Abstract
The unpredictable nature of the loads and non-linearity of the components of microgrid systems make optimal scheduling more complex. In this paper, a deterministic optimal load-scheduling problem is developed for microgrids operating in both islanding and grid-connected mode under different energy scenarios. Various cases are considered in this research, based on the interaction and dynamic behavior of the microgrid, considering electric vehicles (EVs) in the scenario. The aim of this research is to minimize the overall cost of microgrid operations. The concept of dynamic pricing has also been introduced in order to optimize the energy cost for the consumers. For ensuring the stability of the microgrids, a load variance index has been considered, and the fuzzy-based approach has been used for cost and load variance minimization to reduce the operation cost without compromising the stability of the microgrid. The grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations of EVs are integrated into the microgrid, which would help in valley filling and peak shaving of the loads during the off-peak and peak hours, respectively. In order to solve the proposed complex combinatorial optimization problem, elephant herding optimization (EHO) is modified and implemented. The performance of the proposed improved EHO (IEHO) is first tested on the latest CEC test functions. The results obtained by IEHO after 100 different trials are compared with the latest published methods and are found to be better based on the average value and the standard deviation for different CEC test functions. In addition, the simulation results obtained by particle swarm optimization (PSO), EHO, and proposed IEHO on a microgrid test system for different scenarios with all cases reveal that the proposed model with a mix of energy resources in the dynamic load dispatch environment bring the maximum benefits of microgrid systems. Furthermore, the results obtained from the simulation verifies that if free trade of power is allowed between the microgrids and the main grid, the process of power generation can be more economical, and further introduction of dynamic pricing into the scenario proves to be even cheaper. The implementation of the G2V and V2G operations of EVs operations in the proposed scenario not only helped in cost minimization but also helped in stabilizing the grid.
Highlights
The modern power system consists of large-scale interconnections of generators and loads at a national level, which leads to various challenges and issues such as low connectivity in far-fetched areas, optimal scheduling of generation, and controlling voltage and frequency [1]
The results prove that connecting electric vehicles (EVs) to the microgrid can be beneficial for the energy scenario of a nation
Both conventional and renewable DGs are considered for optimal load dispatch of microgrids in a deterministic environment
Summary
The modern power system consists of large-scale interconnections of generators and loads at a national level, which leads to various challenges and issues such as low connectivity in far-fetched areas, optimal scheduling of generation, and controlling voltage and frequency [1]. A deterministic multi-objective optimization problem is considered for optimal scheduling of microgrids by considering a mix of multiple dispatchable and non-dispatchable (renewables) distributed energy resources to exploit the maximum benefits of such resources over different scenarios This deterministic multi-objective optimization problem is solved using the proposed fuzzy-based improved elephant herding optimization (IEHO) approach.
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