Regional Power System Research Articles

Development of an integrated BLSVM-MFA method for analyzing renewable power-generation potential under climate change: A case study of Xiamen

In order to reduce fossil-energy carbon emission and mitigate its climate change impact, developing integrated mathematical methods that are capable of predicting renewable power-generation (e.g., wind and photovoltaic power) potential are desired. This study advances an integrated Bayesian least-squares-support-vector-machine based multilevel-factorial-analysis (BLSVM-MFA) method to find out the main factors affecting wind- and photovoltaic-power generations (WPG and PPG), as well as predict WPG and PPG potentials. The BLSVM-MFA method is then applied to a case study of Xiamen (China), where various factors including climate, economic, technological and capacity are investigated and 216 scenarios are analyzed. Results disclose that the main factors affecting WPG are wind power index (contributing 54.04%) > installed capacity (41.45%) > technology (2.60%), and the main factors affecting PPG are installed capacity (60.36%) > solar radiation (19.27%) > technology (9.24%). Results also reveal that WPG and PPG potentials (in 2020–2035) decrease under most scenarios and WPG and PPG show seasonal complementarity. Ensemble predictions under 216 scenarios indicate that WPG and PPG would be 130.21 WMh and 436.51 MWh by 2035. The promotion of high-conversion and high-profit technologies can improve the competitiveness of WPG and PPG in the regional power system. Results are valuable for revealing the impacts of climate change, economic development, and technological improvement on renewable power potentials and providing support for regional energy-structure transformation and carbon-emission abatement.

Multi-Period Transmission Expansion Planning for Renewables-Rich Power Grid Enabling Transfer Capacity Enhancement of Hybrid AC/DC Interface

With the increasing integration of HVDC tie-lines, the regional power systems in both the energy-exporting area and the energy-importing area have been gradually evolving into “strong DC, weak AC” systems. In this paper, a multi-period transmission expansion planning optimization model is proposed for an energy-exporting power grid with hybrid AC/DC interface. While the existing literature has not considered the dynamic security problem in TEP, this paper adopts the conventional total transfer capacity (TTC) index to evaluate the security limit of hybrid AC/DC interface under different transmission expansion schemes. Multiple objectives are considered to reduce the investment cost while promoting the consumption of renewables by enhancing the total transfer capacity of hybrid AC/DC interface. The non-dominated sorting genetic algorithm-II (NSGA-II) is used to compute the optimal solution for the proposed multi-period multi-objective transmission expansion planning problem. A case study on the modified IEEE 39-bus system is presented to demonstrate the effectiveness of the proposed method.

The Adverse Effects of the Outbreak of Russia-Ukraine Conflict on the Energy Supply System of Europe

Energy is the foundation of modern civilization and national prosperity. The production, distribution and utilization of energy have become an indispensable pillar in the world economic structure and influence the development of international relations. However, due to the deterioration of the earth's environment, issues such as climate change have become a common concern all over the world. The international community needs to build a new order of energy transformation, from the use of fossil energy to the choice of natural gas as a transitional energy, and finally make renewable energy become dominant. In this context, carbon neutrality has been proposed and has gradually become a political chip in the new pattern since the 21st century, which is highly colored by geopolitical games. Regional power system integration, control of mineral resources and energy trade layout become the trend, so the traditional energy exporters try to realize the energy as possible diplomatic leverage before the energy transition, and countries and organizations trying to become leaders of the energy transition put forward the new concept of carbon border tax, trying to further implement new forms of international intervention of carbon intervention. This phenomenon has been demonstrated incisively and vividly in the Russia-Ukraine full-scale conflict since February24, 2022, that is, the impact of international security situation and relations on energy supply, among which the most severely damaged is undoubtedly the European Union. This paper will analyze the adverse effects of the outbreak of Russia-Ukraine conflict on the energy supply system of Europe from three perspectives.

Research on fault reconstruction of ship regional distribution System based on improved genetic algorithm

To ensure that the power supply can be restored quickly when the ship’s power system fails, the fault reconstruction method of the system is studied. Taking the number of switching operations and load loss as the objective function, the traditional genetic algorithm is improved by introducing a Tent population initialization, adaptive crossover probability, and mutation probability to realize the fault reconstruction of the ship regional distribution system. Two reconstruction examples show that the improved genetic algorithm can effectively solve the reconstruction problem of the ship’s regional distribution power system, and has good convergence speed and accuracy, which can ensure the stable operation of the ship power system.

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia.

A Linear Chance-Constrained Mixed-Integer Programming Model for Optimizing Regional Electric Power Systems under Carbon Constraints

In view of increasing population size and energy consumption, greenhouse gas (GHG) emissions are increasing and are one of the main causes of climate change. The regional electric power system is one of the main sources of carbon emissions, so there is an urgent need to optimize the regional electric power system to meet the Paris Agreement's long-term temperature goal. Therefore, this study provided a linear chance-constrained mixed-integer programming (LCMI) model with the objective of maximizing the total system profit and applying it to the regional electric power system. Chance-constrained programming and mixed-integer programming were integrated into the LCMI model to address input uncertainties. Including five commonly used power generation technologies, namely coal-fired, natural gas-fired, hydropower, wind power, and solar power, the model can provide the optimal electricity generation schemes and capacity expansion plans for different technologies at the regional level to meet the end-user’s needs while meeting the carbon dioxide emission targets under different risk levels. The outcomes of the research will offer decision-makers a framework for optimizing conventional regional electric power systems for their long-term sustainability in environmental and economic development.

Концептуальное представление энергетического перехода в электроэнергетике региона в новых реалиях

The energy transition is a global problem affecting environmental and energy security, sustainable economic development, social well-being. However, since its implementation differs in certain regions, it is necessary to develop specific approaches that consider local factors, external threats and risks. The article proposes a conceptual vision of energy transition at the regional level in the context of crisis, economic and logistical changes, and socio-economic, scientific and technical transformations. It is hypothesised that in order to implement the energy transition, a compensation method is required to ensure the equivalence of environmental, economic and technical results. The study analysed expert opinions published in foreign and Russian journals indexed in the SCOPUS, Science Direct, MDPI, WIT Press databases, as well as analytical reports of international energy agencies and consulting firms. The analysis revealed that the most appropriate form of organisation of the regional electric power system is a flexible model combining system and regional circuits and involving power plants with a wide range of generating capacities. The integrated power system and decentralised energy sources are seen as energy transition objects. The study presented an energy transition scheme from the implementation of low-cost energy demand management measures to the reconstruction of coal-fired power plants and construction of renewable energy facilities. An ideal model of the regional electric power system was developed as a strategic guideline in the energy transition implementation. Possible scenarios and stages of the energy transition were discussed. The findings can be applied by government and industry regulators, energy companies, large electricity consumers when planning structural, organisational and market transformations in the regional energy sector under uncertainty.

Capacity Allocation of Hybrid Power System with Hot Dry Rock Geothermal Energy, Thermal Storage, and PV Based on Game Approaches

This study utilizes hot dry rock (HDR) geothermal energy, which is not affected by climate, to address the capacity allocation of photovoltaic (PV) -storage hybrid power systems (HPSs) in frigid plateau regions. The study replaces the conventional electrochemical energy storage system with a stable HDR plant assisted by a flexible thermal storage (TS) plant. An HPS consisting of an HDR plant, a TS plant, and a PV plant is proposed. Game approaches are introduced to establish the game pattern model of the proposed HPS as the players. The annualized income of each player is used as the payoff function. Furthermore, non-cooperative game and cooperative game approaches for capacity allocation are proposed according to the interests of each player in the proposed HPS. Finally, the proposed model and approaches are validated by performing calculations for an HPS in the Gonghe Basin, Qinghai, China as a case study. The results show that in the proposed non-cooperative game approach, the players focus only on the individual payoff and neglect the overall system optimality. The proposed cooperative game approach for capacity allocation improves the flexibility of the HPS as well as the payoff of each game player. Thereby, the HPS can better satisfy the power fluctuation rate requirements of the grid and increase the equivalent firm capacity (EFC) of PV plants, which in turn indirectly guarantees the reliability of grid operation.

THE EVOLUTION OF THE ENERGY SYSTEMS OF UKRAINE AND THE ORGANIZATION OF MANAGEMENT ACCOUNTING IN ENERGY COMPANIES IN CONDITIONS OF RISK

An essential prerequisite for the development of Ukraine is a rationally formed energy system that covers the electricity demand of society and assures the smooth functioning of the national economy. The study presents the characteristics of different types of power plants in Ukraine, such as thermal, hydraulic, nuclear, geothermal, and tidal. Furthermore, the share of Ukraine’s contribution to the energy supply of other countries is indicated. Today, the United Energy System of Ukraine is one of Europe’s most significant energy com- plexes with seven regional electric power systems (REES), including Dnipro, Western, Crimean, Southern, Southwestern, Northern, and Central. The research presents the structure of electricity consumption by consumer groups in Ukraine. It indicates the extent of the destruction of Ukraine’s energy capacities by Russia’s invasion. The issue of developing electricity production from alternative energy sources in Ukraine is discussed. Permanent risks and the threat of destruction of energy system objects encourage managers of economic entities to carefully search for quick and accurate problem-solving tools for avoiding critical situations. The accounting system, in particular, management accounting, provides the in- formational component that satisfies the timeliness of providing boards with recommendations on making managerial decisions. The study highlights and describes the stages of implementation of management accounting in energy supply companies in Ukraine. The effectiveness of management accounting in this aspect is emphasized.

A bi-level optimal scheduling model for new-type power systems integrating large-scale renewable energy

Abstract The construction of a new type of power system is a key way to achieve the goal of ‘carbon peaking and carbon neutrality’. In the process of developing renewable energy, large-scale wind and photovoltaic power systems replace conventional units, which will have an impact on the stability of the power grid. To eliminate these concerns, this paper proposes a bi-level optimal scheduling model for new-type power systems. The upper level aims to minimize fluctuation of net load, with the consideration of demand response, to smooth the load curve. The lower level takes the minimum operating cost of the new-type power system as the objective function and the most economical scheduling strategy is established. To deal with the uncertainty of renewable energy integrated within the system, the lower model is transformed into a two-stage robust optimization model and solved by applying a column-and-constraint generation method. Finally, a regional power system is selected to conduct a case study comprising 760 MW thermal power, 50 MW·h energy storage, 200 MW wind turbine and 150 MW photovoltaic power. The results show that the constructed two-stage robust optimization model is conducive to establishing the most economical scheduling scheme of the system with an uncertain budget and the minimum operation cost is $45,9031. In addition, demand response and energy storage can reduce peak-to-valley differences in the power system.

Low-Carbon Transition Pathway Planning of Regional Power Systems with Electricity-Hydrogen Synergy

Hydrogen energy leads us in an important direction in the development of clean energy, and the comprehensive utilization of hydrogen energy is crucial for the low-carbon transformation of the power sector. In this paper, the demand for hydrogen energy in various fields is predicted based on the support vector regression algorithm, which can be converted into an equivalent electrical load when it is all produced from water electrolysis. Then, the investment costs of power generators and hydrogen energy equipment are forecast considering uncertainty. Furthermore, a planning model is established with the forecast data, initial installed capacity and targets for carbon emission reduction as inputs, and the installed capacity as well as share of various power supply and annual carbon emissions as outputs. Taking Gansu Province of China as an example, the changes of power supply structure and carbon emissions under different scenarios are analysed. It can be found that hydrogen production through water electrolysis powered by renewable energy can reduce carbon emissions but will increase the demand for renewable energy generators. Appropriate planning of hydrogen storage can reduce the overall investment cost and promote a low carbon transition of the power system.

SVM based imbalanced correction method for Power Systems Transient stability evaluation

Due to the requirement of safety and reliability in power systems, unstable samples in the real system are rarely appeared. The evaluation results of the model trained by these imbalance samples have a certain preference. Generally, the imbalance in quantity is taken into account, while the imbalance in quality is ignored. Faced with such a problem, an imbalanced correction method based on support vector machine (SVM) is proposed. Firstly, the classification hyperplane trained by SVM and the normalized Euclidean distance between each sample and the classification hyperplane are calculated so as to obtain their fault severity. Based on this, training samples can be grouped to multilevel sets. Then, the original stacked sparse auto-encoder (SSAE) are pretrained to quantify the imbalance between two classes of samples in multilevel sets. Subsequently, in order to improve the imbalance of training samples, a cost-sensitive correction matrix is generated according to the imbalanced information of multilevel sets. Finally, the loss function of SSAE is modified by cost-sensitive correction matrix to establish the final classifier. Simulation results in IEEE 39-bus system and the realistic regional power system of Eastern China show the high performance of the proposed imbalanced correction method.

Role of digitalization in energy storage technological innovation: Evidence from China

Booming digital technologies have brought profound changes to the energy sector. Digitalization in energy storage technology facilitate new opportunities toward modernized low-carbon energy systems. This study offers a technological perspective to help understand the role of digitalization in energy storage development. We depict the landscape of convergence between digital and energy storage technologies based on a patent co-classification analysis and investigate the impact of the digital transformation on energy storage innovation through a firm-level empirical analysis. Our findings demonstrate a significant upward digital trend in energy storage technology, with main interaction fields ranging from daily life power supplies to regional energy power systems. Meanwhile, digitalization positively promotes technological innovation in energy storage, of which digitization and Internet of Things strategy make more decisive contributions. We provide implications for the achievement of cross-regional energy systems through the internal coordination between energy storage and digitalization. The findings shed light on the coordinated development of digitalization and energy system toward a more sustainable and smart society.

A control strategy for improving power system resilience in N-k contingency

With the global climate change, the frequency of extreme weather is getting higher and higher, and the threat to the safe operation of the power system is gradually increasing, which is likely to cause large-scale power outages and then result in N-k contingencies. Meanwhile, the Modular Multi-level Converter (MMC) based Multi-Terminal High Voltage Direct Current (MTDC) power system has been confirmed that can provide the possibility for the network interconnection between regional power systems and various renewable energy resources to boost supply reliability and economy. To enhance the resilience of the power grid, a generation rescheduling scheme by optimal emergency control that considers the risk-based dynamic security constraint and reactive power constraints is proposed. Based on the transient stability criterion of the rotor angle speed of the center of inertia (COI), the active power is adjusted to improve the transient stability of the system. The usefulness of the proposed control strategy is highlighted on a 10-machine-39-bus hybrid power system built on MATMTDC, a MATLAB-based open-source software. The obtained results demonstrate that the state optimization control strategy is capable of enhancing the resilience of hybrid power systems and improving the transient stability when suffering N-k contingencies.

Assessing the integration effect of inter-regional transmission on variable power generation under renewable energy consumption policy in China

Integrating a high share of variable renewable energy into multi-region power systems is essential and requires an interconnected transmission grid to coordinate regional power system operations. This paper proposes a multi-region power system optimization model to evaluate the role of interconnection in China's power sector for economic benefit, variable renewable energy power generation and allocation, transmission line efficiency and carbon emission transfer in the context of renewable energy consumption policy. The results show that inter-regional power transmission coupled with flexibility technology can facilitate renewable power generation and delivery. The renewable energy consumption policy would intensify this effect, although it leads to a slight drop in economic efficiency. Improving the compatibility of transmission network with variable power is crucial because wind and solar power are expected to make up 60% of the total inter-regional power transmission, particularly the share in the outward transmission lines from the northwest region reaching 91%. Renewable energy integration policy targets in northwest, north, Inner-Mongolia and northeast regions can be improved to 37.5%, 31.5%, 35.3%, and 36.9%, respectively.

Analysis of grid-connected operation characteristics and limit access capacity of offshore wind farms

Wind power is a relatively ripe renewable energy power generation technology, which has the superiority of large-scale development and utilization. Large-scale deep-sea wind farms are a significant direction for wind power development. With the continuous growth of the capacity of a single offshore wind farm, it is necessary to study the impact of grid connection of large-capacity offshore wind farms on the normal operation of the power grid, which can guarantee the safety and stability of the power grid. Based on the smooth working of the power system, it is meaningful to determining the limit access capacity of offshore wind farms for guiding offshore wind power planning. In this paper, an evaluation index system for the operation characteristics of offshore wind farms integrated into regional power grids is constructed, and based on that, the influence of offshore wind farms on the safety, stability, economy and power quality of regional power system operation is studied, and the grid-connected power limit of offshore wind farms is further calculated.

Capacity value analysis of interruptible loads in regional power systems with intermittent renewable energy

The proportion of renewable energy is increasing rapidly to develop low-carbon power systems and the intermittence nature of renewable energy harms the security operation of power systems. The participation of interruptible loads is an effective means to handle the intermittence of renewable energy. However, the capacity value of interruptible loads has not been fully recognized, which results in limited involvement of interruptible loads in power system operations. Hence, it is urgent to analyze the capacity value of interruptible loads. In this paper, a capacity value calculation method of interruptible loads is proposed. A joint optimal operation model of interruptible loads and multiple power sources including thermal power units, hydropower units, and wind turbines is established to realize the application paradigm of power system operations with interruptible loads. Case analysis based on the operation data of the power system in a particular area verifies that the proposed method can effectively recognize the capacity value of interruptible loads and reduce the installed capacity of thermal power units. It thereby lays the theoretical foundation for analyzing the role of interruptible loads in the low-carbon transition of the electric energy industry.

Інформаційна система моніторингу динаміки розвитку альтернативної електроенергетики

The article proposes and substantiates an original approach to the design of a monitoring information system of the state and dynamics of development of generating facilities of regional energy systems, which include an ever-growing number of power plants based on renewable energy sources. The development of a new system for describing these power plants by expanding the list of indicators of their functioning is a distinctive feature of the proposed approach. In contrast to the description of the indicators of the facilities of electricity producers of the centralized power system, their detailing at the level of regional power systems regarding the types of energy resources used for power generation, as well as the characteristics of their connection to (high-voltage or distribution) power transmission networks, was added. The main purpose of the information system proposed for development has been defined - it is the formation of an information resource that is updated for solving the assignments of modeling pricing processes in the electric energy market and developing regulatory mechanisms for stimulating the development of renewable energy at the level of regional energy systems of the United Energy System of Ukraine.

A GAN-Based Fully Model-Free Learning Method for Short-Term Scheduling of Large Power System

In order to reduce the dependence on accumulated experience that is difficult to replicate for the human dispatchers to make power generation scheduling more automatically, quickly, and intelligently, higher requirements are placed on the level of the auxiliary decision-making system. In this paper, a short-term scheduling problem was treated as a regression task that concentrates on how to learn a reliable statistic model that concludes the intrinsic logic of the dispatching policy from extensive historical dispatching experience. In this way, since Kullback-Leibler distance can better measure the distance between two distributions, we designed a novel GAN-based learning method for the scheduling task. Also, we proposed a feasible framework that combines the stage of learning, decision-making, and deployment to support the practical implementation of the proposed algorithm. In the experiment, a real case that takes short-term scheduling tasks on a regional large-scale power system is considered in our experiments. As a result, the comparison of several methods further shows the superiority of the proposed GAN-based method under our implementations.

Probabilistic power flow calculation considering electro-thermo-mechanical dynamics of overhead conductor

Conductor temperature and tension are important physical states that determine the security of the overhead line. The states are sensitive to the line power flow and the meteorological conditions around the conductor that have strong uncertainty. In this paper, the electro-thermo-mechanical coupling dynamics of the power system are modeled. Then, focusing on the calculation of the distributions of the electro-thermo-mechanical dynamics (ETMDs) of critical spans under the uncertain operational environment of the power system, the implementation framework and the fast calculation methods for the probabilistic power flow considering electro-thermo-mechanical dynamics (PPF-ETMD) are proposed. The work presented in this paper provides an effective method for operators to capture distributions of the ETMDs of critical spans under the uncertain environment and detect the underlying system security risk based on the thermal and mechanical essence of the security of the overhead line. Numerical simulations based on a regional power system in China and the IEEE 300-node system are carried out to verify the effectiveness of the proposed method.