Distributed optimal-tracking control to coordinate the optimization of active distribution networks with automatic generation control

Abstract

To the shortage of automatic generation control (AGC) resources in power systems with high proportions of renewable generators, this paper proposes an optimal-tracking control strategy to integrate the optimization of active distribution networks (ADNs) into AGC. Different ADNs can coordinate to absorb the power fluctuations beyond AGC adjustment ranges in a distributed way. First, we build a time-varying model to integrate the optimization of ADNs into AGC, which gives the power allocation mechanism among different ADNs and AGC units in real time. Second, we design a distributed strategy to continuously drive the operation of ADNs to the solutions of the time-varying model using the optimal-tracking sensitivities calculated based on the feedback of measurements. In this strategy, the measurements of net load powers are calculated using the integral of the area control error in AGC; moreover, the optimal-tracking sensitivities are decomposed into several items of which each one only relates to the inner information of the transmission network or an ADN, which is deduced according to the physical laws of power flow of transmission and distribution networks. Based on the decomposition, each ADN can form the optimal-tracking sensitivities only based on its inner information and some coordination information from the transmission network. Thus, the distributed optimal-tracking controller is achieved. Finally, the effectiveness of the proposed control strategy is verified by case studies: ADNs are regulated to effectively restrain the excessive frequency deviations, caused by the sharp fluctuations of renewable generator outputs, with meeting the operational constraints of ADNs (e.g. the constraints on voltages) in real time.