Peer-to-peer (P2P) energy trading is one of the promising approaches for implementing decentralized electricity market paradigms. In the P2P trading, each actor negotiates directly with a set of trading partners. Since the physical network or grid is used for energy transfer, power losses are inevitable, and grid-related costs always occur during the P2P trading. A proper market clearing mechanism is required for the P2P energy trading between different producers and consumers. This paper proposes a decentralized market clearing mechanism for the P2P energy trading considering the privacy of the agents, power losses as well as the utilization fees for using the third party owned network. Grid-related costs in the P2P energy trading are considered by calculating the network utilization fees using an electrical distance approach. The simulation results are presented to verify the effectiveness of the proposed decentralized approach for market clearing in P2P energy trading.

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Peer-to-Peer Energy Trading in Smart Grid Considering Power Losses and Network Fees

This paper proposes two novel strategies for determining the bilateral trading preferences of households participating in a fully Peer-to-Peer (P2P) local energy market. The first strategy matches between surplus power supply and demand of participants, while the second is based on the distance between them in the network. The impact of bilateral trading preferences on the price and amount of energy traded is assessed for the two strategies. A decentralized fully P2P energy trading market is developed to generate the results in a day-ahead setting. After that, a permissioned blockchain-smart contract platform is used for the implementation of the decentralized P2P trading market on a digital platform. Actual data from a residential neighborhood in the Netherlands, with different varieties of distributed energy resources, is used for the simulations. Results show that in the two strategies, the energy procurement cost and grid interaction of all participants in P2P trading are reduced compared to a baseline scenario. The total amount of P2P energy traded is found to be higher when the trading preferences are based on distance, which could also be considered as a proxy for energy efficiency in the network by encouraging P2P trading among nearby households. However, the P2P trading prices in this strategy are found to be lower. Further, a comparison is made between two scenarios: with and without electric heating in households. Although the electrification of heating reduces the total amount of P2P energy trading, its impact on the trading prices is found to be limited.

Blockchain-Based Fully Peer-to-Peer Energy Trading Strategies for Residential Energy Systems

The concept of peer-to-peer (P2P) trading, or transactive energy (TE), is gaining momentum as a future grid restructure. It has the potentials to utilize distributed energy resources (DERs), proactive demand side management (DSM), and the infusion in information and communication technologies (e.g., blockchain and Internet of Things (IoT)) for promoting the technical and economic efficiency of the system in its entirety. An efficient market framework is vital for the successful and sustainable implementation of such a concept. This article proposes a P2P energy trading framework enabled by blockchain. It consolidates bilateral contracts, an electronic-commerce platform, a double-auction Vickrey-Clarke-Groves (VCG) mechanism, and trading functionalities with the main grid. Through these multi-layer mechanisms, various trading preferences and attributes of electricity generation and/or consumption are accommodated. Meanwhile, the VCG mechanism eliminates any potential for market power exercise via incentivizing truthful bidding of participants. Different remedies are proposed to overcome the drawback of VCG, i.e., the lack of balanced-budget property. Accordingly, the proposed trading framework is described as multi-settlement and quasi-ideal. Case studies are conducted to analyze and evaluate the proposed trading framework and demonstrate the effectiveness of the proposed remedies in handling probable market deficiencies.

A Blockchain-Enabled Multi-Settlement Quasi-Ideal Peer-to-Peer Trading Framework

Moving to a user-centric approach is seen as a key change of paradigm in order to increase the efficiency and sustainability of energy systems. Massive integration of new economic agents such as prosumers and mobile or stationary storage will play a key role in the energy transition. In this article, a design of a community-based local energy market (CB-LEM) is proposed where the members are allowed to trade energy among each other through a local pool. The price is set on a day-ahead basis under the coordination of a Community Manager (CM). The novel aspect of this work is that every agent takes part in the determination of the local market price while deciding its own scheduling problem under uncertainty concerning renewable-energy generation and storage. After day-ahead clearing, real time operation and ex-post settlement of the local market by the CM are also explained in order to complete the proposed design. A real case study in a neighborhood in Amsterdam, The Netherlands, is used for testing the proposed framework. In addition, the performance of the ADMM-based clearing process is analyzed in terms of scalability and convergence.

A Community-Based Energy Market Design Using Decentralized Decision-Making Under Uncertainty

An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining

In the future power system, an increasing number of distributed energy resources will be integrated including intermittent generation like photovoltaic (PV) and flexible demand like electric vehicles (EVs). It has been long thought to utilize the flexible demand to absorb the PV output locally with the technical solution proposed while an effective commercial arrangement is yet to be developed due to the significant uncertainty associated with local generation. This paper proposes a peer-to-peer (P2P) local electricity market model incorporating both energy trading and uncertainty trading simultaneously. The novelty is to match the forecast power with demand having time flexibility and the uncertain power with demand having power flexibility. This market enables more PV uncertainty to be balanced locally rather than propagating to the upper layer system. In the test case, 55.3% of PV forecast error can be balanced locally in the proposed joint market. In comparison, 43.6% of PV forecast error is balanced locally when the forecast power and uncertain power are traded separately in a day-ahead market and a real-time market. The proposed P2P market can also motivate PV owners to improve forecast accuracy.

A Novel Peer-to-Peer Local Electricity Market for Joint Trading of Energy and Uncertainty

Peer-to-peer trading-based efficient flexibility securing mechanism to support distribution system stability

Energy forecasting at the individual level remains a technical barrier for the peer-to-peer (P2P) energy market. Forecasting errors will cause energy imbalances between real-time delivery and contracts. To reduce the economic loss, this paper proposes an imbalance reduction method based on hierarchical energy forecasting. Existing hierarchical forecasting usually cluster prosumers based on the similarities of their energy profiles. However, minimising the variance cannot guarantee reductions in energy imbalances. This paper explores a novel closed-loop clustering (CLC) algorithm, which aligns the mutual objectives of clustering and imbalance reduction through the introduction of a feedback mechanism. The proposed method is applied in a simulated P2P energy market to cluster photovoltaics (PVs) into virtual groups (VG). The output of each VG is predicted and traded with flexible demands as an entity. The results show that CLC could reduce up to 25.70% energy imbalance compared with individual trading. Network constraints have shown minor impact on the trading results.

Zhong Zhang

Papers

A Novel Peer-to-Peer Local Electricity Market for Joint Trading of Energy and Uncertainty

Peer-to-peer trading-based efficient flexibility securing mechanism to support distribution system stability

Imbalance Reduction of P2P Energy Market by Closed-Loop Clustering and Forecasting