Abstract
An AC security constrained unit commitment (AC-SCUC) in the presence of the renewable energy sources (RESs) and shunt flexible AC transmission system (FACTS) devices is conventionally modeled as a deterministic optimization problem to minimize the operation cost of conventional generation units (CGUs) subject to AC optimal power flow (AC-OPF) equations, operation constraints of RESs, shunt FACTS devices, and CGUs. To cope with the uncertainties of load and RES generation, robust and stochastic optimization and linearized formulation have been used to achieve a sub-optimal solution. To arrive at a more optimal solution, an evolutionary algorithm-based adaptive robust optimization (EA-ARO) approach to solve the non-linear and non-convex optimization problem was proposed. A hybrid solver of grey wolf optimization (GWO) and teaching learning-based optimization (TLBO) was proposed to solve the AC-SCUC problem in the worst-case scenario to obtain robust and reliable optimal solution. Finally, the proposed method was simulated on standard IEEE test systems to demonstrate its capabilities, and the results showed the proposed hybrid solver obtained robust optimal solutions with reduced computation time and standard deviation. Moreover, the numerical results proved the proposed strategy’s capabilities of improving the economics of generation units, such as lower operational cost, and enhancing the performance of the transmission networks, such as improved voltage profile and reduced energy losses.
Highlights
INTRODUCTIONThe problem included AC power flow (AC-PF) constraints, transmission network technical constraints, conventional generation units (CGUs) operation models, spinning reserve formulations, as well as operational constraints associated with renewable energy sources (RESs) and parallel flexible AC transmission system (FACTS) devices
NUMERICAL RESULTS AND DISCUSSION The numerical results of the proposed AC security constrained unit commitment (AC-security-constrained unit commitment (SCUC)) problem applied to the modified IEEE 6-bus and IEEE 118-bus networks were described
This research attempted to solve the AC-SCUC problem considering the uncertainty of load forecast and renewable energy sources (RESs) generation forecast in the presence of parallel flexible AC transmission system (FACTS) devices
Summary
The problem included AC-PF constraints, transmission network technical constraints, CGU operation models, spinning reserve formulations, as well as operational constraints associated with RESs and parallel FACTS devices This problem had mixed integer non-linear programming (MINLP) frameworks, with binary (continuous) variables that are independent (dependent) for the uncertain parameters. In consideration of the third research gap, the evolutionary algorithm-based ARO (EA-ARO) were used to model the uncertainties In this method, a bi-level model that did not require the use of duality theory or linearization of equations for the robust AC-SCUC problem was expressed, and its optimal solution was obtained by the EA. - Modeling of uncertainties in the load forecast and active power generation of RESs in the AC-SCUC problem using adaptive robust optimization based on the evolutionary algorithm. - Using the hybrid TLBO and GWO algorithms to obtain a reliable optimal solution, in a comparatively low computation time, with low standard deviation
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