Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty
Abstract
Abstract This paper proposes an application of the recent metaheuristic rider optimization algorithm (ROA) for determining the optimal size and location of renewable energy sources (RES) including wind turbine (WT), photovoltaic (PV), and biomass‐based Distributed Generation (DG) units in distribution systems (DS). The main objective function is to minimize the total power and energy losses. Power loss‐sensitivity factor (PLSF) is used with the ROA to determine the suitable candidate buses and accelerate the solution process. The Weibull and Beta probability distribution functions (PDF) are employed to characterize the variability of wind speed and solar radiation, respectively. The high penetration of intermittent renewable resource together with demand variations has introduced many challenges to distribution systems such as power fluctuations, voltage rise, high losses, and low voltage stability, therefore battery energy storage (BES) and dispatchable Biomass are considered to smooth out the fluctuations and improve supply continuity. The standard 33 and 69‐bus test systems are used to verify the effectiveness of the proposed technique compared with other well‐known optimization techniques. The results show that the developed approach accelerates to the near‐optimal solution seamlessly, and in steady convergence characteristics compared with other techniques.