Optimal design and evaluation of solar bifacial PV-wind-battery-split genset hybrid power system

Abstract

A Hybrid Power System (HPS) is a power generation system consisting of renewable and non-renewable means of energy generation, and an energy storage scheme. It is considered as a more suitable alternative energy generation for sustainable development in off-grid and grid-connected applications. However, the optimal design of the components making up the HPS is very essential in reducing not only the total cost and environmental effects of the system, but to also improve its reliability. Most of the existing solution methods were found to be time-consuming, unable to handle a large number of control variables and suffer from slow convergence speed; leading to system designs with low-quality optimal solutions. Thus, there is need to develop an HPS model with a fast run time and high speed of convergence, that is reliable and cost-effective. This work, therefore, aims to design an optimal off-grid hybrid solar bifacial PV-wind-battery-split Genset power system model using Giza Pyramids Construction (GPC) Algorithm as an optimization technique. Individual component of the proposed HPS is modeled in Simulink using their respective mathematical equations. In order to increase the share of renewable energy in the optimal system design, a bifacial PV, which has the ability to generate more additional energy compared to the conventional monofacial PV was used as the solar generator component. The performance of the bifacial PV module is evaluated by determining the most appropriate orientation state capable of producing more additional energy. A multi-objective optimization solution method was employed to find the optimal design of the proposed HPS using the GPC algorithm. The proposed approach was applied to study four case studies including (split genset only, wind/battery/split genset, bifacial PV/battery/split genset and Bifacial PV/wind/battery/split genset) to meet the load requirement of a remote community located in northern part of Nigeria using real time meteorological data of the area. The performance evaluation of the GPC algorithm was done by comparing its solution with those obtained using Firefly Algorithm (FA) and Whale Optimization Algorithm (WOA) techniques respectively using Life Cycle Cost (LCC) and Total Environmental Pollution (TEP) as performance metrics. To further illustrate the performance of the GPC algorithm, a comprehensive comparison based on numerical analysis is carried among the reported optimization algorithms. Simulation results showed that the optimal design of the proposed HPS consisting of Bifacial PV/wind/battery/split genset is the most practical energy solution to meet the energy requirement of the studied area, as all the three algorithms predicted the lowest values of LCC and TEP for the optimal configuration as compared to using the split genset only with LCC and TEP values of $1,830,752.40 and 3,241,987.00 kg respectively. The LCC and TEP obtained using the proposed algorithm, WOA and FA techniques are $803,599.09 and 1,265,933.58 kg, $799,243.58 and 1,188,139.91 kg and $836,135.65 and 1,469,829.44 kg respectively; which corresponds to 56.10 % and 60.95 %, 56.34 % and 63.35 % and 54.32% and 54.66 % reduction as compared to the split genset only configuration. The results also showed that GPC algorithm converges faster than the two other optimization algorithm and has a simulation run time of 9.78 minutes as compared to 10.59 and 12.28 minutes recorded for both WOA and FA techniques respectively. Moreover, the results of numerical analysis carried out on the fitness score of the objective function over 20 runs showed that the GPC algorithm has a standard deviation and efficiency of 1.0096 and 96.28 % as compared to 3.4915 and 87.09; and 07142 and 97.36 estimated for both WOA and FA techniques respectively. Generally, the results demonstrate the robustness and efficient performance of the GPC algorithm as compared to WOA and FA techniques in solving optimal design problem of HPS. The significant reduction in the values of LCC and TEP of the proposed approach is expected to enhance wider acceptability of HPS consisting of both renewable and non-renewable energy sources among policy makers, decision makers, government agencies and power system engineers for sustainable development and a safer environment.