Adaptive global energy optimal management strategy based on the Pontryagin’s minimum principle: An isolated microgrid example

Abstract

Optimal control is a common control strategy to solve complex non-linear systems. Pontryagin’s minimum principle, as a typical optimal control theory, is widely used in energy management systems. Due to the randomness of new energy generation and the diversity of load power consumption, microgrid energy management system is a complex non-linear stochastic system. The efficient operation of microgrid energy management strategy largely depends on the real-time performance of the control algorithm. Pontryagin’s minimum principle is an offline control strategy, whose co-state variable λ depends on expert experience and needs to be manually adjusted according to different working conditions, so it is difficult to achieve real-time optimal control. First, the energy management system model of island-type microgrid is established in this paper. In order to improve the economy of power generation and prevent battery over-charge or over-discharge, the state of charge (SOC) change of battery pack is comprehensively considered, and the fuel cost and pollutant treatment cost are taken as the objective function. Second, an adaptive Pontryagin’s minimum principle energy management strategy is proposed. By introducing the penalty mechanism and adjusting the parameters adaptively, the problem that the open-loop control of Pontryagin’s minimum principle needs to adjust the co-state variables in real time is solved. Comparative experiments show that compared with Pontryagin’s minimum principle and particle swarm optimization, adaptive Pontryagin’s minimum principle can not only limit battery SOC within the ideal range but also effectively reduce the daily operation cost of microgrid. Experimental results verify the effectiveness of the proposed algorithm.