Distributed Market Clearing Approach for Local Energy Trading in Transactive Market

This paper proposes a market clearing mechanism for energy trading in a local transactive market, where each player can participate in the market as seller or buyer and tries to maximize its welfare individually. Market players send their demand and supply to a local data center, where clearing price is determined to balance demand and supply. The topology of the grid and associated network constraints are considered to compute a price signal in the data center to keep the system secure by applying this signal to the corresponding players. The proposed approach needs only the demanded/supplied power by each player to reach global optimum which means that utility and cost function parameters would remain private. Also, this approach uses distributed method by applying local market clearing price as coordination information and direct load flow (DLF) for power flow calculation saving computation resources and making it suitable for online and automatic operation for a market with a large number of players. The proposed method is tested on a market with 50 players and simulation results show that the convergence is guaranteed and the proposed distributed method can reach the same result as conventional centralized approach.Comment: Accepted paper. To appear in PESGM 2018, Portland, OR, 201

Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading

Peer-to-Peer (P2P) energy trading can facilitate integration of a large number of small-scale producers and consumers into energy markets. Decentralized management of these new market participants is challenging in terms of market settlement, participant reputation and consideration of grid constraints. This paper proposes a blockchain-enabled framework for P2P energy trading among producer and consumer agents in a smart grid. A fully decentralized market settlement mechanism is designed, which does not rely on a centralized entity to settle the market and encourages producers and consumers to negotiate on energy trading with their nearby agents truthfully. To this end, the electrical distance of agents is considered in the pricing mechanism to encourage agents to trade with their neighboring agents. In addition, a reputation factor is considered for each agent, reflecting its past performance in delivering the committed energy. Before starting the negotiation, agents select their trading partners based on their preferences over the reputation and proximity of the trading partners. An Anonymous Proof of Location (A-PoL) algorithm is proposed that allows agents to prove their location without revealing their real identity. The practicality of the proposed framework is illustrated through several case studies, and its security and privacy are analyzed in detail

Two-Step market clearing for local energy trading in feeder-based markets

Recent innovations in Information and Communication Technologies (ICT) provide new opportunities and challenges for integration of distributed energy resources (DERs) into the energy supply system as active market players. By increasing integration of DERs, novel market platform should be designed for these new market players. The designed electricity market should maximize market surplus for consumers and suppliers and provide correct incentives for them to join the market and follow market rules. In this paper, a feeder-based market is proposed for local energy trading among prosumers and consumers in the distribution system. In this market, market players are allowed to share energy with other players in the local market and with neighborhood areas. A Two-StepMarket Clearing (2SMC) mechanism is proposed for market clearing, in which in the first step, each local market is cleared independently to determine the market clearing price and in the second step, players can trade energy with neighborhood areas. In comparison to a centralized market, the proposed method is scalable and reduces computation overheads, because instead of clearing market for a large number of players, the market is cleared for a fewer number of players. Also, by applying distributed method and Lagrangian multipliers for market clearing, there is no need for a central computation centre and private information of market players. Case studies demonstrate the efficiency and effectiveness of the proposed market clearing method in increasing social welfare and reducing computation time.Comment: 6 page

Design of auction-based approach for market clearing in peer-to-peer market platform

This paper designs a market platform for Peer-to-Peer (P2P) energy trading in Transactive Energy (TE) systems, where prosumers and consumers actively participate in the market as seller or buyer to trade energy. An auction-based approach is used for market clearing in the proposed platform and a review of different types of auction is performed. The appropriate auction approach for market clearing in the proposed platform is designed. The proposed auction mechanism is implemented in three steps namely determination, allocation and payment. This paper identifies important P2P market clearing performance indices, which are used to compare and contrast the designed auction with different types of auction mechanisms. Comparative studies demonstrate the efficacy of the proposed auction mechanism for market clearing in the P2P platform.Comment: 6 page

A framework for participation of prosumers in peer-to-peer energy trading and flexibility markets

As the owners of distributed energy resources (DER), prosumers can actively manage their power supply and consumption and partake in new energy services. In order to enable prosumers to benefit from their participation in energy services, innovative market models need to be designed. This paper proposes a framework for local energy and flexibility trading within distribution networks, in which prosumers participate in a peer-to-peer (P2P) market to trade energy with each other based on their preferences. The P2P market is cleared in a decentralized manner with direct interaction of seller and buyer prosumers. Then, the distribution system operator (DSO) checks the network constraints based on the energy scheduling of prosumers. If the network constraints are not satisfied, the DSO calculates the flexibility that is required in each feeder to avoid network issues. Triggered by the requested flexibility by the DSO, prosumers in each feeder form a community and participate in a flexibility market, in which they can offer their flexibility in response to the DSO’s request. An iterative auction is employed to clear the flexibility market, which enables the prosumers to independently decide on their offered flexibility, while the DSO adjusts the flexibility price to minimize its costs. The proposed framework is tested on a real-world distribution network. Simulations based on a number of case studies indicate that through the proposed framework, the DSO can avoid network constraints violation by employing prosumers’ flexibility. Besides, participation in the P2P and flexibility trading reduces the net energy costs of the prosumers in different community by an average of 17.09%.©2022 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

Enhancing scalability of peer-to-peer energy markets using adaptive segmentation method

This paper proposes an adaptive segmentation method as a market clearing mechanism for peer-to-peer (P2P) energy trading scheme with large number of market players. In the proposed method, market players participate in the market by announcing their bids. In the first step, players are assigned to different segments based on their features, where the balanced k-means clustering method is implemented to form segments. These segments are formed based on the similarity between players, where the amount of energy for trade and its corresponding price are considered as features of players. In the next step, a distributed method is employed to clear the market in each segment without any need to private information of players. The novelty of this paper relies on developing an adaptive algorithm for dividing large number of market players into multiple segments to enhance scalability of the P2P trading by reducing data exchange and communication overheads. The proposed approach can be used along with any distributed method for market clearing. In this paper, two different structures including community-based market and decentralized bilateral trading market are used to demonstrate the efficacy of the proposed method. Simulation results show the beneficial properties of the proposed segmentation method

Market design for peer-to-peer energy trading in a distribution network with high penetration of distributed energy resources

This thesis examines different market structures for peer-to-peer (P2P) energy trading. Different market clearing mechanisms are designed for market settlement, including auction-based method, distributed optimisation, and decentralised market clearing. Also, price signals are introduced to model network constraints in any individual transaction in the electricity market. Moreover, a segmentation method is proposed to enhance the scalability of the P2P markets, using the clustering method

Bidding strategy for participation of virtual power plant in energy market considering uncertainty of generation and market price

Due to the small capacity of DGs, their individual participation in the energy market is not beneficial. In the case of wind and solar plants, their uncertain power generation is another issue for their participation in the market, especially when their capacity is low. Commercial Virtual Power Plant (CVPP) is a new market participant, which represents a group of various DGs in the market, and bids to the market. This paper proposes a new bidding strategy approach for the participation of CVPP in the day-ahead energy market, considering uncertainties of wind turbine generation and Market Clearing Price (MCP). The market is pay as bid, and each participant bids a multi-step price-power curve. The uncertainty of MCP has formulated analytically, while the wind uncertainty is modeled by a quantized Rayleigh probability distribution function. Particle Swarm Optimization (PSO) algorithm is utilized for optimizing the objective function, which is the expected benefit of the CVPP. Numerical results are provided to evaluate the performance of proposed approach in increasing the benefit of VPP

A Decentralized Bilateral Energy Trading System for Peer-to-Peer Electricity Markets

Increase in the deployment of distributed energy resources (DERs) has triggered a new trend to redesign electricity markets as consumer-centric markets relying on peer-to-peer (P2P) approaches. In the P2P markets, players can directly negotiate under bilateral energy trading to match demand and supply. The trading scheme should be designed adequately to incentivise players to participate in the trading process actively. This article proposes a decentralized P2P energy trading scheme for electricity markets with high penetration of DERs. A novel algorithm using primal-dual gradient method is described to clear the market in a fully decentralized manner without interaction of any central entity. Also, to incorporate technical constraints in the energy trading, line flow constraints are modeled in the bilateral energy trading to avoid overloaded or congested lines in the system. This market structure respects market players' preferences by allowing bilateral energy trading with product differentiation. The performance of the proposed method is evaluated using simulation studies, and it is found that market players can trade energy to maximize their welfare without violating line flow constraints. Also, compared with other similar methods for P2P trading, the proposed approach needs lower data exchange and has a faster convergence.</p

Auction based energy trading in transactive energy market with active participation of prosumers and consumers

This paper proposes a Transactive Energy Market (TEM) platform for Peer-to-Peer (P2P) energy trading among prosumers and consumers in the Transactive environment. Prosumers with excess energy participate in the market as seller and consumers play a buyer role and communicate with each other to maximize their welfare, which is the difference between their benefit and cost. The proposed platform is an hour-ahead market, where market subscribers join to trade energy for the next hour. Market clearing is performed using auction approach and a double auction with average mechanism is applied to determine allocation and price of energy. In this platform, market subscribers pay a Subscription Charge (SC) for utilizing the distribution network and this charge is used as a price signal to reduce the possibility of overload in the network's lines. Power Transfer Distributed Factor (PTDF) is used to calculate SC by incorporating network topology and the distributed nature of prosumers and consumers. Simulation results on a simple IEEE 13 node distribution network with 10 subscribers (5 buyers and 5 sellers) demonstrate the efficacy of the proposed TEM platform and market clearing mechanism