access icon openaccess Advanced control strategy for an energy storage system in a grid-connected microgrid with renewable energy generation

The operating cost of the consumer can be reduced in an electricity market-based environment by shifting consumption to a lower price period. This study presents the design of an advanced control strategy to be embedded in a grid-connected microgrid with renewable and energy storage capability. The objectives of the control strategy are to control the charging and discharging rates of the energy storage system to reduce the end-user operating cost through arbitrage operation of the energy storage system and to reduce the power exchange between the main and microgrid. Instead of using a forecasting-based approach, the proposed methodology takes the difference between the available renewable generation and load, state-of-charge of energy storage system and electricity market price to determine the charging and discharging rates of the energy storage system in a rolling horizon. The proposed control strategy is compared with a self-adaptive energy storage system controller and mixed-integer linear programming with the same objectives. Empirical evidence shows that the proposed controller can achieve a lower operating cost and reduce the power exchange between the main and microgrid.

Inspec keywords: integer programming; power generation control; linear programming; pricing; renewable energy sources; power grids; adaptive control; distributed power generation; power markets; energy storage

Other keywords: renewable energy storage capability; grid-connected microgrid; discharging rates; mixed-integer linear programming; advanced control strategy; electricity market-based environment; forecasting-based approach; renewable energy generation; self-adaptive energy storage system controller; charging discharging rates; end-user operating cost reduction; electricity market price; power exchange

Subjects: Distributed power generation; Optimisation techniques; Power system management, operation and economics; Control of electric power systems; Optimisation techniques; Self-adjusting control systems

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-stg.2018.0024
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