混合能源协同控制的智能家庭能源优化控制策略

发布时间：2018-05-31 13:19

本文选题：家庭能源管理系统 + 智能家庭　；参考：《电工技术学报》2017年12期

【摘要】：家庭能源优化控制是家庭能源管理系统(HEMS)的重要分支之一,然而由于缺少有效的智能优化算法,制约了家庭能源优化控制的实际应用。本文通过对家用电器运行特性的分析,将家庭用电设备分为刚性负荷,简单可调节负荷,电池类设备,供暖、通风和空调(HVAC)系统设备等,并建立相应的负荷模型;以市电电网、光伏发电、储能电池三种能源作为智能家庭的供给源,以电能花费和用户舒适度作为优化目标,建立混合能源协同控制的智能家庭能源优化控制模型;并提出一种基于改进的快速粒子群算法(APSOA)的智能求解方法,得出每个电器最优的用电时段,室温控制系统各个时段所需功率以及蓄电池各个时段的充放电功率。以某智能家庭夏季某一天用电情况为例,在Matlab环境下,建立模型并仿真,与粒子群算法(PSOA)、遗传算法(GA)进行对比,说明了模型和算法的可行性及有效性。
[Abstract]:The household energy optimal control is one of the important branches of the household energy management system (HEMS). However, due to the lack of effective intelligent optimization algorithm, the practical application of the household energy optimization control is restricted. Based on the analysis of the operating characteristics of household appliances, this paper divides the household electrical equipment into rigid load, simple adjustable load, battery equipment, heating, ventilation and air conditioning HVAC system equipment, and establishes the corresponding load model. Photovoltaic power generation, energy storage battery as the supply source of intelligent home, power consumption and user comfort as the optimization goal, the intelligent home energy optimal control model based on hybrid energy collaborative control is established. An intelligent solution method based on improved fast particle swarm optimization algorithm (APSOA) is proposed. The optimal power of each electrical appliance, the power required for each period of room temperature control system and the charge and discharge power of battery in each period are obtained. Taking the electricity consumption of an intelligent family in summer as an example, a model is built and simulated in Matlab environment, and compared with particle swarm optimization (PSO), genetic algorithm (GA), the feasibility and effectiveness of the model and algorithm are illustrated.
【作者单位】：东北石油大学电气信息工程学院;
【基金】：黑龙江省普通高等学校新世纪优秀人才培养计划资助项目(1252-NCET-006)
【分类号】：TU855

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