基于物理-数据融合的楼宇用电需求响应潜力分析

Demand Response Potential Analysis of Buildings Based on Physical-data Fusion Method

建筑楼宇能耗在能源总消耗量中所占比重较大,需求响应技术可以充分利用楼宇的用电需求响应(demand respond,DR)潜力,提高电网功率平衡的稳定性。提出了一种基于物理-数据融合的楼宇用电需求响应潜力分析方法,可以实现对楼宇DR潜力的准确评估。首先基于楼宇的用电能耗模型,提出了物理-数据融合算法可对模型的关键参数进行修正;其次,定量分析了楼宇DR潜力的时变特性,并通过物理-数据融合算法对计算过程中负荷模型产生的误差进行修正,表明DR潜力的容量、速率和概率是DR潜力的主要指标;最后,考虑建筑的固有蓄热特性,提出了提高楼宇DR潜力的智能优化策略。通过实例分析,给出了一种考虑楼宇DR潜力时变特性的智能DR策略,证明了该方法的合理性和有效性。

Energy consumption of buildings accounts for a large proportion of total energy consumption.Demand response(DR)potential of buildings can be fully utilized through the demand response technologies,which can improve the stability of power balance on power grid.This paper proposes a physical-data fusion method for buildings which can achieve the accurate assessment of demand response potential.Firstly,based on the energy consumption model of buildings,a physical data fusion algorithm is proposed to modify the key parameters of the model.Secondly,the time-varying characteristics of buildings’DR potential are quantitatively analyzed,and the errors generated by load model during the calculation was also corrected through physical-data fusion algorithm,which shows the capability,rate and probability are the main indicators for DR potential.Thirdly,considering of the inherent thermal storage characteristics of buildings,an optimization strategy is proposed to improve the demand response potential of buildings.Finally,through the analysis of a case study,a building DR strategy considering the time-varying characteristics of DR potential is proposed,which proves the rationality and effectiveness of the physical-data fusion method.