A novel asynchronous time-scale holistic control method for heating system based on the energy state space

Abstract

Optimal characteristic parameters and control strategies in the operation of urban heating systems are significant for carbon reduction and high efficiency. Considering load fluctuations and real-time outdoor temperature changes, this research constructs steady-state and dynamic heat current models of the heating system based on the standard thermal resistance model. Combined with genetic algorithms, an optimal setting method is proposed for the operating characteristic parameters of the heating system under variable operating conditions. To achieve the control of the optimal characteristic parameters, the dynamic heat current model is applied to derive the system energy state space equations and obtain the state space parameter matrix. Moreover, a holistic control strategy for the heating system based on the optimal node parameters is proposed. The control simulation results show that the proposed holistic control strategy based on the optimal node temperature can save energy by 25.4 % compared with the fixed node temperature. Meanwhile, the exergy efficiency of the heating system increases by 2.3 %. That is, the proposed asynchronous time-scale holistic control method is significant for the day-ahead optimal regulation strategy of the district heating system.