Thermal Battery Modeling of Inverter Air Conditioning for Demand Response

Since thermal energy generated by air conditionings (ACs) can be stored in the buildings providing the potential of shifting electricity consumption between different time periods, ACs are considered as an important demand response (DR) resource and attract extensive attentions. In order to achieve the compatibility of the inverter ACs with the current dispatch models, this paper attempts to model an inverter AC system as a thermal battery (TB). The comparisons between the TB and the lithium-ion battery are given. In order to protect the end-users' privacy and relieve the computational burden of the centralized control, a hierarchical control framework is designed and an aggregated TB model is proposed to handle the heterogeneity of the inverter ACs. A finite-horizon optimization model is used to compare the operating performances of the aggregated TBs and the lithium-ion batteries. Simulation results demonstrate that the aggregated TB model works well with the power dispatch model developed for the lithium-ion batteries. In other words, with the TB modeling of ACs, lithium-ion batteries can be replaced in current dispatch models providing service for the grid.

I. Introduction

Load fluctuations are becoming increasingly serious due to the integration of both large scale intermittent energy sources (e.g., wind and solar power) and new loads (e.g., electric vehicle load) to the grid. This will not only require the electric power system to perform better in frequency regulation and peak shaving but also challenge operators in economic assessment under the environment of electricity market. Traditionally, it is considered that end users’ are inelastic and the adjustment of generators is the only effective way to keep real-time supply-demand in a balance. However, too frequent control times increase the mechanical stress on these generators [1] and the increased capacity of spare generators causes huge waste due to too little usage time. Recent developments in smart grid, particularly the two-way communication network and advanced metering infrastructure, can enable end-users to obtain informed electricity price and communicate with control centers [2]. Thus, it becomes possible to adjust end-users’ loads to participate in the system operation. As one of the key technologies of smart grid, demand response (DR) has been widely accepted for the reason that it is able to relieve the tension of supply-demand unbalance, strengthen the grid’s ability of dealing with power fluctuations, improve energy efficiency and reduce the economic loss of utilities. Among all flexible loads, air conditionings (ACs) can shift load within a certain time and have attracted much more attention [3], [4].