Design and optimal energy management of community microgrids with flexible renewable energy sources

A Model Predictive Control-Based Decision-Making Strategy for Residential Microgrids

“…Thus, the benefits of the presence of the storage options could be further explored by ensuring these exchanges are done in an optimal way. More realistic relationships can be used to describe the performance of the renewable energy technologies (e.g., variation of efficiency of generation units at part-loads [46,47], defining alternating power function and state of charge for storage systems [28,48]), or using clustering techniques to select typical operating periods [49,50].…”

“…Eng 2022, 3 101 Microgrids are capable of operating either in grid, connected, or autonomous operation mode during a faulted situation, yet their stability, reliability, and operational control is more challenging during the islanded mode [27,28].…”

“…In traditional hierarchical control architectures, the control model has three levels [29]: the primary control, responsible for load sharing and for maintaining stability and autonomous operation, the secondary control, which restores the voltage/frequency offsets introduced by the primary control, and the tertiary control level, to calculate the optimal references for the microgrid sources based on economic objectives. Modern architectures utilize approaches ranging from decentralized and distributed multi-agent [30,31], bilevel programming and reinforcement learning [28], fuzzy logic [32], or genetic algorithms [33] for control and coordination purposes.…”

“…MPC is currently a popular control methodology for industrial and process applications, largely due to its inherent ability to efficiently handle constraints in multivariable dynamical systems [39]. It comprises characteristics such as optimization of power flow in the microgrid, incorporating the costs of generation and operation of the DER systems as constraints [28]. The rolling (or receding) horizon concept has been broadly used in control methods as a means to deal with control problems when a cost function has to be minimized in a given time horizon.…”

Day-Ahead Optimal Scheduling of an Integrated Energy System Based on a Piecewise Self-Adaptive Particle Swarm Optimization Algorithm

“…An integrated energy system (IES) can couple various forms of energy, such as electricity and natural gas, to meet the demands of users for multiple energy sources. Additionally, IESs are capable of realizing the complementary utilization of energy, reducing the operation cost of the system, promoting the absorption of solar/wind power [1,2], improving energy efficiency, and mitigating pollution emissions, which makes them a viable option to solve the energy and environmental problems [3]. Optimal energy flow (OEF) calculation provides a basis for the economic operation of IESs.…”