With the implementation of clean energy heating project in rural areas of northern China, the pollution of coal-fired heating in winter has been greatly improved. However, the use of large-scale electric heating equipment put forward new challenges to the power supply reliability of low-voltage distribution network. Especially in rural power grid, the load is heavy in winter and low in other seasons. It is one of the effective measures to achieve optimal resource allocation and improve the power supply quality of the distribution grid to exploit the demand response potentialities of electric heating loads, and motivate electric heating loads to actively respond to demand response programs (DRP) for peak-load shifting. Therefore, a load optimal control strategy for rural electric heating equipments based on demand side peak load regulation was proposed in this paper. A market transaction model was designed for third-party agency companies to represent coal-to-electricity users in the peak shaving market. The agency company made the centrally control strategies of electric heating users’ equipment according to the peak shaving volume and corresponding price obtained from the peak shaving market bidding. The electric heating users were classified based on the controllability of each user by the agency company. Each kinds of users could get different compensation price to encourage them to participate in the demand response programs for peak-load shifting. In this market model, a multi-objective optimization model was established to control the users’ air source heat pump. The goals of the optimization model were to meet the user's temperature demands to the maximum extent and to maximize the benefit of the agent company. Meanwhile, user's comfort requirements for indoor temperature were considered in this model, and the user classification compensation mechanism was introduced to improve the user's initiative to participate in peak load regulation. Taking the load data of electric heating users in Pinggu District of Beijing as an example, the simulation analysis was carried out. The results show that the total load reduction of all electric heating equipment was 159.773 kWh, there was no over-control for anyone user, the load reduction of each user fluctuated around average reduction of 7.989 kWh, the peak valley of the user's power consumption curve was changed, the optimal control strategy proposed in this paper played the role of peak load reduction and valley filling, which can relieve the pressure of the upper power grid during peak load period. The indoor temperature of the users was (18±1) ℃, which meet the demand of comfortable temperature for heating in winter. Compared with the target of not considering the benefit, the one-day compensation cost of the agency company was saved 31.9%, and the users with the highest degree of control got the most compensation income, the peak load regulation strategy could encourage the users to participate in the peak load regulation actively. [ABSTRACT FROM AUTHOR]