Novel configuration and optimum energy flow management of a grid-connected photovoltaic battery installation. (July 2020)

• Record Type: Journal Article
• Authors: Guidara, Imen; Souissi, Anoir; Chaabene, Maher
• Is Part Of: Computers & electrical engineering. Volume 85(2020)
• Publication Date: 2020-07
• Subjects: Grid-connected photovoltaic-battery installation -- Battery sizing -- Self-consumption strategy -- Energy management algorithm; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106677
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Optimal sizing of battery storage of a grid-connected photovoltaic-battery installation. Energy management and control algorithm to select the appropriate supply source. Power flow dispatching based on operating scenarios. Improvement of self-consumption to reduce the grid electricity purchase. Abstract: Integrating an energy storage device into a grid-connected photovoltaic system not only increases the self-consumption of the installation, but it also helps to solve the many issues related to photovoltaic power grid injection. Thus, the first phase of this study interested in determining the optimal battery capacity for a grid-connected photovoltaic installation with the objective of minimizing the operating cost. The second phase consisted in the implementation of an energy management algorithm to manage the energy flows of the grid-connected photovoltaic-battery installation. Therefore, five operating scenarios were introduced in an attempt to maximize self-consumption, control the battery safety, and minimize the load consumption from the grid. Three home consumption profiles were implemented in this study (5 KVA, 10 KVA, and 17 KVA). Optimal battery capacity value for each load was obtained using an optimization algorithm. Results of the energy management algorithm confirmed that the self-consumption improvement, the battery protection, and the continuity of load supply. Thus, the efficiency of the proposed solution was confirmed by a 100% self-consumption for a load less than 10 KVA and 86% for a 17 KVA load. Graphical Abstract: Image, graphical abstract