This paper presents two optimal control strategies for a grid independent photovoltaic system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). The first strategy is based on Action Dependent Heuristic Dynamic Programming (ADHDP), a model-free adaptive critic design (ACD) technique which optimizes the control performance based on a utility function. ADHDP critic network is used in a PV system simulation study to train an action neural network (optimal neurocontroller) to provide optimal control for varying PV system output energy and loadings. The second optimal control strategy is based on a fuzzy logic controller with its membership functions optimized using the particle swarm optimization. The emphasis of the optimal controllers is primarily to supply the critical base load at all times, thus requiring sufficient stored energy during times of less or no solar insolation. Simulation results are presented to compare the performance of the proposed optimal controllers with the conventional priority control scheme. Results show that the ADHDP based controller performs better than the optimized fuzzy controller, and the optimized fuzzy controller performs better than the standard PV-priority controller.

Meeting Name

41st IAS Annual Meeting of the Industry Applications Conference, 2006


Electrical and Computer Engineering

Keywords and Phrases

Adaptive Critic Designs; Battery Storage; Energy Dispatch and Management; Fuzzy Logic; Neural Networks; Optimal Control; Particle Swarm Optimization; Photovoltaic System; Solar

International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2006 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 2006