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Development of a Markov-Chain-Based Energy Storage Model for Power Supply Availability Assessment of Photovoltaic Generation Plants

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4 Author(s)
Junseok Song ; Dept. of Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX, USA ; Krishnamurthy, V. ; Kwasinski, A. ; Sharma, R.

A new Markov-chain-based energy storage model to evaluate power supply availability of photovoltaic generation is proposed. Since photovoltaic resources have high output variability subject to weather conditions, energy storage can be added in order to increase the availability of photovoltaic generation. Although adding energy storage is a promising strategy to improve the availability of photovoltaic generation, energy storage sizing to meet a certain availability must be taken into account in order to avoid over-sizing or under-sizing capacity, which are two undesirable conditions leading to increased system cost or inadequate availability, respectively. This paper proposes a new Markov-chain-based energy storage model to develop a power supply availability framework for photovoltaic generation. The proposed work models energy states in a photovoltaic-energy storage system in order to understand the nature of charge/discharge rates for energy storage that affect the system's power output. This developed Markov chain model may assist when planning both large and small-scale grid integrated photovoltaic generation because energy state's behavior of the photovoltaic-energy storage model can be used for forecasting expected power output. In addition, an example using lithium-ion batteries is given in order to explore the effects on availability of energy storage capacity degradation.

Published in:

Sustainable Energy, IEEE Transactions on  (Volume:4 ,  Issue: 2 )

Date of Publication:

April 2013

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