Electrical energy becomes necessary for human being. Generation of electrical energy mostly depends on fossils fuel, they are limited in nature and also responsible for environmental pollution. Renewable energy resources provides a better alternative for future,In comparison to conventional energy resources economical aspect is a major issue of renewable energy sources with the feasibility and efficiency. These limitations are tried to overcome by deployment hybrid renewable energy resources. There are certain criteria to analyze and implement the sized, optimized and cost efficient system. This paper focus on hybrid energy systems based on solar photovoltaic (PV) and wind resources. This paper shed lights on various parameters of economic feasibility, sizing strategies with logical advancements to enhance their utilization, future prospects, and their arrangement. Strategies to develop an effective storage system is also presented here.A brief review on developments in optimization techniques, reliability index and cost analyzing techniques for hybrid renewable energy systems are also presented.

Review of solar photovoltaic and wind hybrid energy systems for sizing strategies optimization techniques and cost analysis methodologies

https://www.econstor.eu/bitstream/10419/244061/1/1694150933.pdf

Modelling and optimization of an off-grid hybrid renewable energy system for electrification in a rural areas

Electrification of villages is a vital step for improving the techno-economic conditions of rural areas and crucial for the country’s overall development. The villages’ welfare is one of the main aims of the rural electrification programs. Rural electrification is relatively costly compared to electrification of urban areas. Now, the research question is to find the best combinations of HRES from the available resources in a given village location that can meet the electricity demand in a sustainable manner and to see whether this is a cost-effective solution or not. This study is an attempt to structure a model of electricity generation based on multiple combinations of HRES with the application of HOMER energy software at an identified off-grid village location in India. The main objectives of this study are to analyze the best-suited configuration of a hybrid RE system out of various combinations to meet the village load requirement reliably, continuously and sustainably. The study also reduces the total system net present cost and least cost of energy (COE) using multi-objective HOMER Pro software. In this study, a resource assessment and demand calculation have been carried out and the COE per unit has been ascertained for different systems and configurations. A combination of PV–Wind–Biomass–Biogas–FC along with battery has been identified as the cheapest and most dependable solution with a COE of $0.214/kWh.

Techno-economic analysis of off-grid solar/wind/biogas/biomass/fuel cell/battery system for electrification in a cluster of villages by HOMER software

This paper mainly focuses on the optimal design of a grid-dependent and off-grid hybrid renewable energy system (RES). This system consists of Photovoltaic (PV), Wind Turbine (WT) as well as Fuel Cell (FC) with hydrogen gas tank for storing the energy in the chemical form. The optimal components sizes of the proposed hybrid generating system are achieved using a novel metaheuristic optimization technique. This optimization technique, called Improved Artificial Ecosystem Optimization (IAEO), is proposed for enhancing the performance of the conventional Artificial Ecosystem Optimization (AEO) algorithm. The IAEO improves the convergence trends of the original AEO, gives the best minimum objective function, reaches the optimal solution after a few iterations numbers as well as reduces the falling into the local optima. The proposed IAEO algorithm for solving the multiobjective optimization problem of minimizing the Cost of Energy (COE), the reliability index presented by the Loss of Power Supply Probability (LPSP), and excess energy under the constraints are considered. The hybrid system is suggested to be located in Ataka region, Suez Gulf (latitude 30.0, longitude 32.5), Egypt, and the whole lifetime of the suggested case study is 25 years. To ensure the accurateness, stability, and robustness of the proposed optimization algorithm, it is examined on six different configurations, representing on-grid and off-grid hybrid RES. For all the studied cases the proposed IAEO algorithm outperforms the original AEO and generates the minimum value of the fitness function in less execution time. Furthermore, comprehensive statistical measurements are demonstrated to prove the effectiveness of the proposed algorithm. Also, the results obtained by the conventional AEO and IAEO are compared with those obtained by several well-known optimization algorithms, Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Grey Wolf Optimizer (GWO). Based on the obtained simulation results, the proposed IAEO has the best performance among other algorithms and it has successfully positioned itself as a competitor to novel algorithms for tackling the most complicated engineering problems.

An improved artificial ecosystem optimization algorithm for optimal configuration of a hybrid PV/WT/FC energy system

Using renewable energy sources instead of fossil fuels is one of the best solutions to overcome greenhouse gas (GHG) emissions. However, in designing clean power generation microgrids, the economic aspects of using renewable energy technologies should be considered. Furthermore, due to the unpredictable nature of renewable energy sources, the reliability of renewable energy microgrids should also be evaluated. Optimized hybrid microgrids based on wind and solar energy can provide cost-effective power generation systems with high reliability. These microgrids can meet the power demands of the consuming units, especially in remote areas. Various techniques have been used to optimize the size of power generation systems based on renewable energy to improve efficiency, maintain reliability, improve the power grid’s resilience, and reduce system costs. Each of these techniques has shown its advantages and disadvantages in optimizing the size of hybrid renewable energy systems. To increase the share of renewable energies in electricity supply in the future and develop these new technologies further, this paper reviews the latest and most efficient techniques used to optimize green microgrids from an economical and reliable perspective to achieve a clean, economical, and highly reliable microgrid.

https://www.mdpi.com/1996-1073/15/9/3359/pdf?version=1651822482

Intelligent and Optimized Microgrids for Future Supply Power from Renewable Energy Resources: A Review

In this paper, a new maximum power point tracking (MPPT) framework for photovoltaic (PV) systems is presented based on the remora optimization algorithm (ROA) subjected to standard and partial shading conditions. The studied system includes a PV array, a DC/DC converter, and a load and MPPT control system. The control variable is the voltage, and the optimization variable is the converter duty cycle, which is optimally determined using the ROA that is inspired based on the parasitic behavior of remora for achieving the maximum power of the PV system. In this study, the ability of the ROA is compared with manta ray foraging optimization (MRFO) and particle swarm optimization (PSO) methods for the MPPT solving of different shading patterns in view of extracted power, efficiency, and tracking rate. The results show that the ROA is a competitive method with higher efficiency in maximum power tracking and convergence accuracy than the MRFO and PSO for the MPPT solving of different patterns with higher exploration power. Moreover, an examination of the two partial shading patterns also showed that the power extracted using the ROA is higher than the MRFO and PSO while also reaching the global power value more quickly. The ROA achieved a tracking efficiency of 99.97% in a partial shading condition, with faster tracking in comparison with the MRFO and PSO methods. Therefore, the ROA is a high-speed tracking optimization method for enhancing the PV system’s efficiency in standard and especially in shading conditions.

/pdf/a-new-maximum-power-point-tracking-framework-for-11yztgwg.pdf

A New Maximum Power Point Tracking Framework for Photovoltaic Energy Systems Based on Remora Optimization Algorithm in Partial Shading Conditions

— This paper presents an Optimization Sizing of a stand-alone PV/FC/Wind Hybrid System (PFWHS) to optimize the sizes of components of PFWHS. Based on PSO algorithm, one optimal sizing method was developed to determine the optimal configuration of system that can achieve the load required power supply probability (Reliability) with a minimum overall cost of energy (OCE).PFWHS costs involve investments, operation and maintenance as well as loss of load costs. The applied wind and radiation datasets belong to northwest region (Jolfa, latitude: 38_56, longitude: 45_37, altitude: 710, m) of Iran. In this paper the impact of availability of PFWHS components is investigated on optimal sizing. So, to investigating the impact of component availability rate on costs and PFWHS reliability due to failure and repair rate of PFWHS components and uncertainty in wind speed and solar irradiance, two scenarios are considered. In first scenario the availability of all components is considered 1 and in second scenario isn’t considered 1 because of failure and repair rate of components and uncertainty in wind speed and solar irradiance. Obtained results prove that while the overall cost of energy is optimized, the reliability indices are within a satisfactory bound with regard to the reliability standards. Also the results indicate that considering complete availability of components causes more reliability rate, so to achieve the actual behavior of PFWHS, the rate of components availability must be considered in suitable insight to designer for supply the load.

/pdf/economic-designing-of-pv-fc-wind-hybrid-system-considering-1nk3gb7cf4.pdf

Saber Arabi

Papers

A New Maximum Power Point Tracking Framework for Photovoltaic Energy Systems Based on Remora Optimization Algorithm in Partial Shading Conditions

Economic Designing of PV/FC/Wind Hybrid System Considering Components Availability