Search

As decarbonization policies emerge around the world, research on cost-effective renewable energy is increasingly emphasized, but the uncertainty inherent in renewable energy disrupts the operation of power systems. Considering these issues, this paper presents a peer-to-peer (P2P) transaction platform that minimizes the cost of each transaction participant while considering photovoltaic (PV) generation uncertainty using stochastic programming. First, in the proposed algorithm, P2P energy transactions are conducted between prosumers who own PV and consumers. Then, prosumers purchase uncertainty demand response (UDR) capacity from consumers to counter the uncertainty of their PV. The performance of the proposed platform is verified through a case study using MATLAB 2021b Academic, Optimization Tool toolbox, and Matpower toolbox to demonstrate the economic feasibility by comparing the operating costs of participants and the power flow of Point of common coupling (PCC) with and without UDR transaction. The case studies show that the prosumers reduce the cost damage caused by the PV generation forecast error through the day-ahead UDR transaction, and the consumers reduce operating cost by bidding additional capacity in the UDR transaction that was not matched in the P2P transaction. In addition, the result of the power flow analysis indicates that the subject grid operates closer to day-ahead scheduling when the UDR transactions and implementations are performed.

Nowadays, due to the renewable energy policy, the penetration of photovoltaic (PV) has increased, but the curtailment of PV output power has also increased. However, for PV power producers, who earn profit from selling power to the utility, this kind of curtailment will lead to a decline in their profit. Thus it is necessary to determine how to perform proper curtailment for them. This study proposes a shared energy storage system (ESS) operation strategy based on the power flow at the points of common coupling (PCC) and the power sensitivity of the line loss effect between buses where each PV power producer is located. The proposed algorithm maximizes the overall regional profit through arbitrage trading of shared ESS and performs a curtailment that reduces the effect of line loss at the PCC points. The performance verification of the proposed algorithm is conducted through a simulation on MATLAB, the benefits of shared ESS and the economic feasibility of reducing the curtailment are also analyzed. Moreover, the results of shared ESS benefits and curtailment allocations based on power sensitivity are analyzed for each PV power producer. The results show an improved local profit and PCC power flow.