Security Of Electricity Supply Research Articles

Сучасні рішення забезпечення оцінки та контролю безпеки постачання електричної енергії

The introduction of market relations in the energy industry brought the issue of energy security to a new level, defining one of its components in the market as the security of electric energy supply. In the work, a comparative analysis of the existing conceptual terminological apparatus related to the definitions of energy security and security of supply was carried out in order to establish the main differences. At the same time, assessment and control of the security of electricity supply, as integral indicators that make it possible to plan the activities of the single European energy market, have become fundamental issues for various countries. Assessment and control of the security of electricity supply in modern Ukraine is becoming an increasingly urgent task in connection with the connection of its unified energy system to the energy system of Europe and the need to ensure emergency-free parallel operation. Therefore, the purpose of the study is to form an idea of modern approaches to the assessment of the security of electricity supply in Ukraine and the EU countries, as well as to search for opportunities to improve the control system of security of supply. It was established that, apart from the prescriptive regulation of the basic principles of the formation of indicators, at the moment there are no unified approaches that would allow them to be used to create a national methodological base for a conscious and qualitative assessment of security of supply. Based on the results of the comparative analysis, the main ways by which the issue of security of supply assessment is considered have been identified. It has been proven that an important direction is the creation of a multi-level system of assessment and control of the security of electricity supply, as well as ensuring the control of the implementation of organizational measures aimed at improving the security of supply. Keywords: security of electric energy supply, electricity, law, monitoring, regulation, reliability, directive.

Impact of Under Voltage Load Shedding Approach for Voltage Security Control in Power Quality Environment

Contingencies in power system are an ever-present problem for electrical engineers. They may cause the system to have low voltages due to active and reactive power deficiencies. Engineers shold consider the many solutions to approach this problem. The solution has to be appropriate to the contingency faced so as to be able to solve the issue without major damage to a power system. A drastic measure that can be used is by removing low voltage loads or ‘shedding’ the problematic loads. This method of Under Voltage Load Shedding is done by shedding or ‘islanding’ buses that have fallen to a predetermined minimum voltage for a predetermined time to prevent a cascade of blackouts in the widespread power system. The method to automate the process is by using two optimization techniques, Evolutionary Programming (EP) and Particle Swarm Optimization (PSO). This paper proposes a new hybrid algorithm, named Integrated Chaotic Swarm Based-Evolutionary Programming Optimization (ICSBEP) Technique for Voltage Security Control using Under Voltage Load Shedding (UVLS) approach. Voltage security is indicated by the reduction in voltage stability index, FVSI. In this study, EP, PSO and ICSBEP optimizations algorithms were developed and tested on a IEEE 30-bus reliability test system (RTS). Comparative studies were conducted to observe the advantages of the hybrid algorithm over traditional EP and PSO algorithms. The results obtained from the study can help manage the power quality of the system in ensuring that the customer receive secure electricity supply.

Cross-border electricity transfers in the case of differentiated renewable energy sources: A simulation analysis for Germany and Spain

Renewable electricity plays an increasingly important role in the effort to reduce CO2 emissions in the electricity sector. One of the major challenges that must be addressed is the fluctuating supply of renewable electricity. We explore the impact of cross-border electricity transfers on both the security of electricity supply and renewable electricity expansion. We focus on Spain and Germany due to the relative abundance of their country-specific renewable electricity sources (solar for Spain and wind for Germany). We develop an electricity market model that allows for cross-border electricity transfers by connecting country-specific electricity markets. We apply six policy scenarios aiming towards securing the electricity supply and renewable electricity expansion. Our simulation results show that cross-border electricity transfers postpone supply shortages in both countries. These shortages occur as a result of an increasing amount of low-marginal-cost renewable electricity, which, in turn, leads to a decrease in the electricity price, so that power plants cannot operate profitably. However, the postponement of these supply shortages is primarily achieved through an excess supply of German conventional power plants that are utilised to meet excess demand in Spain. Although this serves to reduce required government subsidies, it also leads to an increase in CO2 emissions.

Визначення граничних величин споживання електричної енергії засобами оптимізаційного моделювання

In the heating season of 2022/2023, as a result of the military aggression of the Russian Federation and targeted attacks on electric power facilities, a significant shortage of electric energy occurred in the Integrated power system of Ukraine. Restriction schedules and emergency disconnection of consumers were forcibly applied. In the conditions of such an unprecedented violation of the security of electricity supply, the problem of determining the limit values of electric energy and power consumption has gained new relevance for the electricity market participants. In this study, the problem of determining the optimal limit values of electricity consumption based on the criterion of maximum income from its sale to three groups of consumers was set and solved: "Critical infrastructure", "Households" and "Non-household consumers". The formation of the three specified groups is related to price discrimination in the electricity market and the need to supply critical infrastructure facilities without limits. The decision variables in the optimization model are proposed to be specified in fractions of the provision of electrical energy needs (unit fractions), which allows for establishing equal conditions regarding restrictions for all distribution system operators. To take into account the social significance of electric energy as a commodity, an additional constraint was included to the basic optimization model: the lower limit of the decision variable for the "Households" group. Approbation of the proposed optimization model was carried out using spreadsheet modeling in MS Excel on reported data on the results of electrical load measurements on regime days. The results of computational experiments are presented for the conditions of different values of the deficit of electric energy in the Integrated power system of Ukraine and different values of the additional constraint for the «Households» group, in particular, quantitative estimates of the consequences of the included constraints for the functioning of the electricity market. The proposed method of determining the limit values of electric energy consumption allows to formalize the procedure for decision-making according to predetermined rules and thereby achieve a fair distribution of limited resources. Keywords: electric energy consumption, shortage, limit value, optimization modelling, spreadsheet model.

Centrality Measures to locate the COI of the Mexican Electricity Grid

Centrality measures based on network topology are valuable for decision-making in complex systems. These measures allow the identification of the most essential elements of the network, i.e. those that have the most significant impact on the overall operation of the system. In the case of electricity grids, centrality measurements can be used to identify the most crucial power plants, the most critical transmission lines, or the most vulnerable connection points. This information can be used to improve network planning and control to ensure a reliable and secure electricity supply. In this paper, centrality measures are used to identify those nodes in the Mexican electricity network that are topologically the most relevant. These are used to locate frequency meters that act as critical points for frequency control. Results are presented for an equivalent network of 190 busbars divided into geographical control regions.

Forecasting Renewable Energy Generation Based on a Novel Dynamic Accumulation Grey Seasonal Model

With the increasing proportion of electricity in global end-energy consumption, it has become a global consensus that there is a need to develop more environmentally efficient renewable energy generation methods to gradually replace traditional high-pollution fossil energy power generation. Renewable energy generation has become an important method of supplying power across the world. Therefore, the accurate prediction of renewable energy generation plays a vital role in maintaining the security of electricity supply in all countries. Based on this, in our study, a novel dynamic accumulation grey seasonal model is constructed, abbreviated to DPDGSTM(1,1), which is suitable for forecasting mid- to long-term renewable energy generation. Specifically, to overcome the over-accumulation and old information disturbance caused by traditional global accumulation, a dynamic accumulation generation operator is introduced based on a data-driven model, which can adaptively select the optimal partial accumulation number according to the intrinsic characteristics of a sequence. Subsequently, dummy variables and a time trend item are integrated into the model structure, significantly enhancing the adaptability of the new model to the sample sequence with different fluctuation trends. Finally, a series of benchmark models are used to predict renewable energy generation in China, wind power generation in the United States, and hydropower generation in India. The empirical results show that the new model performs better than other benchmark models and is an effective tool for the mid- to long-term prediction of renewable energy generation.

Implications of environmental constraints in hydropower scheduling for a power system with limited grid and reserve capacity

AbstractThe negative impacts of power systems on biodiversity have to be mitigated, while simultaneously ensuring affordable and secure electricity supply for the future. This may lead to trade-off situations where ecological, recreational or social needs are weighted against the need for flexible power supply. This paper explores the interaction between the security of electricity supply and environmental constraints on the operation of flexible hydropower plants in the Norwegian renewable-based power system. A long-term, stochastic scheduling model of a wind- and hydropower-dominated power system is used to assess the implications of environmental constraints and reserve capacity requirements in combination. The model is used for a representative case study where three types of environmental constraints are imposed on the operation of the hydropower plants in a region of the congested Norwegian power system. In addition, requirements for spinning and non-spinning reserve capacity have to be met. The case study results demonstrate varying impacts on the operation of the hydropower plants, curtailment of demand and provision of reserve capacity depending on the type of environmental constraint being imposed.

Market Design for Cross-Border Co-Optimised Energy-Reserve Allocation

To achieve its energy goals, the European Union (EU) needs to establish a geographically large market by initially improving its cross-border electricity interconnections. The Hungarian project focuses on this topic. A geographically large market, based on imports and exports of electricity, could increase the level of competition, boost the EU’s security of electricity supply through creating alternative routes to the customers and integrate more renewables into energy markets. Electricity should, as far as possible, flow between Member States as easily as it currently flows within Member States, in order to increase sustainability potential and real competition, as well as to drive economic efficiency of the energy system. To this end, Facilitating Regional CROSS-border Electricity Transmission (FARCROSS) aims to address this challenge by connecting major stakeholders of the energy value chain and demonstrating integrated hardware and software solutions that will facilitate the “unlocking” of the resources for the cross-border electricity flows and regional cooperation. The targets of the project are to optimise the usage of the available cross-border capacity for reserve procurement while transitioning from ATC to Flow-based mechanism, to achieve simultaneous interconnector reservation for energy and balancing capacity to enable reserve market coupling and to create state-of-art technologies to materialise market coupling platforms.

Technical versus socio-economic and environmental criteria in power transmission projects

In recent years, the efforts of countries to reach agreements on the development of cross-border electricity interconnection have intensified because they optimize energy resources and constitute the most significant instantaneous support for the security and continuity of electricity supply. In addition, interconnections play a key role in the integration of electricity markets. However, the planning of European electricity infrastructures constitutes complex analyses due to the large number of factors involved. This article applies a multicriteria methodology for the evaluation and prioritization of cross-border interconnection projects with the simulation of different scenarios, in total 12 scenarios, to study the effect of changes in the selected criteria on the results obtained. To test the defined methodology, the variation in the weight of different criteria in the assessment of a new cross-border electrical interconnection project between Spain and France is studied. It was verified that the tool is coherent and that the analysis developed improves the understanding of such large and complex projects and can facilitate the prioritization of project portfolios with a clear and explicit method.

An Efficient Primal-Dual Interior-Point Algorithm for Volt/VAR Optimization in Rectangular Voltage Coordinates

Security and reliability of electrical power supply has become indispensable to modern society, and the system operator is challenged to manage the increasingly complex modern power system in a manner that ensures the expected reliability and security of system operation. In this context, Volt/VAR optimization (VVO) plays a key role in the efficient delivery of power through the transmission system, contributing significantly to the security, reliability, quality and economy of system operation. This article presents the design and implementation of an efficient primal-dual interior-point algorithm for the solution of the VVO problem. The primal-dual interior-point method combines efficient constraint handling by means of logarithmic barrier functions, Lagrangian theory of optimization, and the Newton method to constitute one of the most efficient deterministic algorithms for large-scale nonlinear optimization. The developed algorithm also incorporates the efficient Newton-Raphson load flow computation, which ensures that the solution is feasible with respect to the power flow balance equations at each iteration of the VVO algorithm. Both the VVO and Newton-Raphson load flow problems are formulated in the rectangular coordinates of system voltages. This is a departure from most researchers, who make use of the polar formulation, and adds considerably to the efficiency of the developed algorithm. The efficiency and effectiveness of the developed algorithm has been demonstrated by means of case studies performed on the 6-bus and IEEE 14-bus, 30-bus and 118-bus test systems, which have been selected to analyse the computational efficiency and scalability of the algorithm as it is applied to systems of various sizes. The extensive analyses that have been conducted reveal the developed primal-dual interior-point algorithm’s effectiveness and efficiency, particularly in being able to successfully solve the VVO problem for systems of widely varying sizes without disproportionate increase in computational cost or deterioration in the quality of the results. The developed algorithm exhibits characteristics of fast convergence, high efficiency, and scalability to large-scale problems.

New Power Quality Measurement Techniques and Indices in DC and AC Networks

Currently, we are living through the implementation of the electrical smart grid, a network that can intelligently integrate the actions of all users connected to it in order to efficiently deliver the sustainable, economical and secure supply of electricity [...]

How Dependent Are European Power Systems and Economies on Natural Gas?—A Macroeconomic Optimization for Security of Electricity Supply

How dependent are European power systems and economies on natural gas? To answer this pressing question, we coupled a simulation model for assessing security of electricity supply and an economic optimization model. With this, we were able to analyze different reduction scenarios of the amount of gas utilized in the power sector. Our results show that reducing the amount of natural gas in the European power sector by up to 30% has a relatively moderate impact on the security of electricity supply. Restrictions of 40% or more result in substantially higher reductions in electricity demand shortfall and are associated with economic costs of more than EUR 77 billion. Furthermore, we demonstrate that a close coordination of gas distribution on a European level would be instrumental in mitigating negative economic consequences. Finally, it can be deduced that a coordinated delay of planned power plant shutdowns could effectively compensate for reduced gas volumes in the electricity sector.

Spatial Aggregation of Local Flexibility – Horizon2020 project experiences

With the growth of renewables, the increased interconnection of European grids, the development of local energy initiatives, and the specific requirements on TSO–DSO cooperation as set forth in the different Network Codes and Guidelines, TSOs and DSOs face new challenges that will require greater coordination. The aforementioned measures encourage procurement of services at both the transmission and the distribution level, recognizing that this will enable more efficient and effective network management and will increase the level of demand response and the capacity of renewable generation. Digitalization is a key driver for coordination and active system management in the electricity grid, enabling TSOs and DSOs to optimize the use of distributed resources and ensure a costeffective and secure supply of electricity. It also empowers endusers to become active market participants, supporting selfgeneration and providing demand flexibility. To support the transformation, the INTERRFACE project, started in 2019, will design, develop and exploit an Interoperable pan-European Grid Services Architecture (IEGSA) to act as the interface between the power system (TSO and DSO – transmission system operator, distribution system operator) and the customers, and allow the seamless and coordinated operation of all stakeholders to use and procure common services. This paper describes the approach of one INTERRFACE demonstration, the spatial aggregation of local flexibility and its realization that contributes providing a clear market approach to include local constraints into the already well-established and working wholesale energy market solutions

Energy security – the case of Polish National Power System facing energy transition’s challenges

Energy security plays a key role in energy and economic policy. The importance of energy security has been highlighted by the energy and geopolitical crisis. The aim of this article is to present the crucial threats and challenges facing Polish National Power System, as well as to provide solutions to ensure Poland's energy security over the next 10 years. Article verify the hypothesis that security of electricity supply in Poland may be endangered in the coming years due to, among others, investment gap, coal power plants phase-out and undiversified energy mix. Therefore, it is a necessity to accelerate the investment processes in new generation capacity, especially in nuclear energy. Energy transition plans and energy policy need to be revised in light of the current energy and geopolitical crisis. Rapid growth of photovoltaics improves the energy security, mainly in the summer period, nevertheless, there is still insufficient development of investment in renewable energy sources, particularly in wind energy. In the Polish National Power System there are a lot of constraints such as investment gap, low capacity of transmission and distribution grids and high exposure to climate risk, thus it is necessary to take comprehensive investments to improve energy security in both the short and long term. Key words: Energy security, energy transition, energy crisis, decarbonisation, coal phase-out, energy policy.

Recharging China in War and Revolution, 1882-1955 by Ying Jia Tan (review).

Reviewed by: Recharging China in War and Revolution, 1882–1955 by Ying Jia Tan Zhaojin Zeng (bio) Recharging China in War and Revolution, 1882–1955 By Ying Jia Tan. Ithaca: Cornell University Press, 2021. Pp. 294. China, the largest fossil energy consumer today, recently vowed to decarbonize its economy. The country has announced plans to reach peak emissions in 2030 and carbon neutrality by 2060. These ambitious goals have once again drawn wide attention to the development trajectory of China as a carbon economy. In Recharging China in War and Revolution, 1882–1955, Ying Jia Tan offers a timely account of China's energy history, detailing its electrical development from the late Qing to the early Mao periods. Tan discusses three interrelated aspects of China's electrification: local efforts to secure electricity supply, national strategies to pursue energy independence and economic sovereignty, and, at the planetary level, China's entry through accelerated industrial growth into the Anthropocene Epoch. Framing electrical industries as a central site for power struggles and technological competition, Tan argues that the intertwined processes of infrastructure development and state-building gave rise to resilient political and economic institutions in China after war and revolution. A multilevel analysis of individuals, agencies, and regimes pioneering China's electrical growth, Tan's book sheds new insights on the complex relationship between energy, politics, and state-making in the early twentieth century. [End Page 921] As Tan reveals, China's path toward a carbon-intensive economy stemmed from constant energy crises. Chronic power shortages in everyday life and power loss during wartime became the major impetus for governments and elites to build and control the electrical infrastructure. The engineer-bureaucrats, in particular, brokered the electrification process. They did so while vying for dominance over the new infrastructure. In the Lower Yangtze areas, where cotton mills and silk filatures were concentrated, newly built power stations and grids generated not only electricity but also tensions and conflicts between local elites, government officials, and factory workers. The grip on energy supply allowed the Shanghai Municipal Council to intervene in the labor strikes at the British and Japanese mills. Local power stations also became a weapon for Huzhou industrial elites to fend off the Nationalist government's nationalization efforts. In these two cases, Tan highlights the crucial role of electricity production and consumption in the shaping of everyday politics and nation-building in the early Republican era. Tracing the footsteps of engineer-bureaucrats, Tan continues to examine how wartime electrification centralized state power. The Sino-Japanese War and World War II witnessed a new wave of energy-infrastructure development spearheaded by different authorities: Nationalist China, Imperial Japan, and the United States. In the north, the Japanese regime rationalized coal distribution and reorganized the regional power networks. The Nationalists in the southwest also resorted to a greater degree of state intervention. Tan shows that the Electrical Works represented the Chinese state's remarkable efforts to improve energy efficiency by applying advanced technology, optimizing resource use, and establishing industrial standards. China's wartime energy story also involves the transnational flow of human capital. American dam builders and Chinese engineers made the joint—albeit unsuccessful—attempt to survey the Yangtze Gorges in the hope of reconfiguring China's energy geography. Nevertheless, the war deepened China's coal reliance, making the country march further toward a carbon-intensive economy. Electrical industries transformed into political assets in the postwar years. Failing to appropriate major power plants doomed the Nationalist regime's plan to restore economic and social order. The Communists, by contrast, chose a more cooperative and lenient approach toward engineering elites. In so doing, the new regime turned the electrical infrastructure into the economic foundation for its political rule. Following the founding of the People's Republic, electricity supply further increased, but mostly through labor mobilization and social control rather than new capital investments. Those practices strengthened the state's control over the industries, paving the way for a state-led, labor-intensive developmental approach that descended on the country after 1955. Tan's narrative, ending on the eve of China's accelerated industrial growth, thus invites scholars to [End Page 922] explore how energy continued to propel China...

Assessment of Algeria's electricity power demands during COVID-19 pandemic and wildfires incidents

The COVID-19 pandemic has had enormous negative impacts on several activity sectors such as health, energy, and the economy. Aiming to limit its spread, extraordinary containment measures have been taken by the Algerian government by proclaiming the confinement on March 22, 2020, while maintaining the security of electricity supply to hospitals, critical infrastructures and the households. This manuscript presents a deep analysis of the impacts of the COVID-19 pandemic on the electricity power demands in northern and southwestern Algeria. The analysis covers the period from January 1, 2019, to December 31, 2021, and considers sudden and large changes (increase or decrease) in electricity power demand that may put power system reliability and stability at risk. One promising solution, which can avoid such situations, is to detect the power ramp rate; it is proposed as a power fluctuation indicator. In addition, the analysis also includes the impacts of wildfires that menace most of northern Algeria during the summer of 2021.

A multi-vector community energy system integrating a heating network, electricity grid and PV production to manage an electrified community

Electrification in energy supply–demand plays a critical role in domestic heating and road transport, delivering an electrified community to reduce carbon emissions. This solution, however, places a significant power demand increase on the distribution networks. To ensure the security of electricity supply, an efficient energy system and energy demand reduction are essential. In this paper, a multi-vector community energy system, applying an electrified heating network, electric vehicle smart charging, community-scale peak shaving and photovoltaic (PV) generation, is demonstrated in three models to manage an electrified community. Firstly, a heating network model, comprising a central ground source heat pump, low-temperature district heating system, electric heaters and thermal storage, is established to measure the optimum distribution temperature. Next, an electrified community model illustrates hourly electricity demands and performances of a community energy system, which is then used to identify the required degree of housing thermal efficiency improvement (i.e., heating demand reduction). The third model evaluates decentralised PV/storage units to maintain the power demand below a targeted power. Modelling results show that the demand ratio of domestic hot water to space heating determines the distribution temperature, which indicates the temperature is increasing with growing housing thermal efficiency. Moreover, the electrification of a community could increase the peak power demand on the highest demand day by over five times, converting heating demands into electricity directly. This significant peak demand can be possibly reduced to only a 33% increase by employing a community energy system. The model of PV/storage units is validated through a 12-week assessment. Ultimately, a modelling tool is developed by assembling the mentioned models, providing four pathways to attain electrification. Users can adjust specific parameters and database to align with the local conditions. The results indicate the requirements of building a community energy system and electricity demands in the highest consumption period.

Priorities for tariff compensation of distributed electricity generation in Brazil

The economic, financial, environmental, social, and regulatory impacts of distributed generation influence energy policymaking. In 2012, Brazilian National Electricity Regulation Agency issued Normative Resolution 482/2012 to regulate the access and compensation of energy produced by micro-generation and mini-generation distributed to electric energy distribution systems. The paper aims to contextualize the history of the Brazilian electricity industry and its focus on centralization to demonstrate the need for expanding decentralized (distributed) generation. It is expected to contribute to the discussion about the decentralization of the natural monopoly from the expansion of distributed energy generation and its regulation. It is also expected to contribute to the discussion on the compensation of distributed generation in the electricity tariff in Brazil considering the regulatory basis/update and additional aspects like prosumer as a new player in the electricity market, diversification of renewable sources in the energy and in the electricity matrix, financing of investments in distributed generation, electricity supply versus GDP growth, and security of electricity supply to the country.

Prediction of electricity energy consumption including COVID-19 precautions using the hybrid MLR-FFANN optimized with the stochastic fractal search with fitness distance balance algorithm.

The increase in energy consumption is affected by the developments in technology as well as the global population growth. Increasing energy consumption makes it difficult to ensure electrical energy supply security. Meeting the energy demand can be achieved with the right planning. Proper planning is critical for both economical use of resources and low cost for the end consumer. On the other hand, erroneous estimation of demand may cause waste of resources and energy crisis. Accurate estimation is possible by accurately modeling the factors affecting electricity consumption. Apart from known factors such as seasonal conditions, days of the week and hours, modeling in extreme events such as pandemics that affect all our behaviors increases the success in modeling the future projection. This ensures that the security of electrical energy supply is carried out effectively with limited resources. For this purpose, in this study, a hybrid multiple linear regression‐feedforward artificial neural network (MLR‐FFANN) based algorithm model was proposed, taking into account the estimated impact of the COVID‐19 pandemic on the energy consumption values of Bursa, an industrial city in Turkey. The aim of the hybrid MLR‐FFANN approach was to simultaneously optimize the β polynomial for multiple linear regression and the weight and bias coefficients for the forward propagation neural network using the adaptive guided differential evolution, equilibrium optimizer, slime mold algorithm, and stochastic fractal search with fitness distance balance (SFSFDB) optimization algorithms. The success of the model whose parameters were optimized using the optimization algorithms was determined according to mean absolute error, mean absolute percentage error, and root mean square error evaluation criteria and statistical analysis of these results. According to the results of the analysis, the MLR‐FFANN approach whose parameters were optimized with the SFSFDB algorithm was more successful in the training of the dataset containing the COVID‐19 precautions.

Analysis of Electricity and Natural Gas Security. A Case Study for Germany, France, Italy and Spain

This work aims to present an analysis of electricity and natural gas supply security in the four European Union countries with the highest level of consumption, namely Germany, France, Italy, and Spain. The goal of the study is to use and adapt a set of 22 indicators for estimating the level of energy security. The evaluation of an index called “Energy Security Level”, measuring the overall energy security, is performed for the period 2006–2018 in order to compare its evolution in each of the analyzed countries. The application of the proposed indicator system demonstrates which measures weakened or strengthened energy security in the past. The analysis of the energy security level demonstrates that Germany and France perform better than Italy and Spain in terms of energy security assurance. The main factors for these differences are the rich energy mix for Germany and the massive presence of nuclear power in France. These two elements make German and French energy systems more resilient than the Italian and Spanish ones. The results of sensitivity and uncertainty analysis demonstrate that the initial values of indicator weights have low impact on the uncertainty of energy security level estimations.