Optimal Modeling and Feasibility Analysis of Grid-Interfaced Solar PV/Wind/Pumped Hydro Energy Storage Based Hybrid System

Abstract

Access to inexpensive, clean energy is a key factor in a country’s ability to grow sustainably The production of electricity using fossil fuels contributes significantly to global warming and is becoming less and less profitable nowadays. This work therefore proposes to study the different possible scenarios for the replacement of light fuel oil (LFO) thermal power plants connected to the electrical network in northern Cameroon by renewable energy plants. Several scenarios such as the combination of solar photovoltaic (PV) with a pumped hydro storage system (PHSS), Wind and PHSS and PV-Wind-PHSS have been studied. The selected scenarios are evaluated based on two factors such as the system’s total cost (TC) and the loss of load probability (LOLP). To achieve the results, metaheuristics such the non-dominated sorting whale optimization algorithm (NSWOA) and non-dominated sorting genetic algorithm-II (NSGA-II) have been applied under MATLAB software. The optimal sizing of the components was done using hourly meteorological data and the hourly power generated by the thermal power plants connected to the electrical grid. Both algorithms provided satisfactory results. However, the total cost in the PV-PHSS, Wind-PHSS, and PV-Wind-PHSS scenarios with NSWOA is, respectively, 1%, 6%, and 0.2% lower than with NSGA-II. According to NSWOA results, the total cost for the PV-Wind-PHSS scenario at LOLP 0% is 4.6% and 17% less than the Wind-PHS and PV-PHSS scenarios, respectively. The profitability study of all three scenarios showed that the project is profitable regardless of the scenario considered.

A Multi-Objective Approach to Hybrid Renewable Energy Systems: Cascading Hydropower for Solar and Wind Variability Compensation

“…In terms of water dispatch ability, cascade reservoirs outperform single reservoirs. Equation (3) determines the output power of cascade hydropower stations [24]. = Water level of downstream of reservoir '𝑖' with respect to time 't'.…”

“…A multi-objective model considering the maximization of economic gain while limiting power production fluctuation, minimizing economic risk while maximizing financial return, and so on has been established in numerous previous researches on the hybrid power system [16,17]. While many studies have looked at small-scale systems, they tend to focus on their short-term operations and neglect to analyze their long-term operational potential [18,19]. Considering the smoothness of the output variance and the potential annual power generation, this work builds a multi-objective model for a long-term hydro-PV wind hybrid power system.…”

Optimal Design and Sizing of Hybrid Photovoltaic/Fuel Cell Electrical Power System

“…Advanced control strategies, incorporating innovative algorithms and machine learning techniques, are being extensively explored to optimize system performance and enhance energy management efficiency. In parallel, researchers are diligently investigating the integration of energy storage technologies, such as advanced batteries, supercapacitors, and hydrogen storage, which enables the smooth incorporation of intermittent renewable energy sources, thereby enhancing system flexibility and reliability [44,45]. The development of diverse optimization models and simulation tools, considering factors like weather conditions, load profiles, and component characteristics, is a key focus area, with the goal of achieving an optimal design and sizing of hybrid systems, leading to notable improvements in efficiency and cost-effectiveness [46][47][48].…”

Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant

“…The WOA metaheuristic optimization method does a better job of quickly finding high-performance zones in single and multi-objective functions cases in hybrid renewable energy sources [35]. Banerjee et al [36] used a different method based on the HS algorithm to change the reactive power in a model of an autonomous hybrid power system.…”