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Probabilistic optimal sizing of stand-alone PV systems with modeling of variable solar radiation and load demand

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3 Author(s)
Ng, S.K.K. ; Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China ; Zhong, J. ; Cheng, J.W.M.

This paper presents a comprehensive sizing methodology which could contain all key elements necessary to obtain a practical sizing result for a stand-alone photovoltaic (PV) system. First, a stochastic solar radiation model based on limited/incomplete local weather data is formulated to synthesis various chronological solar radiation patterns. This enables us to evaluate a long-term system performance and characterize any extreme weather conditions. Second, a stochastic load simulator is developed to simulate realistic load patterns. Third, two reliability indices, Expected-Energy-Not-Supplied (EENS) and Expected-Excessive-Energy-Supplied (EEES), are incorporated with an Annualized Cost of System (ACS) to form a new objective function called an Annualized Reliability and Cost of System (ARCS) for optimization. We then apply a particle swarm optimization (PSO) algorithm to obtain the optimum system configuration for a given acceptable risk level. An actual case study is conducted to demonstrate the feasibility and applicability of the proposed methodology.

Published in:

Power and Energy Society General Meeting, 2012 IEEE

Date of Conference:

22-26 July 2012