Implementation of an effective hybrid model for islanded microgrid energy management

Abstract

Objective: To propose an effective hybrid model for predictive control (EHMPC) to efficiently manage demand and supply of energy for a microgrid operating in islanded mode operation. Due to the intermittent nature of renewable energy sources and variation in load in the microgrid, maintaining the system stability and reliability along with the economy is a critical issue to be addressed. In the islanded mode of operation, the voltage and frequency have to be monitored in addition to managing energy storage units. The different uncertainties occurring at various stages of microgrid should be taken into account to operate the microgrid with reliability under critical condition Methods: This paper proposes an effective algorithm to efficiently control the operation of microgrid and to operate it with optimal efficiency and reliability. In this work, we have proposed a three-stage control of the microgrid where the first stage consists of the arbitrarily distributed generation (ADG) stage, the second stage has energy storage unit (ESU), and the final stage has the energy management scheme (EMS). Finding: A case study has been carried out and the proposed method is found to be better in performance, economical and robust in comparison with the conventional two-stage model predictive control (MPC) optimization approach. Further important parameters have been analyzed. Novelty: To overcome the limitations of conventional MPC algorithm, we propose a three-stage EHMPC algorithm it consists of three stages, ADG had the first stage of the algorithm the main features of this stage. To optimize the placement, sizing, power factor, minimize network losses and maximize DG integration. The second stage has ESU, the main features of this stage to improve control strategy for optimal power management of microgrid and the final stage has the EMS, to improve tested analysis for a real-time islanded microgrid under various load conditions.

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