A transactive energy management system for future community needs

Abstract

Transactive energy (TE) is emerging as one of the most innovative approaches for the transformation of existing electricity grids towards the future smart grid as the penetration level of distributed generation (DG) is increasing in power systems. TE based local energy trading (LET) is one of the novel concepts in the area of distribution networks. Peer-to-peer (P2P) energy trading is a kind of LET, and it is one of the promising approaches for implementing decentralized electricity market paradigms. A proper business model is required to manage LET. The pricing mechanism is crucial because the agreed energy price determines the benefits of LET. Since the physical network or grid is used for energy transfer, power losses are inevitable, and grid-related costs always occur during energy transactions. These grid-related aspects should be considered while designing a business model for LET. A proper market clearing mechanism is necessary to facilitate energy transactions among different parties. Designing a proper market clearing mechanism with a specific objective considering the privacy of agents and different aspects of physical networks is a challenging task.This thesis presents the study of different types of TE based energy trading and management schemes for future smart grids. The focus of the thesis is to develop market clearing algorithms for TE based LET and P2P energy trading. The contributions in this thesis are broadly divided into three parts. The first part proposes a novel game-theoretic approach for P2P energy trading among the prosumers in a community microgrid. The objective of trading is to maximize individual welfare.The proposed approach models the price competition among the sellers as a noncooperative game. The evolutionary game theory is used to model the dynamics of the buyers for selecting sellers. The proposed approach is applied to a small community microgrid with photovoltaic (PV) and energy storage systems. Simulation results show that P2P energy trading provides significant financial and technical benefits to the community, and it is emerging as an alternative to cost-intensive energy storage systems. The second part proposes a decentralized algorithm for LET in microgrids with an integrated pricing mechanism considering welfare maximization and network voltage management through local information exchange among neighbors. The proposed algorithm ensures that the energy transactions do not violate voltage constraints in a physical network, and agents’ privacy is preserved. A two-stage approach is proposed to achieve fast convergence and increase the practicability of the algorithm. The efficacy of the proposed approach is demonstrated using illustrative case studies. The final part presents 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 network utilization fees using an electrical distance approach. The effectiveness of the proposed decentralized approach for market clearing in the P2P energy trading is demonstrated using illustrative scenarios.