Electric Power

Cooperative Operation Optimization for Multi-region Hydrogen-Integrated Integrated Energy System Based on Hybrid Wasserstein Two-Stage Distributionally Robust

DING Xiaoqiang, YUAN Zhi, LI Ji

2025, 58(7): 1-14. DOI: 10.11930/j.issn.1004-9649.202410026

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An integrated energy system (IES) coupled with hydrogen energy is significantly influenced by source-load uncertainties when operating alone. Traditional robust optimization techniques are overly conservative, which impedes the economic performance. In order to enhance the robustness and economy of each local IES under multi-region power interactions, this paper puts forward a cooperative operation optimization strategy for multi-region hydrogen-integrated IES based on hybrid Wasserstein two-stage distributionally robust. Firstly, a min-max-min three-layer two-stage distributionally robust optimization model was established based on the fuzzy set of the probability distribution of Wasserstein distance. Secondly, the collaborative cost minimization and optimal pricing problems are formulated by applying enhanced Nash bargaining principles to incentivize active participation from all entities. Finally, we proposed an ADMM-nested distributed C&CG algorithm to solve the problems while preserving privacy. Case study shows that the proposed strategy exhibits good robust performance while enhancing the conservatism of traditional robust optimization techniques, and improves economic efficiency through cooperative operation.

Allocation of Multiple Resources for Integrated Energy System Based on Capacity Value Function

GUO Zhenglin, CHEN Shutong, TIAN Jiawen, CHEN Luan, GUO Zhongjie, HU Weihao, FU Qiang

2025, 58(7): 15-23. DOI: 10.11930/j.issn.1004-9649.202410031

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The integrated energy system is an important carrier for realizing the goal of "double carbon", and economic and efficient collaborative allocation of multiple resources is the prerequisite for realizing sustainable and healthy development of the integrated energy industry. At present, the integrated energy system configuration models mainly aim to minimize costs but seldom consider return on investment. This may prolong the payback period, which leads to lower capital turnover efficiency and increased financial risks. Consequently, this paper firstly proposed the capacity value function of the integrated energy system, which takes the allocated resource capacity as the independent variable and the reduced running cost as the dependent variable to realize the analytic expression of the multi-resource capacity value. Then, a multi-resource collaborative allocation model based on fractional planning theory was established, which aims to maximize the return on investment and construct the best cost-effective allocation strategy. Further, the fractional planning problem, which is difficult to solve, was linearized by the variable substitution technique, and a decomposition iteration algorithm was proposed, to realize the outer approximation of the capacity value function and the efficient solution of the multi-resource collaborative allocation strategy. Finally, by simulation analysis and comparing with the cost minimization method, the effectiveness of the proposed method is verified.

Two-Stage Robust Low-Carbon Economic Optimization for Integrated Energy System Based on Oxy-Fuel Combustion Technology

ZHAO Junxiang, WEN Zhong, WANG Qiujie, ZHANG Yewei

2025, 58(7): 24-37. DOI: 10.11930/j.issn.1004-9649.202504038

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Against the dual backdrop of steadily advancing the "dual carbon" goals and increasing operational uncertainties in integrated energy systems (IES), achieving low-carbon and robust scheduling has become a critical challenge. To address the low-carbon scheduling problem under wind power and load fluctuations, this paper developed a coordinated optimization model that integrates Oxy-fuel combustion carbon capture (OXYCC), hydrogen blending and reward-penalty tiered carbon trading mechanism, and a two-stage robust optimization approach was introduced to enhance the system’s scheduling feasibility and operational stability under uncertainties. The column-and-constraint generation (C&CG) algorithm was employed to improve the model’s computational efficiency. Simulation results show that the proposed model achieves a 29.99% reduction in carbon emissions and a 16.11% decrease in system operational costs, and also maintains strong performance under multi-source fluctuations and disturbances, which verifies its effectiveness and practical applicability in addressing dual objectives of low-carbon operation and robust scheduling.

Low-Carbon and Flexible Scheduling of Integrated Energy Systems Considering Multi-utilization of Hydrogen Energy

ZHANG Hangong, XIE Lirong, WANG Cengceng, REN Juan, BIAN Yifan, HAN Xianchao

2025, 58(7): 38-53. DOI: 10.11930/j.issn.1004-9649.202411086

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In order to improve the economy, low carbon and flexibility of the traditional hydrogen-containing integrated energy system, a low-carbon and flexible scheduling model of integrated energy system with multiple utilization of hydrogen energy is proposed. Firstly, based on an analysis of the source-load dual-side uncertainty, a source-load dual-side uncertainty model was established, and typical source-load dual-side scenarios were generated using the Latin hypercube sampling method and K-means clustering. Secondly, an integrated hydrogen-enabled energy system model was developed with its core comprising carbon capture power plants, multi-utilization hydrogen conversion devices, and energy storage components, to fully exploit the potential of the hydrogen-containing integrated energy system in terms of economy, low carbon and flexibility. Finally, the stepped carbon emission trading mechanism and time of use electricity pricing mechanism were introduced to establish an optimal scheduling model with the objective function of minimizing the sum of economic and environmental costs, and the CPLEX solver was used to solve the model. The case study shows that the proposed integrated hydrogen-enabled energy system model effectively reduces the operating costs and CO₂ emissions, realizing the flexible operation of each energy conversion device and multi-energy complementarity.

Optimal Scheduling of Coal Mine Integrated Energy Systems Considering Stepped Carbon-Green Certificate Mutual Recognition and Gravity Energy Storage

WANG Hui, DONG Yucheng, XIA Yuqi, ZHOU Zilan, LI Xin

2025, 58(7): 54-67. DOI: 10.11930/j.issn.1004-9649.202503063

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To address the issues of low renewable energy accommodation rates, high carbon emissions, and poor operational economy in mining areas of Northwest China, this paper proposes an optimal scheduling model for coal mine integrated energy system (CMIES) that incorporates the mutual recognition of stepped carbon and green certificates, as well as gravity energy storage. Initially, the basic CMIES model was developed by considering the diverse utilization of mine resources, including coalbed methane and gravity energy storage of abandoned mines. Subsequently, to enhance the economic efficiency and energy utilization rate of the CMIES, coupling equipment such as carbon capture, power-to-gas, and combined cooling, heating, and power units was incorporated into the system. Additionally, a flexible load model for electricity, heat, and cooling was established to improve the system's operational flexibility. Furthermore, a mutual recognition mechanism for stepped carbon and green certificates was introduced to encourage the utilization of renewable energy equipment through market interactions. Finally, a mixed-integer programming model was formulated to minimize the total operating cost of the system and was solved using Cplex. The simulation results demonstrate that the proposed model significantly enhances the renewable energy accommodation rate in mining areas while reducing system carbon emissions, striking a balance with operational economics, thereby providing a theoretical foundation for the low-carbon and economically viable transition of CMIES.

Robust Optimization Scheduling of Island Multi-energy Microgrid Considering Offshore Wind Power to Hydrogen

GAO Fangjie, SUN Yujie, LI Yi, LE Ying, ZHANG Jiguang, XU Chuanbo, LIU Dunnan

2025, 58(7): 68-79. DOI: 10.11930/j.issn.1004-9649.202407136

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The offshore wind power to hydrogen technology provides a feasible way to solve the energy consumption needs of remote island users. To address the issues of offshore wind power output uncertainty and single island energy supply mode, this paper proposes a robust optimal scheduling model for island multi-energy microgrid considering offshore wind power to hydrogen using probabilistic box-improved multi-scenario confidence gap decision-making. Firstly, an operation framework for island multi-energy microgrid containing offshore wind power to hydrogen system is designed based on the existing state of island energy use. Secondly, considering the uncertainty of wind power generation and the demand response, a robust optimal scheduling model for island multi-energy microgrid is developed using the probabilistic box theory and the multi-scenario confidence gap decision-making theory, and the grey wolf optimization algorithm is employed to solve the model. Finally, using an island in Guangdong for case study, the simulation analysis demonstrates that the proposed model can significantly improve the wind power consumption, effectively lower the energy-use cost of multi-energy complementarity, and be more economical and environmentally friendly.

Bi-level Optimization Configuration for Offshore Independent Energy Islands Considering Coordination of Multiple Electrolyzers under Uncertainties

KONG Lingguo, TIAN Yangjin, KANG Jiandong, FANG Lei, LIU Chuang, CAI Guowei

2025, 58(7): 80-90, 104. DOI: 10.11930/j.issn.1004-9649.202501027

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With the in-depth development of offshore wind power and the low-carbon advancement of oil drilling platforms, offshore independent energy islands will become a new model for the in-depth consumption of offshore wind power. To address the challenges of frequent start-stop and uneven operation of electrolyzers in offshore independent energy islands due to the uncertainty of offshore wind power, and the complex problem in economic and flexible operation configuration of the multi-coupling of electricity-hydrogen-water-gas, this paper proposes a bi-level optimization configuration method for offshore independent energy islands that considers the coordination of multiple electrolyzers under uncertainty. Firstly, a method for generating complex offshore wind power uncertainty scenarios is proposed based on the K-means algorithm and Monte Carlo simulation. Secondly, a bi-level optimization configuration model is constructed, with the outer layer aiming to maximize benefits and the inner layer considering the coordination of multiple electrolyzers for multi-objective equilibrium optimization control, and the model is solved using an improved particle swarm-Gurobi hybrid approach. Finally, the methods with and without the coordination of multiple electrolyzers, as well as the deterministic and uncertain models are compared through case studies, which verifies the effectiveness and superiority of the proposed method in this paper.

VSG Catastrophe Mechanism Based on Bifurcation and Catastrophe Theories

MA Xiaoyang, YANG Shun, LIU Yu, WANG Xiaobing, WANG Ying

2025, 58(7): 91-104. DOI: 10.11930/j.issn.1004-9649.202501032

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The virtual synchronous generator (VSG) may have problems that the system bifurcation curve changes and the VSG voltage drops or rises due to catastrophe phenomena during operation, which is not conducive to the stable operation of the VSG. To address these problems, a VSG mathematical model with direct current bus capacitor voltage equation as the swing equation was firstly established. Secondly, the catastrophe phenomenon occurring in the VSG under the variations of internal parameters and external operating conditions were respectively discussed and the catastrophe mechanism was revealed based on the bifurcation and catastrophe theories. Then, the parameter stability regions were partitioned and the correctness of the partitioned regions were verified by time-domain simulation. Finally, the effect of catastrophe on VSG's voltage support capacity was analyzed. The results show that the catastrophe occurs through saddle-node bifurcation points and changes with different parameters; the VSG voltage support capability increases when catastrophe occurs with voltage dropping, while the VSG voltage support capability decreases when catastrophe occurs with voltage swelling; within the parameter stability regions, the VSG is not subject to catastrophe.

Distributed Model Predictive Frequency Control of Interconnected Power Systems Considering Demand Response

ZHANG Bohang, QI Jun, XIE Luyao, ZHANG Youbing, ZHANG Boyang

2025, 58(7): 105-114. DOI: 10.11930/j.issn.1004-9649.202408081

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The new type of power system is facing the problem of increasing risk of frequency instability due to reduced inertia and decreased frequency regulation capacity. As a flexible frequency regulation technology, demand response (DR) has become an important means to solve the frequency instability of power systems. Firstly, a frequency stability analysis and load frequency control (LFC) model for demand-side resources participating in frequency regulation of interconnected power systems are established. Secondly, a distributed model predictive control (DMPC) algorithm for demand-side resources participating in frequency regulation of interconnected power systems is designed. The prediction model of DMPC controlling DR to participate in frequency regulation of interconnected power systems is derived, and then the frequency regulation controller of DMPC for interconnected power systems is designed. Finally, the impact of automatic generation control mode, DR mode, DR capacity and DR communication delay on system frequency stability is analyzed through simulation. Simulation examples show that the designed frequency regulation controller has good frequency regulation performance and DR can enhance the system’s frequency transient stability.

Optimization Strategy for Virtual Power Plant Combined Electric Energy and Peak Regulation Market Considering Differentiated Quotation of Power Supply Equipment

SHEN Yunwei, CEN Wenyu, ZHOU Bo

2025, 58(7): 115-127. DOI: 10.11930/j.issn.1004-9649.202412113

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As an effective carrier for new energy to participate in the electric energy market, the advanced market mechanism and the strategy of controlling flexible resources have become the key problems that need to be solved. Based on this, this paper proposes the joint market optimization strategy of virtual power plant energy and peak regulation considering the differentiated quotation mechanism of power supply equipment, and carries out the participation market behavior of virtual power plants including new energy. Firstly, based on carbon trading, green certificate trading and demand response, a differentiated quotation mechanism for different power supply equipment in virtual power plant is proposed to reasonably guide virtual power plant to participate in the market optimization; secondly, to realize the privacy of the quotation information of each equipment; finally, double-layer model with joint optimization formula and CPLEX solver to verify the effectiveness and practicability of the proposed method and model in different environments. The simulation results show that the proposed differentiated quotation mechanism reduces the joint operation cost, with a maximum reduction of 50.34%, and effectively coordinates the interest relationship between the virtual power plant and the joint market.

A Power Grid Fault Diagnosis Method of Online Monitoring System for Relay Protection under Multiple Dimensionality Reduction

CAO Haiou, HU Xiaoli, DAI Wei, HU Jiatong, LI Ping, ZHANG Yue

2025, 58(7): 128-136. DOI: 10.11930/j.issn.1004-9649.202409057

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With the continuous expansion of the power grid, the amount of fault information data is increasing, and the traditional diagnosis scheme is facing the challenge of dimension disaster fault tolerance is also facing challenges. Based on this, a fault diagnosis method for power grid under the condition of multi-level dimension reduction is proposed. Firstly, the power grid dimension diagnosis model considering information modification is constructed, and further dimension reduction is carried out based on the topological structure; then the improved coati optimization algorithm (COA) is used to optimize fault diagnosis model, and the fault auxiliary judgment is carried out by introducing the online monitoring system of relay protection; Finally, the test results of different positioning methods under different optimization algorithms compared, and it is verified that the proposed method has a good positioning effect and convergence speed.

Modified Static Hysteresis Simulation Method for Electrical Equipment with Silicon Steel Core

LIU Ren, ZENG Yu, HU Anlong, TANG Bo

2025, 58(7): 137-146. DOI: 10.11930/j.issn.1004-9649.202503012

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Compared to traditional hysteresis models like Preisach and Jiles-Atherton (J-A), the micromagnetic Landau-Lifshitz-Gilbert (LLG) equation offers advantages such as clearer physical interpretation and higher simulation accuracy. However, its application to macroscopic static hysteresis simulation of electrical steel sheets has been limited due to computational intensity and memory constraints. This paper first proposes a geometric model discretization method for the LLG equation based on the Representative Volume Element (RVE) approach, tailored to the structural characteristics of electrical steel sheets. Subsequently, simplified expressions for the energy terms within the total Gibbs free energy are developed for the millimeter scale. A rapid parameter identification method for the relevant parameters is also introduced. This leads to the derivation of a simplified LLG equation specifically for macroscopic static hysteresis simulation in electrical steel sheets. Finally, the proposed simplified LLG equation is used to simulate static hysteresis loops of industry-grade grain-oriented (GO) and non-oriented (NO) silicon steel sheet samples under various operating conditions. The simulations exhibit strong agreement with measurements. Comparisons in simulation accuracy with the widely applied Preisach and J-A hysteresis models further validate the superiority of the proposed model and methodology.

Grid-Forming Storage Planning for Renewable Energy Bases Considering the Co-optimization of Inertia Response and Primary Frequency Regulation Parameters

TAN Lingling, ZHANG Wenlong, KANG Zhihao, YE Pingfeng, GAO Yehao, ZHANG Yumin

2025, 58(7): 147-161. DOI: 10.11930/j.issn.1004-9649.202411092

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Remote renewable energy bases often lack conventional power sources for support, leading to prominent frequency stability issues. The deployment of grid-forming energy storage systems can effectively enhance frequency stability. However, fixed frequency support parameter settings fail to fully utilize the frequency regulation capability of grid-forming energy storage, resulting in increased configuration requirements to maintain frequency stability. To address this, a bi-level optimization configuration method for grid-forming energy storage is proposed, based on frequency security in renewable energy bases, which considers the optimization of inertia response and primary frequency regulation parameters. The upper-level optimization aims for economic optimality, deriving the grid-forming energy storage configuration scheme while accounting for operational constraints under typical scenarios of renewable energy HVDC transmission. The lower-level optimization targets multiple frequency security metrics under anticipated power disturbances, optimizing the inertia response and primary frequency regulation parameters of the energy storage system. This ensures the frequency stability of the configuration scheme while maximizing the frequency support capability of grid-forming energy storage. Finally, the effectiveness of the proposed optimization method is validated using historical data from a typical scenario in Northwest China.

Microgrid Optimization and Power Quality Improvement Based on Wind-Solar Hybrid Energy Storage System

WANG Yong, WANG Hui, HU Yahan, Zhao Peng, LI Xuenan

2025, 58(7): 162-167. DOI: 10.11930/j.issn.1004-9649.202408026

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With the rapid development of renewable energy, the energy storage system is increasingly important to maintain the power balance of the power grid. A microgrid model for capacity of new energy hybrid energy storage system is established to realize the optimal configuration of storage capacity in the wind-solar complementary microgrid, thereby improving the power supply quality. on the energy mapping relationship, the alternating direction method of multipliers is used to iteratively solve the optimal number of decomposition modes, and the high and low frequency boundary points are selected to the characteristics of supercapacitors and batteries, and the corresponding power is calculated. Case studies show that the proposed method can not only improve the service life of batteries, but reduce the annual comprehensive cost.

Configuration Optimization of Renewable Energy Systems Based on FDOA

ZHAO Lin, GUO Shangmin, SHANG Wenying, DONG Jian, WANG Wei

2025, 58(7): 168-176. DOI: 10.11930/j.issn.1004-9649.202410100

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With the increasing demand for clean energy worldwide, how to optimize the renewable energy system to reduce the dependence on the traditional power grid is becoming increasingly important. An method for renewable energy system based on flow direction optimization algorithm (FDOA) is proposed, which dynamically adjusts the configuration of photovoltaic, wind and pumped storage minimize the grid usage factor and achieve the balance of load demand. The proposed method is verified to have advantages in optimizing complex renewable energy systems through comparison of 6 different configuration scenarios, can provide guidance for the design of future energy systems.

Balancing Control Strategy for Energy Storage Lithium Battery Pack Based on CCS-MPC

ZHOU Kai, TAO Zhengshun, PAN Tinglong, XU Dezhi

2025, 58(7): 177-186. DOI: 10.11930/j.issn.1004-9649.202407037

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Aiming at the issue of inconsistent state of charge (SOC) among lithium battery modules after long-term charging and discharging, traditional centralized balancing circuits suffer from the drawback of low balancing speed. To address this, a balancing control strategy based on continuous control set model predictive control (CCS-MPC) is proposed, utilizing a symmetrical switch array, boost converter, and LC quasi-resonant circuit as the main balancing circuit. Firstly, the balancing system is modeled, and a discrete state-space equation is constructed. Subsequently, a multi-step model predictive algorithm is designed based on the state equation, with the value function defined by the error between the SOC predicted value and the reference value, as well as the difference between the current input and the previous input of the converter’s switching elements. Finally, a quadratic programming is applied to the value function to obtain an optimal control solution online, which is then implemented in the balancing system. By dynamically adjusting the duty cycle, the magnitude of the balancing current is controlled. Compared with single-step prediction, multi-step prediction requires considering the optimality of the controlled variables over multiple cycles, ensuring that the balancer can output the optimal balancing current in each balancing cycle and effectively preventing instability of the balancer. The simulation results show that compared with the conventional PI algorithm, the proposed model prediction algorithm achieves SOC consistency among battery modules, ensures stable output of balancing current, and reduces the balancing time by 17%.

Methodology for Energy Storage Planning Considering Variable Unit Energy Construction Costs

YUAN Zhenhua, ZHANG Lina, ZHANG Yuyue, TIAN Xin, WANG Peng, DU Ershun

2025, 58(7): 187-196. DOI: 10.11930/j.issn.1004-9649.202409040

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Energy storage is a key component in mitigating power fluctuations of renewable energy sources and supporting the construction of new power systems. However, existing energy storage planning methods do not consider the potential dynamic changes in unit energy construction costs during the planning period, but only rely on a constant unit energy construction cost, which is not conducive for power system planners to comprehensively assess energy storage planning strategies. Therefore, this paper proposes an analytical methodology for energy storage planning considering variable unit energy construction costs, aiming to analyze the relationship between the energy storage unit energy construction costs and the energy storage planning results so that power system planners can get more comprehensive and effective information. Firstly, to address the nonlinear characteristics of the energy storage planning model caused by energy storage charging/discharging complementary constraints, a constraint relaxation-based linearization framework for energy storage planning models was proposed, transforming the original nonlinear optimization problem into a precise linear optimization problem. Furthermore, based on the linear optimization formulation of the energy storage planning models, the unit energy construction cost was treated as a variable parameter. Using the multi-parameter planning theory, an analytical mapping function between the unit energy construction costs and the energy storage planning results was derived, enabling quantitative analysis of the relationship. The proposed method was verified through numerical experiments in the IEEE 118-bus test system. The results show that the proposed method can solve the original nonlinear energy storage planning problem with reduced computational burden while maintaining high precision, enabling accurate quantification of the energy storage planning results.

Evaluation of Grid Investment Effectiveness and Investment Simulation for New-Type Power Systems Based on Machine Learning Algorithm

TIAN Xin, JIN Xiaoling, HAN Xinyang, YANG Junwei, ZHANG Xinsheng

2025, 58(7): 197-206. DOI: 10.11930/j.issn.1004-9649.202411008

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The access of emerging elecments such as distributed power generation, energy storage, and microgrids has a great impact on the operation characteristics of the power system. Power grid, as a critical component of new-type power systems, requires that its planning and investment decisions fully account for the emerging elements' impact on investment effectiveness, so as to ensure that the grid investment scale and allocation align with the construction objectives of new-type power systems. At present, evaluation of the power grid investment effectiveness mostly focuses on cost input and economic benefits. The construction of new-type power systems, however, requires that the power grid investment effectiveness be guided by the overall benefits, and the key influencing factors be extracted to provide directional guidance for the power grid investment simulation. This paper proposes a power grid investment effectiveness evaluation and investment simulation method for new-type power systems based on machine learning algorithm, and constructs a power grid investment effectiveness evaluation model based on the machine learning algorithm of the least squares support vector machine (LSSVM), and uses the particle swarm optimization algorithm (PSO) to optimize the parameters of LSSVM. The distributed power generation and energy storage scenarios are used for case study. Based on the quantitative mapping relationship between the physical indicators of the power grid, the power grid investment indicators and the power grid investment effectiveness indicators under the new-type power systems, the power grid investment simulation method and model are established, and case study is carried out using differentiated scenarios to verify the feasibility of the proposed power grid investment simulation method. This study can provide a theoretical and technical support for the power grid investment decision-making for the new-type power systems.

Evolutionary Trend of Grid Functionalized Investment Structure under Composite Scenarios of New Power Systems

LOU Qihe, LI Yanbin, LIU Zishang, XIANG Yue, JIN Xiao

2025, 58(7): 207-216. DOI: 10.11930/j.issn.1004-9649.202408042

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The construction of new power systems has accelerated the evolution of the form, technology, and functions of the power grid, thus enriching the functions of power grid investment. It is therefore necessary to further understand the functional needs of power grid investment, optimize the investment structure, and further support the transformation of the energy and power structure. This paper uses the system dynamics model to study the changing trends of various forms of the source-grid-load power system during the construction of the new power systems, clarifies the evolution trend of power grid infrastructure investment during the construction of the new power systems, and studies the quantitative evaluation method for investment scale to form a power grid investment demand system that can meet both the needs of traditional economic and social development and the needs of new energy rapid development.

Analysis of Three-Part Tariff Mechanism for Cost Pass-Through of Flexibility-Regulated Coal Power Units

WANG Yueping, TAN Qingbo, ZHAO Erdong, TAN Zhongfu, WU Xuehui

2025, 58(7): 217-226. DOI: 10.11930/j.issn.1004-9649.202405001

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To address the risks to the safe and stable operation of the power grid and the challenges in power balance caused by the high penetration of renewable energy, while promoting the effective consumption of renewable energy and alleviating the peak-valley load disparity, this paper proposed a three-part tariff mechanism based on the functional positioning of coal-fired power units. Firstly, we analyzed the three functions provided by the coal-fired power units under the new power systems, including basic power security, consumption of renewable energy and auxiliary service. Secondly, the cost composition of coal power units was analyzed. Thirdly, a three-part tariff mechanism was constructed based on the values provided by the coal-fired power units, including power value, regulation value and capacity value, and cost pass-through was carried out via diversified routes. Finally, a sensitivity analysis of the cost pass-through of coal-fired power units was conducted under different capacity subsidy ratios and auxiliary service prices. The results show that based on a benchmark coal price of 675 yuan/ton, under the scenario of a 30% coal price increase, the total per-kilowatt-hour costs for coal power would be 42.09 cents/(kW·h), 39.73 cents/(kW·h), and 38.16 cents/(kW·h) respectively when implementing no capacity subsidy, 30% subsidy, and 50% subsidy. Compared with the original coal price scenario, these represent increases of 20.9%, 22.4%, and 23.6% respectively. The proposed three-part tariff mechanism can stimulate the initiative of power units in peak shaving, ensure the power units to provide sufficient standby capacity, and incentivize the power units to participate in the system FM service, thus fully stimulating the vitality of the coal power in the power market.

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