Optimal sizing and economic analysis of Photovoltaic distributed generation with Battery Energy Storage System considering peer-to-peer energy trading


Yaldız A., Gökçek T. , Şengör İ., Erdinç O.

SUSTAINABLE ENERGY GRIDS & NETWORKS, vol.28, pp.100540, 2021 (Journal Indexed in SCI Expanded)

  • Publication Type: Article / Article
  • Volume: 28
  • Publication Date: 2021
  • Doi Number: 10.1016/j.segan.2021.100540
  • Title of Journal : SUSTAINABLE ENERGY GRIDS & NETWORKS
  • Page Numbers: pp.100540

Abstract

Demand for distributed generation (DG) systems has increased in recent years as costs have decreased, policies pursuing zero carbon emission objectives have been implemented, and energy demand has increased, in addition to technological advancements in renewable energy systems. With this increase in the number of DGs, a concept known as Peer-to-Peer (P2P) energy trading has been emerging, which offers innovative solutions in which new generation users take an active role in the market. This concept enables further efficient and optimal resource utilization by providing buying and selling via the P2P market together with the grid. With optimal resource sizing in the proposed structure, maximum self-sufficiency, shorter payback periods, and economical use of energy resources are supplied. This study maximizes the net profit by deducting the gain to customers from the use of Photovoltaic (PV) and Battery Energy Storage Systems (BESS) from their costs. Moreover, an optimal PV/BESS sizing for prosumers is attained through the use of a mixed-integer linear programming (MILP) based algorithm structure. Consumers offer energy with the most economical price in this proposed system through the P2P energy market. On the other hand, capital, replacement, and maintenance costs are all taken into account for a further realistic approach. The case studies of prosumers and consumers trading energy in Peer-to-Grid (P2G) and P2P are contrasted, as is the return on investment and the economic benefit of PV/BESS sizing during the operational time.