Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
764876 | Energy Conversion and Management | 2010 | 10 Pages |
This paper presents the development of an optimized fuzzy logic based photovoltaic (PV) energy dispatch controller using a swarm intelligence algorithm The PV system considered is grid-independent and consists of a fuzzy logic controller (FLC), PV arrays, battery storage, and two types of loads: a constant critical load and a time-varying non-critical load. The swarm intelligence applied in this paper is the particle swarm optimization (PSO) algorithm and is used to optimize both membership functions and rule set of the FLC. By using PSO algorithm, the optimized FLC is able to maximize energy to the system loads while also maintaining a higher average state of battery charge. This optimized FLC is then compared with the standard energy dispatch controller, referred to as the “PV-priority” controller. The PV-priority controller attempts to power all loads and then charge the battery resulting on lesser number of days of power to critical loads unlike the optimized FLC.