variables it can be expressed. Energy safety has been defined a number of times
for Poland. However, no satisfactory description of the issue has been provided so far.
In “Assumptions of Poland’s energy by the year 2020” the energy safety has been defined as:
„– safety of energy deliveries, i.e. meeting conditions to cover current and perspective
demand of economy and society for energy of a given type and quality,
– socially justified energy prices, i.e. an energy price policy employing competitive
market mechanisms or regulation of prices to balance the interest of the consumer
and the company supplying energy,
– minimal environmental hazard, i.e. obeying ecodevelopment principles”.
In “Assumptions of Poland’s energy by the year 2020” the following definition of
energy safety is provided:
„a state of economy, thanks to which current and perspective demand for fuels and
energy can be covered in a technically and economically justified way, accounting for
environmental protection requirements.” Broadened by social aspect, this definition has
been presented in the newest document „Poland’s energy policy by the year 2025” , where
we can read that energy safety is „a state of economy, thanks to which the current and
perspective demand for fuels and energy can be covered in a technically and economically
justified way, with the minimized negative environmental and social impact”.
A new doctrine of energy safety in the above mentioned document focuses on the
development of market as the most important warranty of energy safety. Here the responsibility for energy safety is divided with respect to the time perspective, i.e. short-term,
average term and longterm (tab. 1) as well as local, regional, country and European
dimension (tab. 2).
In turn, according to the definition formulated by prof. W. Bojarski (2004), energy
safety means:
1. energy safety for customers (users of energy) – degree of sureness that the needed
form of energy will be delivered on time, in the required quantity and at accessible
prices.
2. energy supply safety – degree of sureness that a given power energy (supply system)
can:
▪ fully cover the predicted energy demand of all customers at socially acceptable
prices – in normal exploitation conditions, maintaining continuity of deliveries,
required quality parmateres and meeting the environmental prerogatives.
322
TABLE 1
Division of responsibility for energy safety (time factor) (own study)
TABLICA 1
Podział odpowiedzialności za bezpieczeństwa energetyczne w aspekcie czasowym
Safety
Responsibility
State
Operators
Consumers
Investors
Short term
[technical]
Average term
[according to the existing
salability]
●●●
●●●
●
Longterm
[investment]
●
●●
●●
●●●
●●●
TABLE 2
Division of responsibility for energy safety (area factor) (own study)
TABLICA 2
Podział odpowiedzialności za bezpieczeństwa energetyczne w aspekcie obszarowym
Safety
Responsibility
State administration
Local administration
Operators
Consumers
Investors
Local
Regional
Poland
European
●
●●●
●●●
●●●
●
●
●●
●●●
●
●
●●
●●
●●●
●●●
●●
●●
▪ satisfactorily cover definite partial energy demand at deteriorated quality
conditions – in various possible crisis, catastrophe, etc. situations.
3. Energy safety of a country (region) covers both energy safety of customers and
also safety of energy supplies. This safety can be additionally analysed as:
▪ short term (operational) safety, now,
▪ seasonal (tactic) safety, planned and predicted for a given season,
▪ average terms safety, planned and predicted for the coming few years,
▪ longterm (strategic) safety, planned and predicted for the more distant future.
Regardless the assumed form and accuracy, the presented definitions of energy safety
do not exhaust the complexity of the issue. They still contain contradictory postulates,
making the practical realization impossible. The conflict of economy and other interests
is evident, resulting in, e.g. necessity to cover the costs related to the diversification
of deliveries or environmental protection. This stands in a clear opposition to the urge
to minimize the costs, therefore the importance and priority of particular criteria have
323
to be discussed (Staśko, 2006). The present definitions of energy safety combine the
above-mentioned aspects, therefore the answer to this question depends on the assumed
safety strategy.
Owing to this and the character of the notion itself, the objective assessment of the
energy safety level is a difficult, frequently dubious question. As for now, it has been
reduced to determining selected indices (tab. 3.) on the basis of which the general state
of safety is assessed (frequently intuitively).
TABLE 3
Selected indices determining the energy safety level (own study)
TABLICA 3
Wybrane wskaźniki określające poziom bezpieczeństwa energetycznego
Index
Formula
1
2
Stirling
(1)
Description
3
Diversification index(es)
m
åu ln u
WST = -
j =1
j
j
uj – share of j-th carrier
m – number of energy carriers
Unit
4
Desired
value
5
[-]
Possibly
high
Rj – reserves of a given fuel in a country
Pj – fuel production in a given year
[year]
Possibly
high
Pj – fuel production in a given year
ZK – country’s global consumption equal
to the sum of supplied fuels, diminished by
a balance of country’s reserves
[%]
Possibly
high
Index(es) of minerals base abundance
Life of reserves
(2)
Energy selfsufficiency
(3)
WZZ =
WSE =
Rj
Pj
P × 100
ZK
Index(es) of import/export dependence
Import
dependence
(4)
Export
dependence
(5)
WZI =
WZE =
Ij - Ej
Z Kj
E j - Ij
Z Kj
ZKj – global consumption of j-th carrier,
Ij – import of j-th carrier,
Ej – export of j-th carrier.
[%]
Possibly
low
Possibly
high
Index(es) characterizing fuel reserves
Reserves
(6)
WZA =
Mi – state of reserves of i-th energy carrier
Mj
× 365 at the end of calculation period,
Zj
[day]
Zi – consumption of i-th carrier over a year
Possibly
high
Economic index(es)
Current liquidity
(7)
Quick liquidity
(8)
M
WPB =
Zk
M-z
WPS =
Zk
M – turnover assets
Zk – short-term obligations
z – reserves
[multipli
-cation]
>2
>1
324
1
2
Net return
(9)
F ×100
WRN = n
p
3
Fn – net financial results
p – income from whole activity
4
5
[%]
High
[hrs/
year]
Possibly
low
Failure index
Time of undelivered power
(10)
Amount of undelivered power
(11)
WTM = h/t
h – time in shorter unit (e.g. hour)
t – time in longer unit (e.g. year)
WWE = m/t
m – power (e.g. MWh)
t – time (e.g. year)
[MWh/ Possibly
year]
low
4. Basis of the proposed model of assessing energy safety
A model is presented for the analysis of factors implying the energy safety level,
depending on specific exploitation conditions (failure, change of demand for energy,
etc.) economic conditions (investments, oscillations of energy prices, etc.) environmental
conditions (use of renewables, emissions, etc.) social and political conditions (political
situations, social conditions, etc). By analysing each of these factors separately, the most
self-sufficiency situation or import-dependence situation can be pointed out. However,
such an analysis does not give an answer to the best configuration of parameters meeting
all criteria at the same time. The evaluation of the energy safety is related with a number
of functions of purpose, which representing a mathematical description of a given criterion, frequently stay in conflict. Therefore, the analysis of energy safety conditioned
by the assumed criteria can be only made as a search for a solution being a compromise
of a few functions of purpose.
Owing to the character of the issue, the analysis of energy safety should possibly be
made with the use of a multicriteria analysis – a mathematical tool, enabling formulation
of purposes in a number of ways in relation to the analysed issue. Bearing in mind the
complexity of the notion of energy safety, its analysis should be made in view of possibly
all factors having influence on the issue. An algorithm for assessing energy safety, based
on multicriteria analysis is proposed in fig. 9.
The starting point for making an energy safety model is establishing the range of
analyses by determining the types of energy carriers and range of analysis. By the range
we understand the level of analysed energy safety, i.e. the whole country’s safety level
and safety of energy consumers or local power systems. The determined range of analysis
obviously implies further assumptions, mainly selection of appropriate evaluation indices.
The next stage lies in determining the horizon of analysis, and adequately, assuming
available power forecasts (import, export, consumption, etc.). Thus, the analysis is also
connected with the risk of reliability of forecasts. Therefore, the quality and quantity
of available data significantly reduces uncertainty of the forecast, and increasing the
quality of the analysis.
325
SCOPE OF ANALYSIS
HORIZON
OF ANALYSIS
COMPONENTS OF
ENERGY SAFETY
no
DO
COMPONENTS
ACCOUNT FOR
MAIN ASPECTS
OF E.S.
???
OBSERVATION
MATRIX
no
DESCRIBING FACTORS
no
yes(1)
Xo
DOES
LIST
OF FACTORS
DEFINE ASPECTS
OF E.S.
???
yes
DO
THEY
DESCRIBE
IMPORTANT AND
PARTLY INDEPENDENT FACTORS
???
(1)
QUANTITY
INDICES
yes
yes
I
PARTIAL INDICES
OF EVALUATION
DO
INDICES HAVE
QUANTITATIVE
CHARACTER
???
no
stimulants
yes(2)
(2)
destimulants
ORDERING
MATRIX
NORMALIZATION
PROCEDURES
NORMALIZED
MATRIX
X
X
J
ORDER SCALE
II
ARE
VALUES IN
PARTICULAR
VARIANTS
DIFFERENT
???
I
QUALITY
INDICES
no
ELIMINATION OF
IDENTICAL VALUES
yes
ORDERING
MATRIX
DISTRIBUTION
LEVEL
aP
X
EVALUATION
MATRIX
III
M
ap
GLOBAL SUM
Si
EVALUATION
INDEX
f(B)
ARE
VALUES f(B)
DISTINGUISHABLE
ENOUGH
???
WEIGHTS
OFINDICES
lj
no
yes
INDICES OF EVALUATION
OF ENERGY SAFETY
f(B)
Fig. 9. Proposed algorithm of energy safety evaluation (Staśko, 2006)
Rys. 9. Proponowany algorytm oceny poziomu bezpieczeństwa energetycznego
P
326
The analysis of energy safety requires decomposition of a system describing it. This
is done in order to distinguish a hierarchic structure of interrelated components, and
consequently determine possibly all factors having influence on the shape of the energy
safety. In this way the defined and defining variables of the model can be determined.
The characteristics of a given energy safety aspect are ascribed to objects belonging
to the aspect, which enables ordering of the gathered data. This, in turn, has a positive
influence on the quality of deduction and omitting derivative conclusions on the basis of
insignificant premises. The proposed energy safety model bases on an analytical model
following from general to details (Staśko, 2006).
According to the above assumptions of energy safety definition, three main components of energy safety should be distinguished. They generally describe the energy
safety as a whole in a given scope of analysis. Further detailing of the successive stages
requires determining a list of descriptive factors on the specific levels, which would characterize a given safety aspect as fully as possible. Owing to the magnitude of processes
influencing the shape of energy safety, the specification and classification of definable
factors and their division should be unformalized.
Selection of indices enables further comparative analysis of various configurations of
energy safety system in the specific environmental, economic and political conditions.
Thus obtained indices may be described in various physical units; they may also give
a quantitative characteristic of reality. However, they should not coincide. They may
contain an element of an alternative (reaching one goal to a higher degree may hinder
realization of another one). Therefore, at the successive stage the character of the used
variables should be determined in view of their quantitative and qualitative character.
Quantitative indices are based on a definite way of reasoning presented in a mathematical form, thanks to which a result given in figures can be obtained. Except for this, the
quantitative indices can be also divided into:
• stimulants – variables, the high values of which are desired from the point of
view of the general characteristic of the analysed phenomena, e.g. power selfsufficiency.
• destimulants – variables, the high values of which are undesired in view of the
general characteristic of the analysed phenomena (import dependence) (Kamrat,
1999; Kaliski i Staśko 2005).
Once the indices are selected for the analysis, the quantitative properties, i.e. stimulants
and destimulants should be standardized to the interval 0,1. This is done to eliminate
the influence of impact of various units, with which the coefficients were characterized.
Owing to the different character of stimulants and destimulants, they are standardized
differently (Kamrat, 2004) (eq. 12 – fig. 10; eq. 13 – fig. 11).
327
'
1 S xij
0
Xmin
Xmax
Fig. 10. Standardization of stimulants (Staśko, 2006)
Rys. 10. Normalizacja stymulant
S 'xij =
S xij - min i {Sxij }
(12)
max i { S xij } - min i { S x ij }
'
1 D xij
0
Xmin
Xmax
Fig. 11. Standardization of destimulants (Staśko, 2006)
Rys. 11. Normalizacja destymulant
D 'xij =
Dxij - max i {Sxij }
min i {Dx ij} - max i {Dx ij }
(13)
328
In the case of a stimulant-type variable having a variability range of 34 to 127, its
maximum value (127) after standardization will gain a nominal 1, whereas the minimum value (34) will get 0; the remaining xij values from the interval 34 to 127 will get
values 0 < x < 1. In the case of destimulants a “reverse” standardization process causes
that the maximum value of destimulant after transformation will be 0. The transformed
quantitative and qualitative variables for an interval 0,1 should be treated as a specific
type of stimulant matrix, where values from an interval 0 to 0,5 are assumed to be
undesired from the point of view of the analysed phenomena; 0,5 is a boundary point,
where desired and undesired factors are in equilibrium, values above 0,5 are typical of
desired factors.
As a result of the presented standardization, a matrix of indices is obtained, where
the rows represent successive scenarios of energy situation development, and the lines
stand for figures being realizations of individual indices.
When the figure representing a given index is the same for all scenarios, it is automatically eliminated (the obtained partial values do not have an influence on the global
evaluation value).
Another type of indices used for the analyses are variables which cannot be accurately
measured; they can only be stated to exist or not. These are qualitative indices requiring
expert decisions. They define properties of immeasureable character though their quantitative counterparts. This approach is based on an assumption that qualitative differences
are a result of quantitative differences. As a consequence, qualitative properties can be
determined by means of quantitative properties. For this reason, the so-called ordering
scale was determined to enable quantification of the available information. It was assumed in the model that qualitative properties should be evaluated for the interval 0 to 1,
where the increase of the index value denotes an improvement of the evaluated value.
Owing to the range of the ordering scale (from 0 to 1) the values from a subinterval 0 to
0.5 should be treated as undesirable, whereas the remaining ones, especially those close
to 1 are desirable. The following ordering scale is proposed for the model, accounting
for which all the qualitative indices will be evaluated:
1.0 – state of full energy safety in a given range (energy safety threatened only
theoretically),
0.7 – state of acceptable energy safety level (disturbed energy safety possible in
practice only occasionally and at a small scale),
0.5 – state of partly acceptable energy safety (possible loss of energy safety in
a given range); suggested measures of improving this situation,
0.2 – limited energy safety,
0.0 – no energy safety in a given range.
Another stage lies in integrating transformed quantitative indices (standardized
matrix) with qualitative indices (qualitative data matrix). A new ordered matrix was
thus generated, which contains quantitative and qualitative data for <0,1>. In order to
329
differentiate between evaluations of individual strategies, the obtained figures were subjected to another transformation lying in the division of variability values of individual
indices to subintervals of the same range. Depending on the values in a given scenario,
the parameter is qualified to the suitable subinterval. In a great number of subintervals,
the results can be well differentiated. Thus obtained matrix is called a matrix of index
evaluation.
As the influence of the analysed indices on the energy safety issue varies, the next
step lies in determining the weights and ascribing them to the specific indices on the
assumption that the sum of weights is equal to unity.
On the basis of products of the ascribed weights and indices for a given scenario
the so-called global sum was determined. The final stage of the analysis is determining
the index of evaluation, which is obtained as a quotient of the obtained global sum and
maximum global sum attainable by a given strategy. This index constitutes a summaric
index of a given safety level related to the remaining scenarios. In other words, the
evaluation index of energy safety is relative and determines only the best scenario in
a given set of scenarios, for the assumed criteria.
5. Exemplary analysis of energy safety
Basing on the accessible forecasts of power development in Poland and the model
assumptions, an exemplary analysis of energy safety state in Poland in 2020 is presented.
5.1. Scope of analysis
The analysis covered determining the energy safety level for the whole country. It
refers to the primary energy carriers, i.e. coal, lignite, oil, natural gas renewables. It does
not cover electrical nor nuclear energy (planned to be used after 2020).
5.2. Horizon of forecast
The analysis covers the year 2020, and is made on the basis of the survival, reference,
progress plus scenarios (”Assumptions of Poland’s energy by the year 2020”) and treaty,
coal (basic), gas (basic) and efficiency scenarios (”Poland’s energy policy by the year
2025” – working material of 4 December 2004).
5.3. Safety aspects and analysis factors
The multilayer character of the issue, with all the technical, economic, environmental,
political and social aspects becomes the greatest difficulty in evaluation of energy safety.
Therefore, a model which would rely on energy safety definitions presented in chapter 3
is needed. The semantic meaning of the notion is based on the Authors’ definition of
330
energy safety along with the ways of its determination. According to the assumed definition of energy safety (Staśko, 2006):
”methodology describing the system of selection and aggregation of partial evaluation indices to obtain a synthetic measure of evaluation for a given energy safety
structure”.
Thus understood definition of energy safety structure constitutes quantitative relations
between selected components of energy safety (especially between basic indices), relations between these elements and share of each element in the assessment. The energy
safety depends on the assumed strategy of energy safety, e.g. self-sufficiency strategy,
diversification strategy, mixed-type strategy, being a resultant of the assumed priorities
(e.g., self-sufficiency, diversification, etc.).
It follows from the presented definition that the evaluation of energy safety is treated
as a whole, which changes under the influence of certain changes of its components or
changes of their significance level. Therefore, calculation of changes of quantitative
relations between these elements is a core of the analysis of final evaluation of energy
safety level.
Basing on the presented definitions, four main energy safety aspects were distinguished (fig. 12):
• Aspect of reliability of deliveries (A) – embracing mainly factors related with
the reliability of supplies, understood as an access to primary energy carriers,
enabling demands (character of energy balance). This can be solved by the resultant of the country’s exploitation, import, export, storing potential and level of its
utilization.
In the general sense, this aspect should also encompass factors determining the
character of technical infrastructure by indicating the weak points of the existing
technical base and the resultant hazards. Owing to this the technical aspect as mentioned in the definition was encapsulated in the aspect of reliability of deliveries.
• Economic aspect (B) – determining economics of power energy minerals as well
as financial conditions of power companies and energy consumers. This aspect
should cover the broadest possible spectrum of indices of energy prices, economic
situation of companies and energy consumers.
• Environmental aspect (C) – embracing environmental issues related with gaining,
production and use of various forms of energy. The environmental aspect covers
indices defining the degree of use of the renewables and also state and possibilities
of using natural resources.
• Political and social aspect (D) – criterion embracing factors of qualitative character, informing about the influence of the political and social situation on the
quality of energy minerals delivery. This aspect also covers the political aspect,
legal regulations, realization of energy policy, e.g. increasing energy efficiency,
balanced demand and sale, higher competitivity.
331
ENERGY SAFETY
EXTERNAL
FACTORS
EXTERNAL
FACTORS
diversification; reserves;
import dependence;
self-sufficiency;
system sensitivity;
risk of failure
ECONOMIC
ASPECT
Price efficiency;
Inner costs;
Competitivity;
State of economy sector
INTERNAL FACTORS
EO share in balance;
Environmental costs;
Life of reserves
ENVIRONMENTAL
ASPECT
Political environment;
Quality of legal;
Economic stability;
Location of supply sources
ENERGY SAFETY
ENERGY SAFETY
ASPECT OF SAFE
DELIVERIES
POLITICAT
AND SOCIAL
ASPECT
EXTERNAL
FACTORS
EXTERNAL
FACTORS
ENERGY SAFETY
Fig. 12. Proposed division of energy safety according to aspects and factors (own study)
Rys. 12. Proponowany podział bezpieczeństwa energetycznego na aspekty i czynniki
5.4. Indices of evaluation
Below there is a list of evaluation indices assumed for the analysis. The individual
indices were attributed to the respective aspects (component of energy safety):
• Aspect of reliability of delivery (A) (Table 4)
• Economic aspect (B) (Table 5)
• Environmental aspect (C) (Table 6)
• Political-social aspect (D) (Table 7)
To eliminate the important convergence of indices (result of multiple evaluation of
the same factor), they were correlated with the use of the pair analysis. In the case of
indices of highly correlated values, only one evaluation index can be assumed and the
remaining ones should eliminated from the analysis. The inability to determine a given
index should be taken as admissible in the case of a low significance level (Table 8).
TND = h/t
WME = m/t
WIN
Energy selfsufficiency
Reserves
Time of
undelivered
energy
Quantity of
undelivered
power
Sensitivity of
infrastructure
to disturbances
(failure, terrorist
attacks, etc.)
A4
A5
A6
a7
WZA =
SAM =
Zj
´ 365
– power (e.g., MWh)
– time (e.g., year)
– time (e.g., hour)
– time (e.g., year)
1,0 – low sensitivity of system to external disturbances,
highly dispersed system, many independent sources of supply
0,7 – low sensitivity of system, highly dispersed system,
some independent sources of supply
0,5 – system sensitive to external disturbances, some sources
0,0 – system very sensitive to external disturbances, one
source of supply
m
t
h
t
M – state of reserves of i-th energy carrier at the end
of calculation period
Zt – time in a longer unit (e.g., year)
– share of i-th carrier
– number of energy carriers
Mj
ln u j uj
m
Pj – fuel extraction in a given year
ZKj – country’s total fuel consumption in a given year
zj – fuel reserves in a given year
j
Ij – import of fuel in a given year
Ej – export of fuel in a given year
ZKj – country’s total fuel consumption in a given year
Calculation formula/data description
Pj × 100
( Z Kj - zj )
j =1
åu
m
A3
XX _ STR = -
Stirling
A2
Ij - Ej
Z Kj
Import
dependence
A1
ZIM =
Index
Group
Wskaźniki charakteryzujące aspekt pewności dostaw
Indices characterizing aspect of reliability of deliveries (own study)
Character
of index
stimulant
stimulant
Possibly
destimulant
low
Possibly
destimulant
high
Possibly
high
Possibly
high
Possibly
destimulant
low
Desired
value
[-]
1
qualitative
[MWh/ Possibly
destimulant
year]
low
[hour/
year]
[day]
[%]
[-]
[%]
Unit
TABLICA 4
TABLE 4
332
DDN
STE
Diversification
of energy carrier
delivery
Technical state
of sector
a8
a9
[-]
[-]
1,0 – highly diversified, independent sources (many
suppliers)
0,7 – partly dependent, diversified sources (a few suppliers)
0,5 – weakly diversified, partly dependent sources (weak
domination of one supplier <50%)
0,2 – weakly diversified, dependent sources (stron
domination of one supplier >50%)
0,0 – external monopoly (one supplier)
1,0 – system has sufficient powers, transfer and distribution
reserves, negligible failure-proneness which has no influence
on operation
0,7 – system has sufficient powers, transfer and distribution
reserves, requires bigger reserves or partial replacement
of infrastructure, failure-proneness which has slight influence
on operation
0,5 – system on verge of transfer and distribution powers,
requires huge investments on infrastructure, medium failureproneness
0,2 – failure-prone system, deficiency of power, requires
immediate investments on infrastructure
0,0 – system very prone to failures, does not fulfill tasks,
great deficiency of power
1
1
qualitative
qualitative
333
Investments
b8
KIN
XX_ZOE
consumers with financial liquidity
consumers with limited funds
consumers with financial minimum
consumers with no income
investments not necessary
low investment costs to be spent
high investment costs to be spent
very high investment costs
investment costs exceed financial abilities
b7
–
–
–
–
–
–
–
–
–
Consumers’
well-being
1,0
0,7
0,5
0,0
1,0
0,7
0,5
0,2
0,0
E – unit of energy
USD – American dollar
E
USD
ENR =
Energy
consumption
B6
M – active assets
Zk – short-term obligations
z – reserves
Fn – net financial result
p – income from the whole activity
B5
M
Zk
Fn ×100
p
Quick liquidity
B4
WPB =
WRN =
Current liquidity
B3
KW – index of external costs [Usct/Kw]
ZKj – country’s total fuel consumption in a given year
j =1
m
J
EKZ = å K W × ZK
Net return
Efficiency of
internal costs
B2
j =1
Cj – price of energy carrier (import) [PLN/Mtoe]
ZKj – country’s total fuel consumption in a given year
m
ECP = å CJ × ZKJ
M-z
Zk
Price efficiency
of fuels
B1
Calculation formula/data description
WPS =
Index
Group
Wskaźniki charakteryzujące aspekt ekonomiczny
Indices characterizing economic aspect (own study)
[-]
[-]
[kWh/
USD]
[%]
multiplication
[USD]
[PLN]
Unit
Character
of index
1
1
Possibly
high
Possibly
high
>1
>2
qualitative
qualitative
stimulant
stimulant
stimulant
Possibly
destimulant
low
Possibly
destimulant
low
Desired
value
TABLICA 5
TABLE 5
334
EKW = å K z × ZK
j =1
EMI = Zj . ej . vj
Efficiency of
external costs
CO2 emissions
R/P
R/Z
Amount of joint
energy
C2
C3
C4
C5
C6
Calculation formula/data description
XX _ SWE =
R /Z =
R /P =
m
Rj – Fuel home reserves for industry purposes
Zj – Annual fuel demand
Rj – Fuel home reserves for industry purposes
Pj – Annual fuel production
Zj – Consumption of a given fuel type
ej – Emission index
vj – Oxidation index
Kz – Index of external cost of an energy carrier [Usct/Kw]
ZKj – Total annual home fuel consumption
S
×1000 ZK – Associated energy production [toe]
S – Total energy demand
ZK
Zj
Rj
Rj
Pj
J
ZEO – Annual demand for renewables
ZEO
) ×100 % ZK – Total demand
ZK
Kz – External cost index [Usct/Kw]
Share of
renewables
C1
UEOD = (
Index
Group
Wskaźniki charakteryzujące aspekt środowiskowy
Indices characterizing environmental aspect (own study)
[toe]
[lata]
[lata]
–
[USD]
[%]
Unit
stimulant
Character
of index
Possibly
high
Possibly
high
Possibly
high
stimulant
stimulant
stimulant
Possibly
destimulant
low
Possibly
destimulant
low
Possibly
high
Desired
value
TABLICA 6
TABLE 6
335
[-]
d4
high economic growth related with dynamic development of companies
average economic growth
low economic growth
recession
1,0
0,7
XX_SGO
0,5
0,0
Social and
economic
stability
–
–
–
–
[-]
Political
environment
d3
[-]
1,0 – very good and stable international (political and economic) relations
especially with export of energy minerals and transit countries
0,7 – correct and relatively stable international relations (political and
economic)
XX_POL 0,5 – threatened international relations
0,2 – serious political tensions with energy mineral exporters and transit
countries
0,0 – open conflict with a neighbouring country, political power, and some
bigger political-financial structure
Quality of law
and regulations
d2
LZZ
Unit
[-]
Location of
supply sources
d1
1,0 – home source of supplies
0,7 – supplies from neutral countries
0,5 – supplies from countries politically unstable and/or transit through such
countries
0,2 – supplies from countries endangered with conflict and social
disturbances
0,0 – supplied from countries at war
Calculation formula/data description
1,0 – efficient supervision of strategic sources of supply, clarity and stability
of legal system , efficient regulation
0,7 – limited supervision of a country having limited efficiency and regulation
XX_JUS
0,5 – inefficient supervision of a country and poor legal regulation
0,2 – highly inefficient home supervision and poor legal regulation
0,0 – practically no supervision in the strategic areas
Index
Group
Wskaźniki charakteryzujące aspekt polityczno-społeczny
Indices characterizing political-social aspect (own study)
1
1
1
1
Desired
value
qualitative
qualitative
qualitative
qualitative
Character
of index
TABLICA 7
TABLE 7
336
Indices
Import dependence
Stirling
Energy self-sufficiency
Reserves
Time of undelivered energy
Quantity of undelivered power
Sensitivity of system
Diversification of energy carrier supplies
Technical state of energy sector
Price efficiency of energy carriers
Efficiency of external costs
Current liquidity
Net profitability
Energy-consumption
Economic situation of the sector
Well-being of consumers
Capital costs
Share of renewable energy
Efficiency of external costs
Emission
Life of reserves R/P
TABLE 8
A1 A2 A3 A4 A5 A6 a7 a8 a9 B1 B2 B3 B4 B5 b6 b7 b8 C1 C2 C3 C4 C5 C6 d1 d2 d3 d4
ZIM A1 Strongly correlated with A3 – excluded from analysis
STI
! A2
SAM !!! ! A3
WZA 0 0 !!! A4 Index A3 fully incorporates index A4 - excluded from analysis
TNM ? ? ? ! A5 No forecast data – partially represented by a7
WNE ? ? ? ! ! A6 No forecast data – partially represented by a7
WIN ? ? ! ! ! ! a7
DDN ? ? ? ? ? ? ? a8 (*)
STE 0 0 0 0 ! ! ! 0 a9 No forecast data – partially represented by a7
ECP !
0 0 0 0 0 0 0 0 B1
EKZ 0 0 0 0 0 0 0 0 0 ? B2 (*)
PBI 0 0 0 0 0 0 0 0 0 ? ? B3 No forecast data – representation by b6
REN 0 0 0 0 0 0 0 0 0 ? ? ? B4 No forecast data – representation by b6
ENR 0 0 0 0 0 0 0 0 0 0 0 0 0 B5 No forecast data – unrepresented
SES 0 0 0 0 0 0 ? 0 ? ? ! ! ! 0 b6 (*)
ZOE 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ? b7
KIN 0 0 0 0 ? ? ? 0 0 0 0 0 0 0 0 0 b8
UEO ?
! ! ? ? ? ! ! 0 0 ? 0 0 0 0 0 0 C1
EKZ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 C2 Partially represented by B2
EMI 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ! ! C3 Partially represented by B2
R/P
!
! ! 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 C4
Partially represented
R/Z
!
! ! 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 C5
by C4
SWE 0 0 ? 0 ! 0 0 0 0 0 0 0 0 0 0 0 0 0 ! ! 0 0 C6 (*)
LZZ ? ? ! 0 0 0 ! ! 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 d1 (*)
JUS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 d2 (*)
OPO 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 d3 (*)
SSG 0 0 0 0 0 0 0 0 0 0 0 ? ? 0 ! ! ? 0 0 0 0 0 0 0 0 0 d4
TABLICA 8
!!! – high correlation of components of the index; ! – partial correlation; ? – weak correlation, undefined or difficult to define;
0 – no correlation; (*) – no forecast data – unrepresented
Complex energy generation
Location of supply sources
Quality of law and regulations
Political environment
Economic stability
Denotations:
C6
d1
d2
d3
d4
C5 Life of reserves R/Z
A1
A2
A3
A4
A5
A6
a7
a8
a9
B1
B2
B3
B4
B5
b6
b7
b8
C1
C2
C3
C4
Weryfikacja wskaźników cząstkowych oceny
Verification of partial evaluation indices (own study)
337
338
The final list of factors assumed for the analysis
• in the aspect of reliability of deliveries
A1. energy self-sufficiency (stimulant),
A2. Stirling (stimulant),
a7. sensibility of system (qualitative),
• in the aspect of economy
B1. price efficiency (destimulant),
B2. efficiency of external costs (destimulant),
b8. investments (qualitative),
• in the environmental aspect
C1. share of renewables in the balance (stimulant),
C4. life of resources R/P (stimulant),
• in the political and social aspect ,
d3. economic stability (qualitative).
TABLE 9
Values of indices assumed for the analyses (own study)
TABLICA 9
Wartości wskaźników przyjęte do analizy
Partial evaluation indices
scenario
No.
WK_SAM
WK_R/P
WB_SAM
WB_R/P
RN_SAM
RN_R/P
GZ_SAM
GZ_R/P
XX_STR
XX_UOE
XX_ECP
XX_EKZ
WK_WIN
WK_KIN
WB_WIN
WB_KIN
RN_WIN
RN_KIN
GZ_WIN
GZ_KIN
EO_WIN
EO_KIN
XX_SGO
survival reference
1
127,16
75,25
119,67
27,25
8,81
30,12
18,38
35,98
1,41
5,33
18,62
77,58
0,00
0,70
0,50
1,00
0,50
1,00
0,50
1,00
0,70
1,00
0,20
2
129,65
75,25
119,67
27,25
8,33
30,12
16,31
35,98
1,44
6,17
19,96
78,59
0,70
0,70
0,50
0,70
0,50
0,70
0,50
0,70
0,70
0,70
0,50
Author’s
coal
gas
advancement
efficiency
treaty
+
(basic) (basic)
plus
3
4
5
6
7
8
128,86 130,16 124,28 132,73
132,73
148,98
75,25 76,57 66,36 71,54
72,74
72,74
119,67 119,67 119,67 119,67
119,67
132,73
27,25 30,27 33,74 33,20
35,18
35,18
8,54
6,11
6,11
6,11
8,08
11,51
26,36 30,12 21,04 21,04
18,41
14,73
19,43 19,49 18,48 16,85
18,48
25,34
35,98 36,42 45,87 45,87
45,87
38,12
1,45
1,45
1,44
1,48
1,47
1,47
6,41
7,68
7,56
7,64
7,94
7,94
21,44 21,67 22,16 22,88
21,91
21,91
84,06 84,28 86,16 81,28
79,01
79,01
1,00
0,70
0,70
1,00
1,00
1,00
0,80
0,70
0,50
1,00
0,70
1,00
0,70
0,50
0,50
0,70
0,70
1,00
0,80
0,70
0,50
1,00
0,70
1,00
0,70
0,50
0,50
0,70
0,70
1,00
0,50
0,70
1,00
0,30
0,50
1,00
0,70
0,50
0,50
0,70
0,70
1,00
0,50
0,70
1,00
0,70
0,70
1,00
1,00
0,70
0,70
1,00
1,00
1,00
0,50
0,70
1,00
0,50
0,70
1,00
0,70
0,50
0,50
0,50
0,70
1,00
339
Generally, 23 indices were assumed for coal (WK), lignite (WB), oil (RN), natural
gas (GZ) and renewables (EO), in that:
▪ 12 quantitative indices (10 stimulants and 2 destimulants),
▪ 11 qualitative indices.
5.5. Distribution level
The analysed distribution was assumed at γ = 10–4, which means that range of
valiability of each index was divided into 10 000 subintervals of equal length.
5.6. Determining weights for individual indices
The following weight systems facilitating differentiation of significance level of
individual evaluation indices were assumed in the analysis:
• W0 – equal weights
• W1 – weights acc, division to aspects of energy safety:
– for aspect A:
β = 0,5
– for aspect B:
β = 0,2
– for aspect C:
β = 0,2
– for aspect D:
β = 0,1
The β denotes the significance of a given aspect in the scale < 0,1 >, whereas
weights of specific indices in the framework of a given aspect result from a division of index β by a number of indices.
• W2 – weights acc. to index significance criteria (from the most significant to the
least important for the assessment):
– 1 main
β = 0,65
– 2 supplementary
β = 0,3
– 3 other
β = 0,05
• W3 – weights acc, to division into quantitative and qualitative factors
– I quantitative factors β = 0,7
– J qualitative factors
β = 0,3
• W4 – identical weights, with qualitative indices ignored
– I quantitative factors β = 1
– J qualitative factors
β=0
• W5 – weights determined with the use of AHP (Analytic Hierarchy Process) method, where the index of relative significance of index Si over Sj is expressed by
such aij that:
aij =
ei
ej
i, j = 1,2, …, n
(14)
340
where:
ei — absolute rank of index Si
ej — absolute rank of index Sj,
where aij Î {1,2,3,…9}
The evaluation of significance of indices was made on the basis of a five-degree
preference scale:
1 – equality,
3 – moderate significance,
5 – strong prevalence,
7 – very strong prevalence,
9 – critical prevalence.
The factors aij of the degree of mutual domination of factors ei were grouped in
a square matrix, where aij = 1/aij for i, j = 1,2,…n, which is presented in table 10.
TABLE 10
Mutual domination of indices as a square matrix after AHP (own study)
TABLICA 10
Wzajemna dominacja wskaźników przedstawiona jako macierz kwadratowa wg metody AHP
INDEX
SAM
STR
WIN
ECP
EKZ
KIN
UEO
R/P
SGO
SAM
1
1
1/3
1/3
1/3
1/5
1/5
1/9
1/5
STR
1
1
1/3
1/3
1/3
1/3
1/3
1/9
1/5
WIN
3
3
1
1/3
1/3
1/3
1/3
1/9
1/5
ECP
3
3
3
1
1
1
3
1/5
1/3
EKZ
3
3
3
1
1
1/3
1
1/5
1/3
KIN
5
3
3
1
3
1
3
1/5
1/3
UEO
5
3
3
1/3
1
1/3
1
1/5
1/3
R/P
9
9
9
5
5
5
5
1
1
SGO
5
5
5
3
3
3
3
1
1
5.7. Calculation of total sum
Calculation of total sum took a form of a multiplication of the matrix index and the
assumed weight.
5.8. Calculation of energy safety index
Index of energy safety was obtained directly from the total sum as a quotient of total
sum and maximum sum of point ranks attainable for the scenario.
Basing on the above described procedure and available data (table 9) the energy
safety indices were plotted in figures 13 to 18.
341
1,000
0,900
0,859
0,800
Evaluation Index
0,700
0,645
0,592
0,600
0,544
0,525
0,509
0,500
0,517
0,492
0,400
0,300
0,200
0,100
0,000
1
2
3
4
5
6
7
8
Scenario
Fig. 13. Indices of evaluation for scenarios according to weight criterion W0 (own study)
Rys. 13. Wskaźniki oceny dla poszczególnych scenariuszy wg kryterium wagowego W0
1,000
0,900
0,880
0,800
Evaluation Index
0,700
0,644
0,600
0,583
0,539
0,500
0,500
0,480
0,474
0,471
0,400
0,300
0,200
0,100
0,000
1
2
3
4
5
6
7
Scenario
Fig. 14. Indices of evaluation for scenarios according to weight criterion W1 (own study)
Rys. 14. Wskaźniki oceny dla poszczególnych scenariuszy wg kryterium wagowego W1
8
342
1,000
0,937
0,900
0,800
Evaluation Index
0,700
0,600
0,500
0,486
0,423
0,422
0,400
0,368
0,343
0,336
0,309
0,300
0,200
0,100
0,000
1
2
3
4
5
6
7
8
Scenario
Fig. 15. Indices of evaluation for scenarios according to weight criterion W2 (own study)
Rys. 15. Wskaźniki oceny dla poszczególnych scenariuszy wg kryterium wagowego W2
1,000
0,900
0,811
0,800
Evaluation Index
0,700
0,613
0,600
0,543
0,500 0,488
0,469
0,479
0,459
0,431
0,400
0,300
0,200
0,100
0,000
1
2
3
4
5
6
7
Scenario
Fig. 16. Indices of evaluation for scenarios according to weight criterion W3 (own study)
Rys. 16. Wskaźniki oceny dla poszczególnych scenariuszy wg kryterium wagowego W3
8
343
1,000
0,900
0,800
0,751
Evaluation Index
0,700
0,595
0,600
0,500
0,502
0,461
0,447
0,440
0,398
0,400
0,379
0,300
0,200
0,100
0,000
1
2
3
4
5
6
7
8
Scenario
Fig. 17. Indices of evaluation for scenarios according to weight criterion W4 (own study)
Rys. 17. Wskaźniki oceny dla poszczególnych scenariuszy wg kryterium wagowego W4
1,000
0,900
0,890
0,800
Evaluation Index
0,700
0,646
0,596
0,600
0,500
0,474
0,445
0,452
0,400
0,369
0,357
0,300
0,200
0,100
0,000
1
2
3
4
5
6
7
Scenario
Fig. 18. Indices of evaluation for scenarios according to weight criterion W5 (own study)
Rys. 18. Wskaźniki oceny dla poszczególnych scenariuszy wg kryterium wagowego W5
8
344
TABLE 11
Values of indices of energy safety evaluation for scenarios (own study)
TABLICA 11
Wartości wskaźników oceny bezpieczeństwa energetycznego dla poszczególnych scenariuszy
scenario
Weights
W0
ranking
5
2
4
3
1
6
7
8
W1
W2
W3
W4
W5
f(B) ranking f(B) ranking f(B) ranking f(B) ranking f(B) ranking f(B)
0,492
5 0,471
5 0,309
5 0,431
5 0,379
1 0,357
0,509
1 0,474
1 0,336
3 0,459
3 0,398
5 0,369
0,517
2 0,480
2 0,343
2 0,469
1 0,440
2 0,445
0,525
4 0,500
4 0,368
4 0,479
2 0,447
4 0,452
0,544
3 0,539
3 0,422
1 0,488
4 0,461
3 0,474
0,592
6 0,583
6 0,423
6 0,543
6 0,502
6 0,596
0,645
7 0,644
7 0,486
7 0,613
7 0,595
7 0,646
0,859
8 0,880
8 0,937
8 0,811
8 0,751
8 0,890
TABLE 12
Relative values of index of energy safety vs. maximum index (own study)
TABLICA 12
Wartości względne wskaźnika oceny bezpieczeństwa energetycznego wobec wskaźnika maksymalnego
scenario
W0
W1
W2
W3
W4
W5
Weights ranking f(B) ranking f(B) ranking f(B) ranking f(B) ranking f(B) ranking f(B)
5 0,573
5 0,535
5 0,330
5 0,531
5 0,504
1 0,401
2 0,593
1 0,538
1 0,359
3 0,566
3 0,530
5 0,414
4 0,602
2 0,546
2 0,366
2 0,579
1 0,586
2 0,501
3 0,611
4 0,569
4 0,393
4 0,591
2 0,596
4 0,508
1 0,633
3 0,613
3 0,450
1 0,602
4 0,614
3 0,533
6 0,689
6 0,663
6 0,452
6 0,670
6 0,668
6 0,670
7 0,750
7 0,732
7 0,518
7 0,756
7 0,792
7 0,727
8 1,000
8 1,000
8 1,000
8 1,000
8 1,000
8 1,000
The final result of analysis expressed by an evaluation index is conditioned by the
character of energy balance made on the basis of quantitative and qualitative indices.
Weights attributed to individual indices play an important role for the general evaluation of the analysed phenomenon. Therefore, in the Authors’ opinion, the evaluation
may be optimized only when attention is mainly paid to the weights of factors, as they
are frequently critical for the final result of the analysis. The AHP (Analytic Hierarchy
Process) method can be useful here as it enables correct attribution of weights to the
individual indices.
345
Conclusions
The presented approach to evaluation of energy safety lies in linking quantitative
and qualitative indices, The output can be expressed qualitatively and the analysed
evaluation process can be thus systemized. The presented analysis is not fully free of
subjective influences; however it is possible to systematically analyse all factors having
an influence on the studied issue.
Owing to the fact that the evaluation is based on a definition of energy safety, covering
a broad analytical spectrum, the evaluation of energy safety must concentrate on selected, generally defined factors, which can be easily realized. Proper formulation of these
factors, good balance between generality and accuracy, access to information that can
be expressed by indices should obviously influence the quality of the final evaluation.
Partial evaluation indices in the form of a model enable obtaining one measure of
evaluation, i.e. an index comprising all possible conditionings of energy safety.
The presented method is an optimization method expressed by a selection of possible
solutions of a given scenario, which in the light of the assumed criteria has the highest
energy safety index. Optimization is made for weighing technical, political, economic
and environmental influences in the conditions of multicriteria selection and significance
of these influences. The best scenario selected on the basis of the assumed criteria and
available input data represents the highest energy safety level in the analysed range.
In fact, it can be useful for solving problems related with evaluation of energy safety
level.
The analysis shows that the energy safety is a system of complex factors and problems,
which need to be solved. Many of them have been only mentioned in the paper. The
direction and way of approaching the issue have been outlined, and possibly contributed
to further analyses of energy safety.
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REVIEW BY: DR HAB. INŻ. STANISŁAW NAGY, KRAKÓW
Received: 23 March 2006