Article
Automation & Control Systems
Aitazaz Ali Raja, Sergio Grammatico
Summary: In this article, a bilateral peer-to-peer energy trading scheme is proposed for single-contract and multi-contract market setups. The proposed scheme is considered as an assignment game, a special class of coalitional games. The market formulation allows for efficient computation of a market equilibrium while preserving the desired economic properties offered by the coalitional games. The market model also accommodates buyers with different preferences over energy sellers, such as economic, social, or environmental factors. A novel distributed negotiation mechanism is designed to address the scalability issue in coalitional games and improve the convergence speed using the geometric structure of the equilibrium solution. The algorithm enables market participants to reach a consensus on a set of stable and fair bilateral contracts, enhancing prosumer participation. The negotiation process requires minimal information on a time-varying communication network to protect privacy. Rigorous proofs of convergence are provided using operator-theoretic tools. Numerical simulations demonstrate the benefits of the negotiation protocol, with significantly faster execution time compared to the benchmark.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Yu Yang, Yue Chen, Guoqiang Hu, Costas J. Spanos
Summary: This paper investigates the integration of P2P energy trading into existing power systems and proposes a network charge mechanism to address transmission loss and network constraints. A Stackelberg game model is used to determine the equilibrium network charge price, and a method for obtaining this price efficiently is proposed. Simulation results on IEEE bus systems demonstrate that the network charge mechanism is beneficial for grid operators and prosumers, achieving near-optimal social welfare. Additionally, the presence of energy storage affects prosumers' sensitivity to network charge price changes and has an impact on the P2P market.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Sara Mohammadi, Frank Eliassen, Yan Zhang, Hans-Arno Jacobsen
Summary: In this article, the vulnerabilities arising from the incorporation of distributed energy resources in peer-to-peer energy trading are explored, particularly in relation to false data injection attacks. The authors propose a novel machine learning-based detection method and demonstrate its superior performance through experimentation with real-world data.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Automation & Control Systems
Md Habib Ullah, Jae-Do Park
Summary: This article presents a novel two-tier peer-to-peer market paradigm for energy sharing between multiregional proactive prosumers. The proposed approach uses distributed market-clearing methods to protect prosumers' privacy and significantly increase their economic benefits. The effectiveness of the approach is validated through software simulations.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Energy & Fuels
Juan Wang, Junjun Zheng, Liukai Yu, Mark Goh, Yunying Tang, Yongchao Huang
Summary: This paper proposes a distributed reputation-distance-driven iterative auction mechanism to promote energy trading among users who commit contracts well and among electrically closer peers. It introduces a reputation-distance index based on historical trading performance and electricity distance, and uses a self-adaption algorithm based on game theory to arrive at a Nash equilibrium. The mechanism can reduce network loss, increase market efficiency, and improve social welfare.
Article
Engineering, Electrical & Electronic
Kaile Zhou, Jie Chong, Xinhui Lu, Shanlin Yang
Summary: This study proposes a credit-based P2P electricity trading model to address the issues of high transaction costs and mutual distrust among users. By introducing credit management in a blockchain environment, the model effectively manages default behavior and improves trading stability and efficiency.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Electrical & Electronic
Giuseppe Belgioioso, Wicak Ananduta, Sergio Grammatico, Carlos Ocampo-Martinez
Summary: In this paper, a generalized aggregative game model based on peer-to-peer energy market is proposed for efficient and safe energy trading. A distributed market-clearing mechanism is designed to ensure convergence to an economically-efficient, strategically-stable, and operationally-safe configuration. Numerical studies on a real-life test case demonstrate the scalability of the proposed approach and the benefits for both prosumers and the network operator.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Automation & Control Systems
Luhao Wang, Yumin Zhang, Wen Song, Qiqiang Li
Summary: This article studies the coordination and optimization of energy sharing among multiple microgrids belonging to different entities. It proposes a strategy based on stochastic Cartel game for grid-oriented energy bidding problem, with peer-to-peer (P2P) energy trading under uncertainty. A stochastic Cartel nonlinear programming model is formulated and a diagonal quadratic approximation method is employed. The problem is decomposed into subproblems for individual microgrids and equilibrium solutions are derived in an iterative and distributed manner. Comparisons are conducted to validate the proposed strategy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Wei Zhou, Yuying Wang, Feixiang Peng, Ying Liu, Hui Sun, Yu Cong
Summary: In the deregulated energy market environment, small-scale peer-to-peer (P2P) energy trading can increase distributed photovoltaic power generation consumption and promote local energy balance. However, it also raises the risk of security constraints violations during the utility grid operation. To address physical network congestion caused by distributed P2P energy trading, a method based on a continuous double auction mechanism is proposed, along with a two-tier market coordination mechanism to utilize user flexibility.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Chang Liu, Zhixun Wang, Mengqi Yu, Hongyuan Gao, Wei Wang
Summary: This paper proposes an optimal peer to peer (P2P) energy trading method for building microgrid based on data envelopment analysis (DEA). The method consists of a three-layer optimization model. The effectiveness of the proposed method is verified by simulating three possible scenarios and applying comparative analysis.
Article
Automation & Control Systems
Min Zhang, Frank Eliassen, Amir Taherkordi, Hans-Arno Jacobsen, Hwei-Ming Chung, Yan Zhang
Summary: Peer-to-peer energy trading plays an important role in smart grids, and blockchain and smart contract technology ensure secure operation. This article studies the challenges of demand-response management in P2P energy trading and proposes a blockchain-empowered energy trading system.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Kaile Zhou, Jinhuan Guo, Jiong Zhou
Summary: This study proposes a two-stage credit management strategy for P2P electricity trading among microgrids. The strategy reduces default behaviors through robust control optimization and credit-based rewards and punishments, enhancing trust and creating a reliable trading environment for microgrids.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Haoran Ji, Jie Jian, Hao Yu, Jie Ji, Mingjiang Wei, Xinmin Zhang, Peng Li, Jinyue Yan, Chengshan Wang
Summary: This article proposes a DLT-based P2P electricity trading method based on intelligent SOP regulation, which allows multiple regions interconnected by soft open points to flexibly exchange power to alleviate power imbalance. Smart contracts and distributed ledger technology ensure the credibility of transactions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Lahanda Purage Mohasha Isuru Sampath, Amrit Paudel, Hung D. Nguyen, Eddy Y. S. Foo, Hoay Beng Gooi
Summary: A decentralized market framework for P2P energy trading is proposed in this paper. The market equilibrium is achieved through the participation of nodal agents and P2P agents, while protecting the privacy concerns of market participants and considering the allocation of costs/rewards associated with ancillary services.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Construction & Building Technology
Saber Talari, Mohsen Khorasany, Reza Razzaghi, Wolfgang Ketter, Amin Shokri Gazafroudi
Summary: This paper proposes a fully decentralized market mechanism for energy trading, taking into account the preferences and attributes of prosumers. The designed mechanism satisfies market properties and is shown to be effective through simulation results.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Review
Energy & Fuels
Praveen Prakash Singh, Fushuan Wen, Ivo Palu, Sulabh Sachan, Sanchari Deb
Summary: Present trends indicate that electric vehicles are a favorable technology for road transportation, but the lack of accessible charging stations hinders their adoption. Charging station placement and scheduling have become areas of research interest worldwide. Various planning and scheduling models have been proposed, each with its own advantages and disadvantages. Additionally, the models' performance varies depending on the location. This paper provides an overview of charging station placement, charging activity scheduling, and global charging infrastructure planning. It also discusses the challenges, solutions, recommendations, and future scope of EV charging infrastructure.
Article
Energy & Fuels
Xiuli Wang, Xudong Li, Weidong Ni, Fushuan Wen
Summary: Power system stability is at risk due to the increasing integration of intermittent renewable generation. Battery energy storage systems (BESSs) can help regulate frequency fluctuations in the power system. The proposed strategy divides the ACE signal and SOC of BESSs into intervals, considering the frequency control demand and SOC self-recovery to determine the frequency control task. Model predictive control is used to optimize the control variables of BESSs, and simulation results validate the feasibility of the strategy.
Article
Automation & Control Systems
Guolong Liu, Jinjie Liu, Junhua Zhao, Jing Qiu, Yiru Mao, Zhanxin Wu, Fushuan Wen
Summary: Corporate carbon footprint (CCF) estimation is crucial for achieving carbon neutrality, but current methods may lack comprehensiveness, timeliness, and accuracy. This article proposes a novel method that combines appliance identification and electricity consumption calculation to estimate direct and indirect carbon emissions of factories in real time. Experimental results demonstrate the superiority of the proposed method in appliance identification and its ability to achieve comprehensive and accurate estimation of minute-level CCF.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Energy & Fuels
Zhengmao Li, Yan Xu, Peng Wang, Gaoxi Xiao
Summary: This paper proposes a coordinated restoration method for the renewable energy-integrated multi-energy distribution system (MDS) to address the threats of low-probability but high-impact extreme events, such as floods, earthquakes, and hurricanes, to the security of the energy system. The method comprehensively models the MDS restoration with coupled power and thermal network constraints, utilizing thermal inertia and smart buildings' thermal demand response as buffers to reduce post-disaster energy supply cost. Preparation and load recovery stage measures are employed for efficient and reliable system restoration. Multiple uncertainties are dealt with through a risk-averse two-stage stochastic programming approach. Simulation results validate the effectiveness and superiority of the method.
Article
Energy & Fuels
Yesen Yang, Zhengmao Li, Pradeep V. Mandapaka, Edmond Y. M. Lo
Summary: This paper proposes a coordinated restoration framework for a coupled power and water system, considering physical networks and mechanisms. The framework minimizes the aggregate service loss with respect to different consumer loads and time periods by network reconfiguration, energy/water dispatching, load curtailment, and operation management of components. A two-stage risk-averse stochastic programming is applied for reliable restoration and manage risks.
Article
Energy & Fuels
Hongxu Huang, Zhengmao Li, Hoay Beng Gooi, Haifeng Qiu, Xiaotong Zhang, Chaoxian Lv, Rui Liang, Dunwei Gong
Summary: In this paper, a coordinated operation approach is proposed for scheduling the energy-transportation coupled coal mine integrated energy system (CMIES) under diverse uncertainties. The belt conveyors in the coal transportation network (CTN) and the CMIES are used to coordinate coal delivery scheduling and energy management. A novel energy-transportation coordinated model is proposed, which consists of the radial CTN and second-order cone programming (SOCP) relaxed CMIES. The aim is to overcome the challenges of robust optimization and stochastic programming by applying the distributionally robust optimization (DRO) method.
Article
Engineering, Electrical & Electronic
Shengyuan Liu, Changming Chen, Yicheng Jiang, Zhenzhi Lin, Hongtao Wang, Muhammad Waseem, Fushuan Wen
Summary: A bi-level coordinated power system restoration (BiCPSR) model is proposed in this study, considering the support of multiple flexible resources. The upper level optimizes the start-up sequence of generators and network reconfiguration using topology indices and restoration characteristics. The lower level considers the uncertainties of RES and EVS and utilizes multiple flexible resources to accelerate the restoration process and maximize the restorable load.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Ping He, Haoran Jin, Zhiwen Pan, Lei Yun, Fushuan Wen, Hua Yang, Yukun Tao
Summary: In order to tackle the challenges of integrating increasing renewable energy generation, such as wind power and photovoltaic, the wind-PV-thermal-bundled transmission mode is proposed. This mode helps mitigate the intermittent power output from wind and PV units. A WPTB transmission system model is developed based on mathematical models of thermal generation units, wind turbines, and PV units. The objective is to enhance probabilistic small-signal stability through an optimal strategy formulated using eigenvalues and damping ratios.
JOURNAL OF ENERGY ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Xiangyu Zhang, Abinet Tesfaye Eseye, Bernard Knueven, Weijia Liu, Matthew Reynolds, Wesley Jones
Summary: This paper focuses on the critical load restoration problem in distribution systems following major outages. A reinforcement learning (RL) based approach combined with curriculum learning (CL) technique is proposed to optimize the restoration process. Experimental results show that RL controllers are less susceptible to forecast errors and can provide a more reliable restoration process compared to baseline model predictive controllers (MPCs).
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Zhi Zhang, Feng Lu, Zhenzhi Lin, An Wen, Yunwen Gao, Fushuan Wen, Sirui Wang, Li Yang, Yi Ding
Summary: Inaccurate recognition of user characteristics can lead to high trial-and-error costs for load aggregators in the early stage of market-oriented demand response. This study introduces a typical invitation-based DR program in China and proposes a bid and scheduling strategy optimization model as a decision-making tool for load aggregators. A two-stage user characteristic recognition method is also proposed to improve market strategies based on a labeled database.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Proceedings Paper
Green & Sustainable Science & Technology
Yongqing Liu, Qibin Huang, Zihao Li, Zhen Wang, Xiaohui Wang, Hang Wu, Hui Huang, Fushuan Wen
Summary: With the integration of distributed generation and deregulation of the power industry, prosumers, who can play both roles as producers and consumers of electricity, have emerged. The presence of prosumers enhances local electricity energy utilization and accommodation for small-capacity intermittent renewable energy-based generation units through peer-to-peer (P2P) transactions. To address this, an event-driven P2P electric energy trading mechanism based on the blockchain platform is proposed, which utilizes smart contracts, a market clearing model, and a distributed algorithm for market clearing and settlement.
2023 IEEE IAS GLOBAL CONFERENCE ON RENEWABLE ENERGY AND HYDROGEN TECHNOLOGIES, GLOBCONHT
(2023)
Article
Engineering, Electrical & Electronic
Shengyuan Liu, Yicheng Jiang, Zhenzhi Lin, Fushuan Wen, Yi Ding, Li Yang
Summary: This paper proposes a two-step day-ahead electricity price forecasting algorithm based on the weighted $K$-nearest neighborhood (WKNN) method and the Gaussian process regression (GPR) approach. The algorithm detects price spikes in the first step and accurately forecasts electricity price in the second step. It is verified using actual market data and compared to existing algorithms to demonstrate its effectiveness.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Kun Wang, Jiajia Yang, Chunyue Zhang, Fushuan Wen, Gang Lu
Summary: Striving to develop renewable energy generation (REG) has become a global trend. This paper proposes a bi-level optimization model for the joint energy and regulation service market to help fossil-fueled generation units (FFGUs) transition into secure and reliable frequency regulation service providers. The model considers both the environmental cost of FFGUs and the frequency regulation service (FRS) cost of REG units, allowing market operators to determine the scheduling priorities of generation units. The model also applies a dynamic approach to determining the FRS demand and ensures the revenue of FFGUs in the FRS market. Extensive numerical experiments demonstrate the feasibility and efficiency of the proposed mechanism.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
