Search Results (143)

In the context of the global response to climate change and the active promotion of energy transformation, a number of low-carbon policies coupled with the development of synergies to help power system transformation is an important initiative. However, the insufficient articulation of the green power market, tradable green certificate (TGC) market, and carbon emission trading (CET) mechanism, and the ambiguous policy boundaries affect the trading decisions made by its market participants. Therefore, this paper systematically analyses the composition of the main players in the electricity-CET-TGC markets and their relationship with each other, and designs the synergistic mechanism of the electricity-CET-TGC markets, based on which, it constructs the optimal profit model of the thermal power plant operators, renewable energy manufacturers, power grid enterprises, power users and load aggregators under the electricity-CET-TGC markets synergy, and analyses the behavioural decision-making of the main players in the electricity-CET-TGC markets as well as the electric power system to optimise the trading strategy of each player. The results of the study show that: (1) The synergistic mechanism of electricity-CET-TGC markets can increase the proportion of green power grid-connected in the new type of power system. (2) In the selection of different environmental rights and benefits products, the direct participation of green power in the market-oriented trading is the main way, followed by applying for conversion of green power into China certified emission reduction (CCER). (3) The development of independent energy storage technology can produce greater economic and environmental benefits. This study provides policy support to promote the synergistic development of the electricity-CET-TGC markets and assist the low-carbon transformation of the power industry. Full article

In the context of global climate governance and the low-carbon energy transition, virtual power plant (VPP), a key technology for integrating distributed energy resources, is urgently needed to solve the problem of decentralization and lack of synergy in electricity, carbon, and green certificate trading. Existing studies mostly focus on single energy or carbon trading scenarios and lack a multi-market coupling mechanism supported by blockchain technology, resulting in low transaction transparency and a high risk of information tampering. For this reason, this paper proposes a synergistic optimization strategy for electricity/carbon/green certificate virtual power plants based on blockchain cross-chain transactions. First, Latin Hypercubic Sampling (LHS) is used to generate new energy output and load scenarios, and the K-means clustering method with improved particle swarm optimization are combined to cut down the scenarios and improve the prediction accuracy; second, a relay chain cross-chain trading framework integrating quota system is constructed to realize organic synergy and credible data interaction among electricity, carbon, and green certificate markets; lastly, the multi-energy optimization model of the virtual power plant is designed to integrate carbon capture, Finally, a virtual power plant multi-energy optimization model is designed, integrating carbon capture, power-to-gas (P2G) and other technologies to balance the economy and low-carbon goals. The simulation results show that compared with the traditional model, the proposed strategy reduces the carbon emission intensity by 13.3% (1.43 tons/million CNY), increases the rate of new energy consumption to 98.75%, and partially offsets the cost through the carbon trading revenue, which verifies the Pareto improvement of environmental and economic benefits. This study provides theoretical support for the synergistic optimization of multi-energy markets and helps to build a low-carbon power system with a high proportion of renewable energy. Full article

With the rapid development of China’s electric vehicle industry, the influence mechanism of government policies on consumers’ purchase intentions has become a research focus. This study integrates the technology acceptance model (TAM) and SOR theory to propose four key driving factors: policy incentive, perceived usefulness, perceived ease of use, and test drive experience. Through stratified random sampling of 400 valid questionnaires in Shanghai, Beijing, Shenzhen, and Guangzhou, four cities with a high penetration rate of electric vehicles, the structural equation model (SEM) was used for empirical analysis. The results show that policy incentives have a significant impact on purchase intentions and play a mediating role through perceived usefulness and perceived ease of use; driving experience moderates the effects of perceived usefulness and perceived ease of use on purchase intentions. Based on the research results, this paper proposes a three-stage policy optimization path: strengthening the accuracy of fiscal and tax incentives in the short term, improving the visual construction of the charging network in the medium term, and establishing a network of test drive experience centers in the long term. The research conclusions provide a theoretical basis for the government to formulate differentiated electric vehicle promotion strategies and propose a “policy-technology-service” three-dimensional implementation plan for enterprises to optimize product design and improve user experience, so as to help the sustainable development of China’s electric vehicle market. Full article

This research paper analyses the evolution of electricity price volatility in six European countries between 2015 and 2025, focusing on the relationship between the increasing penetration of renewable energy sources (RES) and short-term price fluctuations. Based on high-frequency data (at 15 min to hourly resolution) on electricity prices, solar and wind generation, and residual load, both year-on-year and structural changes in volatility are quantified. The results show a significant increase in volatility after 2021, with outliers appearing particularly during the 2022 energy crisis, most notably in countries with a high share of RES and limited system flexibility. The analysis identifies non-linear relationships between RES generation and the occurrence of negative prices, with country-specific threshold levels. Annual regression models show that the predictive power of these relationships is time-varying and influenced by externalities. The correlation matrices confirm regional differences in the impact of RES on price dynamics. The results support the design of rules for forecasting risk periods and point to the need for market mechanisms increasing flexibility, including accumulation, demand management, and cross-border integration. Full article

Electricity markets with a high share of variable renewable energy require significant balancing reserves to ensure stability by preserving the balance of supply and demand. However, they were originally conceived for dispatchable technologies, which operate with predictable and controllable generation. As a result, adapting market mechanisms to accommodate the characteristics of variable renewables is essential for enhancing grid reliability and efficiency. This work studies the strategic behavior of a wind power producer (WPP) in the Iberian electricity market (MIBEL) and the Portuguese balancing markets (BMs), where wind farms are economically responsible for deviations and do not have support schemes. In addition to exploring current market dynamics, the study proposes new market designs for the balancing markets, with separate procurement of upward and downward secondary balancing capacity, aligning with European Electricity Regulation guidelines. The difference between market designs considers that the wind farm can hourly bid in both (New 1) or only one (New 2) balancing direction. The study considers seven strategies (S1–S7) for the participation of a wind farm in the past (S1), actual (S2 and S3), New 1 (S4) and New 2 (S5–S7) market designs. The results demonstrate that new market designs can increase the wind market value by 2% compared to the optimal scenario and by 31% compared to the operational scenario. Among the tested approaches, New 2 delivers the best operational and economic outcomes. In S7, the wind farm achieves the lowest imbalance and curtailment while maintaining the same remuneration of S4. Additionally, the difference between the optimal and operational remuneration of the WPP under the New 2 design is only 22%, indicating that this design enables the WPP to achieve remuneration levels close to the optimal case. Full article

With the rapid development of a new power system under the “dual carbon” goal, pumped storage has gained increasing attention for its role in integrating renewable energy and enhancing power system flexibility and security. This study proposes a dynamic benefit evaluation method for pumped storage projects, addressing the limitations of static analyses in capturing the evolving benefit trends. In this paper, the multi-stage dynamic benefit evaluation model was constructed by introducing time-of-use tariffs, periodic capacity pricing mechanism, and ancillary service revenue prediction based on machine learning and the multiple regression method. Sensitivity analysis was applied to explore the impact of key parameter variations on economic indicators. The results show that the benefit structure differs significantly across stages, and with electricity market development, a diversified pattern supported by electricity, capacity, and ancillary service revenues will emerge. The application of the model to an actual operating pumped storage power station yielded an internal rate of return of 8.18%, a payback period of 16.4 years, and a 26% increase in net present value compared with traditional methods. The proposed model expands the theoretical framework for pumped storage benefit evaluation and provides strong support for investment decisions, policy design, and operational strategy optimization. Full article

Diversified application scenarios and business models are effective ways to improve the utilization and economic benefits of energy storage systems. In response to the current problems of single application scenarios, high idle rates, and imperfect price formation mechanisms faced by energy storage on the power generation side, a robust two-stage optimization operation strategy for shared energy storage is proposed, taking into account leasing demand and multiple uncertainties, from the perspective of the sharing concept. A multi-scenario application framework for shared energy storage is established to provide leasing services for wind farm clusters, as well as auxiliary services for participating in the electric energy markets and frequency regulation markets, and the participation sequence is streamlined. Based on the operating and opportunity costs of shared energy storage, a pricing mechanism for leasing services is designed to explore the driving forces of wind farm clusters participating in leasing services from the perspective of cost assessment. Considering the uncertainty of wind power output and market electric prices, as well as the market operational characteristics, an optimized operation model for shared energy storage in the day-ahead and real-time stages is constructed. In the day-ahead stage, a Stackelberg game model is introduced to depict the energy sharing between wind farm clusters and shared energy storage, forming leasing prices, leasing capacities, and energy storage pre-scheduling plans at different time periods. In the real-time stage, the real-time prediction results of wind power output and electric prices are integrated with scheduling decisions, and an improved robust optimization model is used to dynamically regulate the pre-scheduling plan for leasing capacity and shared energy storage. Based on actual data from the electricity market in Guangdong Province, effectiveness verification is conducted, and the results showed that diversified application scenarios improve the utilization rate of shared energy storage in the power generation side by 52.87%, increasing economic benefits by CNY 188,700. The proposed optimized operation strategy has high engineering application value. Full article

With the soaring demand for electric power and the limited spinning reserve in the power system in Taiwan, the comprehensive management of both thermal power generation and load demand turns out to be a key to achieving the robustness and sustainability of the power system. This paper aims to design a demand bidding (DB) mechanism to collaborate between customers and suppliers on demand response (DR) to prevent the risks of energy shortage and realize energy conservation. The concurrent integration of the energy, transmission, and reserve capacity markets necessitates a new formulation for determining schedules and marginal prices, which is expected to enhance economic efficiency and reduce transaction costs. To dispatch energy and reserve markets concurrently, a hybrid approach of combining dynamic queuing dispatch (DQD) with direct search method (DSM) is developed to solve the extended economic dispatch (ED) problem. The effectiveness of the proposed approach is validated through three case studies of varying system scales. The impacts of tie-line congestion and area spinning reserve are fully reflected in the area marginal price, thereby facilitating the determination of optimal load reduction and spinning reserve allocation for demand-side management units. The results demonstrated that the multi-area bidding platform proposed in this paper can be used to address issues of congestion between areas, thus improving the economic efficiency and reliability of the day-ahead market system operation. Consequently, this research can serve as a valuable reference for the design of the demand bidding mechanism. Full article

As the second largest power source in the world, hydropower plays a crucial role in the operation of power systems. This paper focuses on the key issues of regulating hydropower stations participating in the spot market. It aims at the core challenges, such as the conflict of cascade hydro plants’ joint clearing, the lack of adaptability for different types of power supply bidding on the same platform, and the contradiction between long-term operation and the spot market. Through the construction of a water spillage management strategy and settlement compensation mechanism, the competitive abandoned water problem caused by mismatched quotations of cascade hydro plants can be solved. In order to achieve reasonable recovery of the power cost, a separate bidding mechanism and capacity cost recovery model are designed. Subsequently, the sufficient electricity supply constraint of the remaining period is integrated into the spot-clearing model, which can coordinate short-term hydropower dispatch with long-term energy storage demand. The operation of the Yunnan electricity spot market is being simulated to verify the effectiveness of the proposed method. Full article

With the rapid growth of global energy demand, the fossil fuel-dominated electric power industry has led to serious environmental problems. Tradable green certificates (TGC) and carbon emission trading (CET) have become key mechanisms for promoting sustainable development of the electricity market by serving as market-oriented policy tools. To deeply analyze the impact of TGC and CET on the sustainable development of China’s electricity market and provide a scientific basis for policymakers. This study uses system dynamics (SD) methods to construct a policy synergy analysis framework for TGC and CET. It explores the impact mechanism of dual policy incentives on the sustainable development of the electricity market. Firstly, the current application status of TGC and CET in China was reviewed. Based on the literature analysis, identify key factors that affect the sustainable development of the electricity market. Then, by deconstructing the interaction between TGC policy and CET policy, an SD model was established that includes multidimensional feedback such as policy, technology, funding, and market, and the dynamic functional relationships in the SD model were quantified. Finally, Vensim PLE software 7.3.2 was used to simulate the evolution of sustainable development in the electricity market under different policy scenarios. The research results indicate that (1) the adjustment of the TGC quota ratio can change the supply and demand mechanism to form a price leverage effect, effectively stimulate the growth of renewable energy generation capacity, and accelerate the low-carbon transformation of power enterprises; and (2) the CET market changes the cost structure of power generation through carbon price signals. When the carbon emission cap target tightens, CET prices quickly rise, leading to a significant trend of carbon reduction in the electricity market; (3) the application of policy combinations can significantly promote the sustainable development of the electricity market, but the unreasonable setting of policy parameters can trigger market risks. Therefore, policy design should focus on flexibility and implement appropriate policy combinations at different stages of electricity market development to promote green transformation while ensuring smooth market operation. This study innovatively reveals the synergistic effect of TGC and CET in the sustainable development of the electricity market from a systems theory perspective. The research results provide a scientific basis for decision-makers to formulate policy adjustment plans and have essential reference value for achieving the dual goals of energy structure transformation and electricity market stability. Full article

The transition towards renewable energy has increased the importance of virtual power plants (VPPs) in integrating distributed energy resources (DERs). However, questions remain regarding the most appropriate auction mechanisms (pay-as-bid (PAB) versus pay-as-clear (PAC)) and imbalance penalty structures, which significantly influence VPP bidding strategies and market operations. This study employs a three-stage stochastic programming model to evaluate VPP bidding behaviors under these auction mechanisms while also considering the effects of imbalance penalty structures. By simulating various market scenarios, the results reveal that PAC markets offer higher VPP revenues due to settlement at the market-clearing price; they also exhibit greater volatility and elevated imbalance penalties. For instance, power deviations in PAC markets were 52.60% higher than in PAB markets under specific penalty structures, and imbalance penalty cost ranges differed by up to 82.32%. In contrast, PAB markets foster stable, stepwise bidding strategies that minimize imbalance penalties and improve renewable energy utilization, particularly during high- and moderate-generation periods. The findings emphasize the advantages of the PAB mechanism in electricity markets with substantial renewable energy integration, providing significant insights for the design of auction mechanisms that facilitate reliable and sustainable market operations. Full article

To promote the low-carbon energy transition, China is implementing renewable energy (RE) development policies such as renewable portfolio standards (RPSs), carbon emissions trading (CET) and China certified emission reduction (CCER) trading. However, using China’s current CET price to accurately reflect market information is difficult, which is not conducive to guiding low-carbon investment. Additionally, as RE power enters the era of grid parity, more revenues are needed to maintain generator operations. Therefore, in this study, we construct a system dynamics model to explore whether and how market mechanisms can optimize the power generation structure, and sensitivity analyses of CCER policy parameters are carried out to identify the impact and scope for improvement. The results show that (1) the market mechanism, especially the RPS mechanism, adjusts the profits of power generators, eliciting a surge in RE generation and optimizing the power generation structure; (2) CET and CCER prices change in the opposite direction of tradable green certificates (TGCs) and show a significant improvement effect on the on-grid electricity price; (3) successful implementation of the CCER mechanism can effectively energize the CET market. A lower CCER benchmark price, higher CCER offset ratio and CET fines can accelerate the growth of CCER and CET prices. Therefore, the government should promote TGC separation from power trading and rationally design CCER policies by lowering the CCER credit ratio, increasing CET fines, and expanding CCER market capacity to ensure that the guiding role of the market mechanism is better utilized. Full article

This paper examines the transformative effects of decarbonization on electricity market design, emphasizing the challenges and opportunities posed by the rapid integration of renewable energy sources such as wind and solar. It analyzes the evolution of key wholesale market segments—including day-ahead, real-time, capacity, long-term purchase agreements, ancillary services, and transmission markets—highlighting their critical roles in managing the variability of renewable energy generation through efficient price signals and resource coordination. Variable renewable energy integration introduces significant operational challenges, including overgeneration risks, ramping capacity demands, forecast inaccuracies, and transmission constraints. Addressing these issues requires enhanced market flexibility, dynamic pricing mechanisms, and advanced real-time balancing strategies. This paper assesses these challenges, offering strategies to align generation with demand and optimize market outcomes. As electricity systems evolve, legacy market structures must adapt to incorporate carbon-free resources while maintaining grid reliability and economic sustainability. By exploring case studies such as Chile and California, this paper demonstrates the importance of targeted innovations in market design, regulatory frameworks, and operational technologies. It advocates for a holistic approach to ensure a reliable, affordable, and equitable transition to a decarbonized energy future. Full article

With the growing market of secondary batteries for electric vehicles (EVs) and grid-scale energy storage systems (ESS), driven by environmental challenges, the commercialization of sodium-ion batteries (SIBs) has emerged to address the high price of lithium resources used in lithium-ion batteries (LIBs). However, achieving competitive energy densities of SIBs to LIBs remains challenging due to the absence of high-capacity anodes in SIBs such as the group-14 elements, Si or Ge, which are highly abundant in LIBs. This review presents potential candidates in metal pnictogenides as promising anode materials for SIBs to overcome the energy density bottleneck. The sodium-ion storage mechanisms and electrochemical performance across various compositions and intrinsic physical and chemical properties of pnictogenide have been summarized. By correlating these properties, strategic frameworks for designing advanced anode materials for next-generation SIBs were suggested. The trade-off relation in pnictogenides between the high specific capacities and the failure mechanism due to large volume expansion has been considered in this paper to address the current issues. This review covers several emerging strategies focused on improving both high reversible capacity and cycle stability. Full article

Security checks are essential for ensuring the safe operation of the regional power grid (RPG) and the smooth functioning of the electricity spot market (ESM). Currently, China’s RPG operating environment encompasses a complex mix of centralized ESM, decentralized ESM, and planned power generation. This complexity has led to increasingly severe RPG congestion issues. To address this, this paper introduces a security check mechanism design and operational optimization approach tailored for RPGs in complex markets, with a focus on congestion management. Firstly, the paper elaborates on the practical foundations, unique constraints, and requirements for security checks and congestion management during the RPG’s operational mode transitions. Secondly, it outlines the principles underlying the security check mechanism and presents a framework for RPG security checks and congestion management. Through a comparative analysis of three different programs, including their advantages, disadvantages, and applicable scenarios, the paper provides an optimal program recommendation. Building on this, the paper develops an operational optimization method that incorporates congestion management for each of the three security check and congestion management programs. Lastly, an IEEE-39 node test system is simulated to validate the effectiveness of the proposed programs. The mechanism and simulation analysis results show that Program 3, based on market mechanisms, has theoretical and practical advantages over Program 1 (based on multiple adjustments) and Program 2 (based on dispatch plans) for congestion management. Under the same line congestion situation, Program 1 requires two adjustments to relieve the line congestion, while Program 2 and Program 3 can solve the problem with just one optimization adjustment, and the congestion management effect of Program 3 is more obvious and superior. Full article