Increasing the penetration of Renewable Energy Sources (RES), the heat pumps are an alternative solution to facilitate the integration of RES into district heating. To hedge against the intermittency of RES, the flexibility potentials of the thermal inertia of buildings are unlocked and integrated into power systems. This paper suggests a novel structure to control the mixing loop of residential heating systems supplied by electrically operated district heating. The Economic Model Predictive Control (EMPC) is proposed to optimize the heat demand of the buildings in response to electricity market price. The EMPC controls the temperature and flow rate of forward/return water in the mixing loop to minimize the energy consumption cost of households. The thermal dynamics of the buildings are modeled by 3-state differential equations to integrate the flexibility potentials of thermal inertia into the district heating. The approach optimizes the heat consumption of the building with multi-temperature zones. The Continuous-Time Stochastic Model (CTSM) is addressed to determine the thermal dynamics of the building using sensor data. Finally, a 150 m² Danish test house with four temperature zones is simulated. The simulation results show that the suggested approach not only minimizes the energy consumption cost but also provides flexibility for the Danish Electricity Market.

提高可再生能源 (RES) 的普及率，热泵是促进可再生能源整合到区域供热的替代解决方案。为了避免可再生能源的间歇性，建筑物热惯性的灵活性潜力被释放并集成到电力系统中。本文提出了一种新的结构来控制由电动区域供热提供的住宅供暖系统的混合回路。提出了经济模型预测控制（EMPC）来优化建筑物的热需求以响应电力市场价格。EMPC 控制混合回路中进/回水的温度和流量，以最大限度地降低家庭的能源消耗成本。建筑物的热动力学通过三态微分方程建模，以将热惯性的灵活性潜力整合到区域供热中。该方法优化了具有多温区的建筑物的热消耗。连续时间随机模型 (CTSM) 用于使用传感器数据确定建筑物的热动力学。最后，一个 150 m²模拟具有四个温度区的丹麦试验室。模拟结果表明，所建议的方法不仅最大限度地降低了能源消耗成本，而且还为丹麦电力市场提供了灵活性。