Abstract

Taking the power load of an industrial park in Shanghai as an example in this paper, particle swarm optimization and cost-benefit model are employed to analyse the economy of new lithium-ion batteries, echelon lithium-ion batteries and lead-carbon batteries in photovoltaic energy storage systems in the whole life cycle. The research results showed that the economic order from large to small among different batteries in the photovoltaic energy storage system was new lithium-ion battery, echelon utilization lithium-ion battery and lead-carbon battery. The declines in energy storage cost and discount rate and the rise in peak electricity price can greatly improve the net present value of a photovoltaic-energy storage system (PV-BES) system.

Highlights

  • By the end of 2019, the installed capacity of photovoltaic power generation in Shanghai has exceeded 1GW

  • It is worth noting that if the unstable photovoltaic factors are introduced into the stable power grid system on a large scale, the safe and stable operation of the power grid will be affected [1]

  • Battery energy storage system is a necessary technical solution. It is expensive for most families, it has more advantages than disadvantages as a buffer pool for variable photovoltaic power [2]

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Summary

Introduction

By the end of 2019, the installed capacity of photovoltaic power generation in Shanghai has exceeded 1GW. When the uncontrollable photovoltaic is connected to the distribution network of residential quarters, there will be voltage fluctuation, flicker, reverse power flow and other problems. Battery energy storage system is a necessary technical solution. It is expensive for most families, it has more advantages than disadvantages as a buffer pool for variable photovoltaic power [2]. The profit of pv-bes hybrid system is evaluated based on battery type, energy storage cost, discount rate and peak price. The evaluation results have important guiding significance for the further development of photovoltaic and bes industries

Methodology and parameters
Net Present Value Analysis
Influencing Factors of NPV
Conclusions
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