Economic optimisation for a building with an integrated micro-grid connected to the national grid

Phan Quang An, M. D. Murphy, Michael C. Breen, T. Scully
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引用次数: 7

Abstract

This paper proposes a novel operating cost optimisation method for a building with an integrated micro-grid (MG) connected to the National Power Grid (NPG). The MG consists of a photovoltaic system (PVS) and a lead-acid battery bank (BB). The optimisation utilised a twenty-four hour forecast of building energy consumption and the corresponding electrical prices from the NPG. A piecemeal decision algorithm (PDA) and a particle swarm optimisation (PSO) algorithm were used to generate a charge/discharge rates schedule for the BB. The building energy consumption model was developed using empirical data and employee work schedules. Electricity prices were predicted using a real time pricing (RTP) model based on data from the single electricity market operator (SEM-O)[1]. The PVS and BB were modelled based on specifications from manufacturers, and weather data from the Cork Institute of Technology (CIT). The simulation results demonstrate that the building operating costs can be reduced by up to 23 % per day for a single charge/discharge rates schedule, or by up to 30 % per day for a multiple charge/discharge rates schedule.
一个集成微电网连接到国家电网的建筑的经济优化
本文提出了一种集成微电网(MG)与国家电网(NPG)连接的建筑运行成本优化方法。MG由一个光伏系统(pv)和一个铅酸蓄电池组(BB)组成。优化利用了24小时建筑能耗预测和NPG相应的电价。采用分段决策算法(PDA)和粒子群优化算法(PSO)生成了BB的充放电率调度。利用实证数据和员工工作时间表建立了建筑能耗模型。使用基于单一电力市场运营商(SEM-O)[1]数据的实时定价(RTP)模型预测电价。PVS和BB是根据制造商的规格和科克理工学院(CIT)的天气数据进行建模的。模拟结果显示,采用单一充电/放电率计划,建筑物的营运成本每天最多可减少23%,而采用多个充电/放电率计划,建筑物的营运成本每天最多可减少30%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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