Abstract

Due to the generation uncertainty of photovoltaic (PV) power generation, it has been posing great challenges and difficulties in maintaining the stability, security, and reliability of PV-storage systems (one kind of microgrid). To overcome these challenges and difficulties, this paper is concerned with secondary control and robust energy management for PVs in a grid-connected microgrid (MG) considering uncertainty. In our designs, to maintain the stable operation of PVs in MG, a novel secondary control method combining an event-triggered finite time sliding mode controller (FTSMC) and consensus controllers is proposed. Furthermore, a robust optimization framework is established to minimize the total cost of grid-connected MG involving the operation cost of multi-battery Energy Storage Systems (BESSes) and the electricity purchased from the main grid. To eliminate the effects of PV uncertainty, the optimization problem with uncertain constraints is converted into a new optimization problem with only deterministic constraints by using the box theory to represent the PV outputs. In other words, the robust optimization strategy makes uncertain boundaries easier to be represented by setting all uncertain parameters into an uncertain domain involving all typical extreme cases. Then, a particle swarm optimization (PSO) method is employed to solve the newly converted optimization problem. Finally, the experimental results validate the effectiveness of the proposed integrated framework.

Highlights

  • Due to growing shortages of fossil energy and environmental deterioration caused by fossil energy, lots of countries in the world are committed to the research of renewable energy, and their high attention and strong support from relevant policies have significantly promoted the rapid development of photovoltaic (PV)-storage system

  • The control work is completed through using a consistency controller and event-triggered finite time sliding mode controller (FTSMC)

  • In the robust energy management strategy, the uncertainty of PV output, multi-BESSs, and TOU price are all considered in the optimization model

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Summary

Introduction

Due to growing shortages of fossil energy and environmental deterioration caused by fossil energy, lots of countries in the world are committed to the research of renewable energy, and their high attention and strong support from relevant policies have significantly promoted the rapid development of photovoltaic (PV)-storage system This system is one kind of microgrids (MGs) (i.e., it is a small power grid that includes distributed generators (DGs), loads, and battery energy storage systems (BESSes)). PV power generation incorporated into MG include uncertainty and volatility of the PV output, and in practice, it is difficult to predict such uncertainty and volatility It always causes great challenges and difficulties for MGs in implementing reliable operation, ensuring power quality, achieving energy management, and maintaining economic efficiency [1,2].

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