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Planning Energy Storage and Photovoltaic Panels for Demand Response with Heating Ventilation and Air Conditioning Systems
IEEE Transactions on Industrial Informatics ( IF 12.3 ) Pub Date : 2018-11-01 , DOI: 10.1109/tii.2018.2833441
Mohemmed Alhaider , Lingling Fan

The objective of this engineering problem is to determine the size of a battery energy storage system and number of photovoltaic (PV) panels to be installed in a building with Heating Ventilation and Air Conditioning systems (HVACs) as the main load. The building is connected to the power grid where electricity price is varying at different hours. This engineering problem is formulated as an optimization problem with a goal to achieve minimum installation cost and operation cost while satisfying room temperature requirements. Stochastic PV outputs are taken into consideration as well. The mathematical problem formulated is a large-scale mixed integer linear programming (MILP) problem. To improve the solving speed, two Benders decomposition strategies are applied to solve this stochastic MILP problem. The optimization problem will lead to the battery energy capacity, power limit, number of PV to be installed, as well as the on/off status of HVACs over 8 h. The contribution of this paper is the implementation of Benders decomposition methods to reduce the computation complexity. Parallel computing structure and maximum feasible subsystem cut generation strategy have been exploited and implemented in this research.

中文翻译:

规划供热通风和空调系统的需求响应的储能和光伏面板

此工程问题的目的是确定电池能量存储系统的大小和要安装在以供暖通风和空调系统(HVAC)为主要负载的建筑物中的光伏(PV)面板的数量。该建筑物已连接到电网,在该电网中,电价在不同时间有所变化。该工程问题被表述为优化问题,其目标是在满足室温要求的同时实现最小的安装成本和运营成本。随机光伏输出也要考虑在内。公式化的数学问题是大规模混合整数线性规划(MILP)问题。为了提高求解速度,应用了两种Benders分解策略来解决此随机MILP问题。优化问题将导致电池能量容量,功率限制,要安装的PV数量以及超过8小时的HVAC的开/关状态。本文的贡献是实现了Benders分解方法,以降低计算复杂度。并行计算结构和最大可行子系统切割生成策略已在本研究中得到开发和实现。
更新日期:2018-11-01
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