Volume 5: Innovative Solutions for Energy Transitions: Part IV

Optimization of Charging/Discharging Strategy of Distributed Battery Storage System in Buildings Using Dynamic Programming Ruiting, Wang Fulin Wang, Bin Hao, Yutong Li, Wei Feng



This paper developed a new control strategy of distributed battery storage in response to price signal as an effective way of demand side management, using dynamic programming algorism to calculate the hourly power use from grid. An office building in Shenzhen, China was studied, verifying the feasibility of the control strategy. The result turned out that the total electricity cost can be saved by 28.1% comparing with a system without distributed battery storage, and by 8.1% comparing with a system where the distributed battery storage operates in the strategy of constant grid power taking.
Furthermore, the relationship of electricity cost with battery size and maximum charging/discharging power was studied. Based on the model, capacity and maximum charging/discharging power of battery fit well with a segmented linear model, in the range of practical application. The maximum charging/discharging power of battery storage system and minimum electricity fee could be fitted into a quadratic polynomial model. These findings could provide information and give reference for battery storage system design and operation.

Keywords energy storage system, demand side management, dynamic programming, control strategy, price signal

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