Planning, operation, and trading mechanisms of transactive energy systems in the context of carbon neutrality

In the context of carbon neutrality, the penetration ratio of renewable energy, flexible load, energy storage, and interactive equipment have been increasing, and the boundary between traditional energy producers and consumers has been getting more blurred. A new type of energy system, namely the transactive energy system (TES), has emerged. The TES uses the value (price) as a guide for market participants in optimizing decisions, realizing centralized/distributed coordination of large-scale energy systems, and developing these systems to improve energy efficiency, thus, reducing carbon emissions and improving the economy. However, the deep coupling between energy trading and physical energy flow complicates the planning, operation optimization, trading, and interaction of traditional energy systems. Based on the abovementioned background, this special issue, which focuses on the planning, operation, and trading mechanism of TES, has received considerable attention from the research community. The four papers selected for publication in this issue are briefly introduced below.

In the article “Towards transactive energy: An analysis of information-related practical issues”, Chen et al. classified existing transactive energy market mechanisms according to the potential market structure and communication networks. Three potential practical problems related to information were proposed: asynchronous computing, real reporting, and privacy protection. Each practical problem was analyzed in detail through investigation and related research. Distributed algorithms for constrained optimizations, such as flexible and asynchronous alternating direction method of multipliers (ADMM), can help solve the problem of asynchronous computing. Mechanism design methods based on the principal-agent framework and Myerson's Lemma can provide some insights into the issue of real reporting. Two main approaches to addressing the challenge of privacy protection are homomorphic encryption and differential privacy. Based on these findings, several potential research directions were proposed to provide some insights for future research.

In the article ‘Optimization of transactive energy systems with demand response: A cyber-physical-social system perspective’, Han et al. focused on the distribution system and analyzed the challenges of TES in optimal operation of demand response (DR) in the context of cyber-physical-social system. An optimized framework of TES, which integrates artificial systems, computational experiments, and parallel energy optimization for DR modelling, was proposed. A data-driven artificial DR system was constructed based on limited data. A complete information on the Stackelberg game model that describes the relationship between distribution network operators and an artificial DR system was established to simulate the response relationship between distribution network operators and power users under different price incentives. In parallel energy optimization, a multi-time scale energy optimization method with day-ahead and intraday optimizations was proposed. The proposed method can reduce the cost for distribution network operators and users and promote renewable energy consumption.

In the article “Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto-optimal profits for the utility and prosumers”, Mohan et al. constructed a microgrid energy portfolio based on the TES. Considering the large amount of renewable energy access and the interaction between energy and financial risks in TES, the portfolio was based on the adjustment of financial and energy risks and had a reasonable trade-off between utility and consumer profits. Based on the relative energy risk level quantified by the conditional value-at-risk, the authors pre-adjusted, and prioritized the bidding prices of wind and solar energy. Non-dominated sorting particle swarm optimization was used to simultaneously optimize the conflicting profits of utilities and consumers to obtain the risk-adjusted price Pareto optimal energy portfolio. Power companies can predict real-time net power balance cost from the dispatching time range using this method to mitigate the adverse impact of renewable energy uncertainty on collective welfare. The microgrid energy portfolio obtained using this method is more realistic, welfare optimized, and cost-effective.

In the article ‘Comparative study on distributed generation trading mechanisms in the UK and China’, Yao et al. discussed the trade mechanism of distributed generation (DG) in the context of TES through a comparative analysis between China and the UK. The policies and arrangements of DG trade in the UK and China, including market structure, connection classification, economic benefits, and practical problems, were comprehensively reviewed. The political, economic, social, and technical characteristics of the mechanisms of the two countries were qualitatively determined and compared based on strengths, weaknesses, opportunities, and threats using the framework of the SWOT-PEST model. The authors made a quantitative comparison between the trade arrangements of the UK and China, analyzed the economic benefits, and revealed the impact. Based on a comparative analysis, a direction for developing and perfecting the DG trading mechanism was proposed. Both UK and China, as well as other countries, can learn from their practical experiences.

Dan Wang (M'15–SM'21) received his M.Sc. degree in electrical engineering from Hohai University, China in 2006 and his Ph.D. degree from Tianjin University, China in 2009. He worked as a postdoctoral fellow at the Institute for Integrated Energy Systems (IESVic), University of Victoria, Canada. He is currently an associate professor at the Department of Electrical Engineering, Tianjin University, China. His research interests include integrated energy systems, smart power distribution systems, distributed energy systems, and microgrids. He was a highly cited scholar in China in 2021, IEEE PES Outstanding Young Talent in 2021, and silver medalist in the 2022 Geneva International Exhibition of Inventions. He won the 2019 China Top 100 most influential domestic academic paper awards. Four of his articles won the top paper (F5000) award of China's top quality scientific and technological journals. He is an editorial board member of the Protection and Control of Modern Power Systems and a young editorial board member of the Electric Power Construction.

Yue Zhou received his B.Sc., M.Sc., and Ph.D. degrees in electrical engineering from Tianjin University, China in 2011, 2016, and 2016, respectively. He is a lecturer in Cyber Physical Systems at the School of Engineering, Cardiff University, Wales, UK. His research interests include demand response, peer-to-peer energy trading, and cyber-physical systems. Dr. Zhou is a managing editor of Applied Energy and an associate editor of IET Energy Systems Integration, IET Renewable Power Generation, and Frontiers in Energy Research. He is the chair of the CIGRE UK Next Generation Network (NGN) Committee. He is also a committee member of the IEEE PES UK and Ireland Chapters.

Nian Liu (S'06–M'11) received his B.Sc. and M.Sc. degrees in electrical engineering from Xiangtan University, Hunan, China in 2003 and 2006, respectively, and his Ph.D. degree in electrical engineering from North China Electric Power University, Beijing, China in 2009. He is currently a professor and the vice dean of the School of Electrical and Electronic Engineering, North China Electric Power University. He is the director of the Research Section for Multi-information Fusion and Integrated Energy System Optimization of the State Key Laboratory of Alternate Electrical Power Systems with Renewable Energy Sources. He is a member of the Standardization Committee of Power Supply and Consumption in the Power Industry of China. He was recognized by Elsevier as a highly cited Chinese researcher in 2020. He was a visiting research fellow at the Royal Melbourne Institute of Technology University (RMIT), Melbourne, Australia from 2015 to 2016. His main research interests include multienergy system integration, microgrids, cyber-physical energy systems, and renewable energy integration. He has authored or co-authored more than 180 journal and conference publications, and has been granted more than 20 patents in China. He is an editor of IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, IEEE Power Engineering Letters, and the Journal of Modern Power Systems and Clean Energy (MPCE).

Meysam Qadrdan is an EPSRC-UKRI Innovation fellow and a reader (associate professor) in Energy Networks and Systems at Cardiff University. Prior to joining Cardiff as a lecturer in January 2015, he spent one year at Imperial College and two years at Cardiff University as a research associate. He obtained his Ph.D. from Cardiff University, UK in 2012, M.Sc. in Energy Systems Engineering from Sharif University of Technology, Iran in 2008, and B.Sc. in Physics from Ferdowsi University, Iran in 2005. He also worked as an energy consultant for two years prior to pursuing a Ph.D. degree in Cardiff. His research area covers the expansion and operational planning of interdependent energy networks at different scales, from the community to the national level. He developed modelling tools to investigate: (i) cross-sectoral flexibility to support the operation of low-carbon power systems, (ii) interactions between gas, electricity, and heat supply systems, (iii) expansion planning of energy infrastructure under uncertainty, and (iv) whole-system impacts of heat decarbonization pathways. He is an associate editor of the IET Energy Systems Integration Journal.

Rohit Bhakar (SM, IEEE) received a B.E. degree in electrical engineering from M.B.M. Engineering College, Jodhpur, an M.Tech. degree in power system engineering from Malaviya National Institute of Technology, Jaipur, and a Ph.D. degree from Indian Institute of Technology, Roorkee. He currently holds a joint appointment as an associate professor of the Department of Electrical Engineering and the Centre for Energy and Environment at the Malaviya National Institute of Technology, Jaipur. His research interests include electricity markets, system operations, energy system planning, renewable forecasting, system flexibility, risk management, local energy market, cyber security, and uncertainty modelling.

Sahban Alnaser received his Ph.D. degree in electrical energy and power systems from the University of Manchester, UK in 2015. Currently, he is an assistant professor of the Power System at the Department of Electrical Engineering, University of Jordan. Prior to joining the University of Jordan, he was a research associate at the University of Manchester focusing on network integration of PV and storage. Between 2005 and 2011, he worked at the Electricity Distribution Company (EDCO), Jordan, as the head of the Power System Studies. His main research interests include grid integration of renewable energy sources, demand response, and energy storage systems.