Optimization And Economic Analysis Of Distributed Energy Storage System

With the growing energy demand in buildings,renewable energy has been a popular research issue.The distributed PV-storage system,as a development direction of renewable energy,is being widely application,flexible scheduling and friendly to the grid.However,how to maintain it's trade-off between investment and payback rate is complicated.Optimized design and control of energy storage systems can improve the economics of distributed PV-storage systems,but it is necessary to clarify the primary and secondary relationships between economic factors.In this paper,we focused on the distributed photovoltaic-energy storage system in buildings.The minimum power consumption of the system is taken as the objective function.Based on the Energyplus software and the mathematical model,the distributed PV-storage system operating parameters are set.Based on the Python programming language,a dynamic programming method is used to present the optimal control and the energy storage system management.Based on the weight of building function,thermal design partition,grid price signal and battery cost performance parameter,the economic benefit of this system is assessed in terms of net value.Also,a control strategy is proposed to optimize the self-suppression of photovoltaic power generation and economic benifit.Taking Chan gsha as an example,distributed photovoltaics are analyzed with different dynamic electricity prices,energy storage capacity and unit cost.Economic changes and feasible areas of energy storage systems,as well as the impact on photovoltaic consumption.T he main conclusions are listed as follows:(1)Comprehensive comparison of the economic impact factors of each system: energy storage unit capacity cost> energy storage capacity> energy storage cycle life> dynamic retail price> thermal design zone>Feed-in tariff price> building function> battery charge and discharge power.Energy storage unit capacity cost is the most important factor affecting system economy,while energy storage charge and discharge power has little impact on system economy.(2)The economic comparison of system weight in representative cities indicates that :in Harbin,Beijing and Guangzhou is mainly affected by energy storage capacity,unit cost and dynamic electricity price,in Changsha is mainly affected by energy storage units cost,capacity and Feed-in tariff price,in Kunming is mainly affected by the cost,capacity and on-grid price of energy storage units.(3)41.5% increase in dynamic electricity price leads to 87% increase in the system economic feasible domain,and system capacity design is the most important determinant of system economy.(4)In the interval II,the unit cost change of the battery is the dominant factor,and the photovoltaic waste capacity is increased with the cost reduction;when the unit capacity cost is reduced by the I interval,The battery capacity becomes the limiting factor of the self-suppression of photovoltaic residual electricity.As the battery capacity increases,the photovoltaic self-discharging capacity increases.