Thermostatically controlled loads (TCLs), such as air conditioners (ACs), are important demand response resources—they have a certain heat storage capacity. A change in the operating status of an air conditioner in a small range will not noticeably affect the users’ comfort level. Load control of TCLs is considered to be equivalent to a power plant of the same capacity in effect, and it can significantly reduce the system pressure to peak load shift. The thermodynamic model of air conditioning can be used to study the aggregate power of a number of ACs that respond to the step signal of a temperature set point. This paper analyzes the influence of the parameters of each AC in the group to the indoor temperature and the total load, and derives a simplified control model based on the two order linear time invariant transfer function. Then, the stability of the model and designs its Proportional-Integral-Differential (PID) controller based on the particle swarm optimization (PSO) algorithm is also studied. The case study presented in this paper simulates both scenarios of constant ambient temperature and changing ambient temperature to verify the proposed transfer function model and control strategy can closely track the reference peak load shifting curves. The study also demonstrates minimal changes in the indoor temperature and the users’ comfort level.

The integration of large-scale renewable energy poses great challenges for the operation of power system because of its increased frequency fluctuations. More load frequency control (LFC) resources are demanded in order to maintain a stable system with more renewable energy injected. Unlike the costly LFC resources on generation side, the thermostatically controlled loads (TCLs) on the demand side become an attractive solution on account of its substantial quantities and heat-storage capacity. It generally contains air conditioners (ACs), water heaters and fridges. In this paper, the supplementary LFC is extracted by the modeling and controlling of aggregated ACs. We first present a control framework integrating the supplementary LFC with the traditional LFC. Then, a change-time-priority-list method is proposed to control power output taking into account customers’ satisfaction. Simulations on a single-area power system with wind power integration demonstrate the effectiveness of the proposed method. The impact of ambient temperature changes and customer preferences on room temperature is also involved in the discussion. Results show that the supplementary LFC provided by ACs could closely track the LFC signals and effectively reduce the frequency deviation.

Various residential electricity pricing strategies provide diverse methods for calculating consumption costs. Due to the existence of electricity company monopolies and single residential electricity pricing systems, residents of certain areas have no option but to accept the electricity pricing offered to them. Based on local residential electricity pricing strategies, a virtual electricity retailer (VER) mechanism is put forward. The proposed VER mechanism includes a pricing package plan (PPP), a consumption-based plan, an add-on plan, and an exclusive plan. A PPP optimization pricing model was established to maximize VER profits when taking into account income, allowances from sponsors, expenditures and customer savings. Finally, payment processes were designed under a fixed pricing system and a time-of-use pricing environment. This case study shows the impact of PPPs and the allowance and demonstrates that the model helps customers save electricity while maximizing VER profits.