A Schedule Method of Battery Energy Storage System (BESS) to Track Day-Ahead Photovoltaic Output Power Schedule Based on Short-Term Photovoltaic Power Prediction
A Schedule Method of Battery Energy Storage System (BESS) to Track Day-Ahead Photovoltaic Output Power Schedule Based on Short-Term Photovoltaic Power Prediction
- Author(s): Tingting Yang ; Xiangjun Li ; Lei Qi ; Dong Hui ; Xuecui Jia
- DOI: 10.1049/cp.2015.0316
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- Author(s): Tingting Yang ; Xiangjun Li ; Lei Qi ; Dong Hui ; Xuecui Jia Source: International Conference on Renewable Power Generation (RPG 2015), 2015 page ()
- Conference: International Conference on Renewable Power Generation (RPG 2015)
- DOI: 10.1049/cp.2015.0316
- ISBN: 978-1-78561-040-0
- Location: Beijing, China
- Conference date: 17-18 Oct. 2015
- Format: PDF
In order to maximize the ability to improve the photovoltaic (PV) system tracking schedule output, based on the short-term prediction power of PV and randomness of prediction error, an energy storage day-ahead scheduling policy that adopts chance-constrained programming is proposed. The PV/energy storage output within the upper and lower range of schedule plan is taken as the objective function, the energy storage charge and discharge power and the state of charge (SOC) constraints are considered. In order to get each time charge and discharge power, the method adopts improved adaptive particle swarm optimization (PSO) algorithm based on Monte Carlo simulation. With typical output of PV power station as an example, the simulation results verify the feasibility and flexibility of the proposed strategy, it also provides effective reference scheme for day-ahead control of battery energy storage systems.
Inspec keywords: battery storage plants; photovoltaic power systems; particle swarm optimisation; power generation scheduling; Monte Carlo methods
Subjects: Optimisation techniques; Monte Carlo methods; Solar power stations and photovoltaic power systems; Other power stations and plants
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