Abstract
A novel optimization strategy is proposed to achieve a reliable hybrid plant of wind, solar, and battery (HWSPS). This strategy’s purpose is to reduce the power losses in a wind farm and at the same time reduce the fluctuations in the output of HWSPS generation. In addition, the proposed strategy is different from previous studies in that it does not involve a load demand profile. The process of defining the HWSPS capacity is carried out in two main stages. In the first stage, an optimal wind farm is determined using the genetic algorithm subject to site dimensions and spacing between the turbines, taking Jensen’s wake effect model into consideration to eliminate the power losses due to the wind turbines’ layout. In the second stage, a numerical iterative algorithm is deployed to get the optimal combination of photovoltaic and energy storage system sizes in the search space based on the wind reference power generated by the moving average. The reliability indices and cost are the basis for obtaining the optimal combination of photovoltaic and energy storage system according to a contribution factor with 100 different configurations. A case study in Thumrait in the Sultanate of Oman is used to verify the usefulness of the proposed optimal sizing approach.
Highlights
Optimal sizing of hybrid renewable plants is essential for utilizing the available resources effectively while at the same time avoiding under- or overestimating the size of the power plants.The intermittent nature of wind speed and solar irradiation mandates the use of optimization methodologies to exploit the complementary nature of wind and solar power sources in a way to mitigate output power fluctuations
The second stage is to get an optimal size of PV and BESS based on the smoothed output of wind power
The results show the impact of wind power on the cost of energy (COE) and the sizes of PV and BESS
Summary
Optimal sizing of hybrid renewable plants is essential for utilizing the available resources effectively while at the same time avoiding under- or overestimating the size of the power plants. Rajkumar et al [8] presented a dynamic programming model, which was used to obtain the optimal loss of the power supply probability (LPSP) and the cost of energy (COE) of a hybrid solar incorporating battery (BESS) and an auxiliary wind plant. In all the studies mentioned, the sizing approaches focus on optimizing the size of HWSPS by minimizing the cost in a way to guarantee the required reliability of power supply. The authors in [27] used two predetermined BESS capacities, one designed for energy and the other for power smoothing, depending on the reference PV power produced from MAV and a low-pass filter. The MAV of wind power is used to generate a smooth reference power within the operational ramping rates instead of using the load demand profile to build an HWSPS.
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