Search Results (70)

With the support of the dual-carbon strategy and related policies, China’s offshore wind power has experienced rapid development. However, constrained by the inherent intermittency and volatility of wind power, large-scale expansion poses significant challenges to grid integration and exacerbates government fiscal burdens. To address these critical issues, this paper proposes a multi-market coupling trading model integrating energy storage-equipped offshore wind power into electricity–carbon–green certificate markets for large-scale grid networks. Firstly, a day-ahead electricity market optimization model that incorporates energy storage is established to maximize power revenue by coordinating offshore wind power generation, thermal power dispatch, and energy storage charging/discharging strategies. Subsequently, carbon market and green certificate market optimization models are developed to quantify Chinese Certified Emission Reduction (CCER) volume, carbon quotas, carbon emissions, market revenues, green certificate quantities, pricing mechanisms, and associated economic benefits. To validate the model’s effectiveness, a gradient ascent-optimized game-theoretic model and a double auction mechanism are introduced as benchmark comparisons. The simulation results demonstrate that the proposed model increases market revenues by 17.13% and 36.18%, respectively, compared to the two benchmark models. It not only improves wind power penetration and comprehensive profitability but also effectively alleviates government subsidy pressures through coordinated carbon–green certificate trading mechanisms. Full article

Our research analyzes the design of an auction model for railway transportation on the South-East Railway of Peru, managed by Ferrocarril Transandino S.A. (Fetransa) and operated by PeruRail. Initially, the regulatory framework aimed to promote competition in railway transportation through timetable auctions and infrastructure access. However, the concession has resulted in a vertically integrated structure that favors PeruRail, which faces minimal direct competition, controls high-demand time slots, and hinders the entry of other operators due to strategic and structural access barriers. To address these distortions, we propose reforming the auction mechanism to neutralize these advantages and enhance competition. In this revised framework, the track usage fee will serve as the competitive factor, with the highest bid above a minimum base rate securing the allocation. Additionally, we propose the implementation of asymmetric tariffs to compensate for the higher costs faced by operators with fewer economies of scale, technological optimizations to facilitate equitable access to time slots, and stricter oversight mechanisms to ensure transparency in timetable allocation. These measures aim to balance the market and safeguard competition through a more equitable and efficient auction design. 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

The European Union continues to lead global efforts toward climate neutrality by developing a cohesive regulatory and market framework for alternative fuels, including renewable hydrogen. This review article critically examines the recent evolution of the EU’s policy landscape specifically for hydrogen as a renewable fuel of non-biological origin (RFNBO), highlighting its growing importance in hard-to-abate sectors such as industry and transportation. We assess the interplay of market-based mechanisms (e.g., EU ETS II), direct mandates (e.g., FuelEU Maritime, RED III), and support auction-based measures (e.g., the European Hydrogen Bank) that collectively shape both the demand and the supply of hydrogen as RFNBO fuel. The article also addresses emerging cost, capacity, and technical barriers—ranging from constrained electrolyzer deployment to complex certification requirements—that hinder large-scale adoption and market rollout. The article aims to discuss advancing and changing regulatory and market environment for the development of infrastructure and market for hydrogen as RFNBO fuel in the EU in 2019–2024. Synthesizing current research and policy developments, we propose targeted recommendations, including enhanced cross-border coordination and capacity-based incentives, to accelerate investment and infrastructure development. This review informs policymakers, industry stakeholders, and researchers on critical success factors for integrating hydrogen as a cornerstone of the EU’s climate neutrality efforts. Full article

While tradable green certificates (TGCs) and carbon emission trading (CET) play key roles in achieving peak carbon and carbon neutrality, the coupling effects between these two policies on the medium- and long-term electricity market and the spot market are still uncertain. In this study, we firstly construct a multi-scale market trading framework to sort out the information transfer of four markets. Secondly, we establish a multi-scale market system dynamics-coupled trading model with five sub-modules, including the medium- and long-term power markets, the spot market, and the carbon market. Subsequently, we adjust the policy parameters (carbon quota benchmark price, carbon quota auction ratio, and renewable energy quota ratio) and set up five policy scenarios to compare and analyze the impacts of the CET and TGC mechanisms on the power market and carbon emission reduction when they act alone or in synergy, in order to provide a theoretical basis for the adjustment of strategies of market entities and the setting of parameters. The results show that CET can increase spot electricity prices and promote renewable energy to enter the spot market, while TGCs can promote a high proportion of renewable energy consumption but lower spot electricity prices for a long time. The coordinated implementation of the CET and TGC mechanisms can improve the power market’s adaptability to high renewable energy penetration, but it may also result in policy redundancy. Full article

This paper aims to develop an optimisation-based price bid generation mechanism for the sellers and buyers in a double-auction-aided peer-to-peer (P2P) energy trading market. With consumers being prosumers through the continuous adoption of distributed energy resources, P2P energy trading models offer a paradigm shift in energy market operation. Thus, it is essential to develop market models and mechanisms that can maximise the incentives for participation in the P2P energy market. In this sense, the proposed approach focuses on maximising profit at the sellers, as well as maximising cost savings at the buyers. The bids generated from the proposed approach are integrated with three different market clearing mechanisms, and the corresponding market clearing prices are compared. A numerical analysis is performed on a real-life dataset from Ausgrid to demonstrate the bids generated from sellers/buyers, as well as the associated market clearing prices throughout different months of the year. It can be observed that the market clearing prices are lower when the solar generation is higher. The statistical analysis demonstrates that all three market clearing mechanisms can achieve a consistent market clearing price within a range of 5 cents/kWh for 50% of the time when trading takes place. Full article

An efficient energy management system (EMS) enhances microgrid performance in terms of stability, safety, and economy. Traditional centralized or decentralized energy management systems are unable to meet the increasing demands for autonomous decision-making, privacy protection, global optimization, and rapid collaboration simultaneously. This paper proposes a hierarchical multi-layer EMS for microgrid, comprising supply layer, demand layer, and neutral scheduling layer. Additionally, common mathematical optimization methods struggle with microgrid scheduling decision problem due to challenges in mechanism modeling, supply–demand uncertainty, and high real-time and autonomy requirements. Therefore, an improved proximal policy optimization (PPO) approach is proposed for the multi-layer EMS. Specifically, in the centrally managed supply layer, a centralized PPO algorithm is utilized to determine the optimal power generation strategy. In the decentralized demand layer, an auction market is established, and multi-agent proximal policy optimization (MAPPO) algorithm with an action-guidance-based mechanism is employed for each consumer, to implement individual auction strategy. The neutral scheduling layer interacts with other layers, manages information, and protects participant privacy. Numerical results validate the effectiveness of the proposed multi-layer EMS framework and the PPO-based optimization methods. Full article

Municipal solid waste (MSW) management in Spain, particularly in the Valencian Community, heavily relies on mechanical–biological treatment (MBT) plants followed by landfill disposal. These MBT facilities utilize mechanical processes like shredding, screening, and sorting to segregate recyclables (metals, plastics, paper) from organic material and other nonrecyclables. While public funding supports these plants, private entities manage them through complex, long-term concession contracts. This structure restricts access to crucial data on the sale prices of the byproducts generated during MBT. Publicly available information on relevant company and administration websites is typically absent, hindering transparency surrounding byproduct revenue. This study addresses this gap by analyzing 2012’s available data on revenues obtained from byproduct sales following mechanical treatment at MBT plants within the Valencian Community and comparing them with Spanish national data. This research revealed a significant finding—the statistical distribution of average prices obtained from Ecoembes auctions in the Valencian Community mirrored the corresponding distribution for prices calculated from auctions conducted in other Spanish regions. This suggests a potential uniformity in byproduct pricing across the country. It has also been found that none of the analyzed price distributions exhibited a normal (Gaussian) distribution. The findings also highlight the need for alternative pricing models that move beyond simple averages and account for regional variations and outliers. As actual prices are not available after 2012, this lack of transparency poses a challenge in comprehensively evaluating the economic viability of MBT plants. Furthermore, it raises concerns regarding whether the revenue generated from byproduct sales reflects fair market value. Limited public access to this information can potentially indicate conflicts of interest or inefficiencies within the waste management system. Full article

To address the centralized trading demand within industrial parks and the scattered peer-to-peer trading demand outside industrial parks, this paper proposes a blockchain-based joint auction architecture for distributed energy in microgrids inside and outside industrial parks. By combining blockchain technology and auction theory, the architecture integrates the physical energy transactions within industrial parks with the distributed transactions in external microgrids to meet the centralized trading demand within industrial parks and the scattered peer-to-peer trading demand outside industrial parks, optimizing resource allocation and improving system resilience. In the microgrid auction mechanism for industrial parks, considering distributed energy providers (sellers) and distributed energy buyers, an auction mechanism with power transmission distance, average electricity price, and enterprise nature as its main attributes was constructed to maximize social welfare, realizing efficient energy flow in a multi-microgrid environment and enabling coordinated mutual benefits for producers and consumers within the region. Finally, a case study was conducted on the joint auction mechanism for microgrids inside and outside industrial parks, including the impacts of market dynamics and user preferences on electricity prices using different trading methods, the computational results using different trading matching methods (comparing single-attribute and multi-attribute methods), and multi-dimensional verification of user satisfaction with peer-to-peer transactions in a blockchain environment. The effectiveness of the joint trading between physical energy transactions within industrial parks and external microgrids was demonstrated, which could efficiently coordinate energy allocation inside and outside the parks and reduce the cost of energy configuration. Full article

Renewable energy, such as wind power and photovoltaic power, has uncertain and intermittent characteristics and zero marginal cost characteristics. The traditional power market mechanism is difficult to adapt to the new power system with a high proportion of renewable energy, and the original market system needs to be reformed. This paper discusses the application of a VCG auction mechanism in the electricity market, proposes a two-stage VCG market-clearing model based on the VCG mechanism, including the day-ahead market and the real-time market, and discusses the nature of the VCG mechanism. In order to address the discrepancy between the actual output of stochastic generator sets in the real-time market and their pre-scheduled output in the day-ahead market due to prediction deviations, a method for calculating punitive costs is proposed. A reallocation method based on market entities’ contributing factors to budget imbalance is proposed to address the issue of budget imbalance under the VCG mechanism, in order to achieve revenue and expenditure balance. Through an example, the incentive compatibility characteristics of the VCG mechanism are verified, the problems of the locational marginal pricing (LMP) mechanism in the stochastic electricity market with a high proportion of renewable energy are analyzed, the electricity prices of the LMP mechanism and the VCG mechanism under different renewable energy proportions are compared, and the redistribution of the budget imbalance of the VCG mechanism is analyzed. Full article

The data economy has arisen in most developed countries. Instruments and tools to extract knowledge and value from large collections of data are now available and enable new industries, business models, and jobs. However, the current data market is asymmetric and prevents companies from competing fairly. On the one hand, only very specialized digital organizations can manage complex data technologies such as Artificial Intelligence and obtain great benefits from third-party data at a very reduced cost. On the other hand, datasets are produced by regular companies as valueless sub-products that assume great costs. These companies have no mechanisms to negotiate a fair distribution of the benefits derived from their industrial data, which are often transferred for free. Therefore, new digital data-driven marketplaces must be enabled to facilitate fair data trading among all industrial agents. In this paper, we propose a blockchain-enabled solution to monetize industrial data. Industries can upload their data to an Inter-Planetary File System (IPFS) using a web interface, where the data are randomized through a privacy-preserving algorithm. In parallel, a blockchain network creates a Non-Fungible Token (NFT) to represent the dataset. So, only the NFT owner can obtain the required seed to derandomize and extract all data from the IPFS. Data trading is then represented by NFT trading and is based on fungible tokens, so it is easier to adapt prices to the real economy. Auctions and purchases are also managed through a common web interface. Experimental validation based on a pilot deployment is conducted. The results show a significant improvement in the data transactions and quality of experience of industrial agents. Full article

The establishment of a long-term, cross-border market in which forward market coupling and bilateral contracts are developed in an integrated approach is instrumental for the European internal electricity market. We propose the joint energy and transmission right auction (JETRA) mechanism, developed by O’Neill et al., as a solution for long-term cross-border markets in Europe. The main contribution of this research lies in its examination of the underlying market structures for effective JETRA implementation. We compare the institutional setting, market rules, and grid modeling under nodal and zonal pricing systems, adapting JETRA to the flow-based market coupling (FBMC) mechanism that is currently implemented in the European day-ahead market. This adaptation reveals the inherent limitations of FBMC in supporting JETRA, in particular in the long-term auction. We also identify constraints posed by existing European market rules, particularly those that affect the application of multi-settlement rules and the effective timeframe of hedging instruments. In conclusion, our research suggests that transitioning from zonal to nodal pricing is essential for JETRA’s effective implementation. Furthermore, a comprehensive market reform is required to seamlessly integrate long- and short-term markets. Full article

This paper presents a detailed review of the existing literature on peer-to-peer (P2P) energy trading considering market architectures, trading strategies, and enabling technologies. P2P energy trading enables individual users in the electricity network to act as sellers or buyers and trade energy among each other. To facilitate the discussion on different aspects of P2P energy trading, this paper focuses on P2P market mechanisms, relevant bidding strategies, and auction models. In addition, to solve the energy management problems associated with P2P energy trading, this paper investigates widely used solution methods such as game-theoretic models, mathematical optimisation, as well as more recent machine learning techniques and evaluates them in a critical manner. The outcomes of this investigation along with the identification of the challenges and limitations will allow researchers to find suitable P2P energy trading mechanisms based on different market contexts. Moreover, the discussions on potential future research directions are expected to improve the effectiveness of P2P energy trading technologies. Full article

The state-owned power Electricity Generating Authority of Thailand (EGAT), a monopoly market in charge of producing, distributing, and wholesaling power, is the focal point of Thailand’s electricity market. Although the government has encouraged people to install on-grid solar panels to sell electricity as producers and retail consumers, the price mechanism, i.e., purchasing price and selling prices, is still unilaterally determined by the government. Therefore, we are interested in studying the case where blockchain can be used as a free trading platform. Without involving buying or selling from the government, this research presents a model of fully traded price mechanisms. Based on the study results of the double auction system, data on buying and selling prices of electrical energy in Thailand were used as the initial data for the electricity peer-to-peer free-trading model. Then, information was obtained to analyze the trading price trends by using the law of demand and supply in addition to the principle of the bipartite graph. The price trend results agree well with those of price equilibrium equations. Therefore, we firmly believe that the model we offer can be traded in a closed system of free-trade platforms. In addition, the players in the system can help to determine the price trend that will occur according to various parameters and will cause true fairness in the sustainable electricity supply chain industry in Thailand. Full article

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. The carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China’s future carbon quota allocation will gradually transition from free allocation to auction allocation, and the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism, constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model, systematically researches the power generation structure under different auction ratios with the time scale of months, and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions. The results of the study show that after comprehensively comparing the total economic cost, renewable energy development, and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits. Full article