Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models

Xiaojuan Han, Hua Zhang, Xiaoling Yu and Lina Wang

Applied Energy, 2016, vol. 184, issue C, 103-118

Abstract: For the generation planning problem of grid-connected micro-grid system with photovoltaic (PV) and energy storage system (ESS), taking into consideration of photovoltaic subsidy policy, two-part tariff and time-of-use (TOU) power price, on the base of cost-benefit analysis (CBA), a generation planning model of micro-grid system including low-carbon economy is established with the objective of the maximum lifecycle net profit in this paper. Many optimization algorithms such as the particle swarm optimization (PSO), artificial fish swarm (AFS), genetic algorithm (GA), Artificial Bee Colony (ABC) algorithm and Interior-point algorithm are respectively used to solve the model for comparison analysis. The generation planning results of micro-grid system and its economic benefits are compared with the above five optimization algorithms from the actual data in a certain area of Shanghai in China. A simulation tests show that the economic benefit obtained by the PSO algorithm is obviously higher than the others. Meanwhile for the financing problems of micro-grid system with small and medium PV system, the user-self-investment model, third-party financing model and joint venture model are introduced into the micro-grid system, compared with the economic performance of the three models. The simulation results show that third-party financing model can reduce owners’ upfront investment for micro-grid system, and both owners and third-party financing providers can benefit from it, which is an effective method to solve the financing difficulty and popularize PV applications.

Keywords: Micro-grid; Generation planning; Cost-benefit analysis; User-self-investment model; Third-party financing model; Joint venture model (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (30)

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DOI: 10.1016/j.apenergy.2016.10.008

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