Renewable energy solutions are appropriate for on-grid and off-grid applications, acting as a supporter for the utility network or rural locations without the need to develop or extend costly and difficult grid infrastructure. As a result, hybrid renewable energy sources have become a popular option for grid-connected or standalone systems. This paper examines hybrid renewable energy power production systems with a focus on energy sustainability, reliability due to irregularities, techno-economic feasibility, and being environmentally friendly. In attaining a reliable, clean, and cost-effective system, sizing optimal hybrid renewable energy sources (HRES) is a crucial challenge. The presenters went further to outline the best sizing approach that can be used in HRES, taking into consideration the key components, parameters, methods, and data. Moreover, the goal functions, constraints from design, system components, optimization software tools, and meta-heuristic algorithm methodologies were highlighted for the available studies in this timely synopsis of the state of the art. Additionally, current issues resulting from scaling HRES were also identified and discussed. The latest trends and advances in planning problems were thoroughly addressed. Finally, this paper provides suggestions for further research into the appropriate component sizing in HRES.

/pdf/a-comprehensive-review-on-techno-economic-analysis-and-3ofwoqcb.pdf

A Comprehensive Review on Techno-Economic Analysis and Optimal Sizing of Hybrid Renewable Energy Sources with Energy Storage Systems

Global population rises, as does the demand for energy, but countries' access to energy sources becomes increasingly constrained. With a growing population and diminishing fossil fuel reserves, hybrid systems are essential for overcoming the intermittent nature of renewable energy sources (RESs). Solar, biomass, wind, biogas, etc. are only few of the RESs that are being considered for use in the generation of electricity today. In addition to lowering carbon emissions, these systems also deliver improved efficiency, lower costs, and more reliability in their electrical output. This article begins with a discussion of renewable energy (RE) principles, their necessity, the projects undertaken in this field, and a comparison with conventional power plants. Then, we introduce and examine the most effective ways for integrating renewable energy sources into existing power systems. 

Hybrid Renewable Energy Sources: Their Potential to Meet Electricity Demand

Optimized FOPID Controller for Transient Stability Improvement in a Microgrid with Energy Storage

Decentralized electricity production solutions based on renewable energies are increasingly used in Africa to promote the social inclusion of the population in rural areas. In these areas not served by the electricity network, there are more and more network infrastructures installed by mobile network operators that are powered by genset. These energy sources only serve to provide electricity to the site elements while the local population lives without electricity. The use of microgrid based on renewable energies, particularly solar energy, on these operator sites can contribute to achieving goals 7 and 9c of the Sustainable Development Goals. Indeed, intelligent management of these microgrids can ensure a continuous supply of electricity to the mobile network operators' sites and the use of excess production to offer electricity to the local population. To achieve this convergence between universal access to telecommunications and energy, based on these microgrids, the use of an optimization algorithm for better planning and operating efficiency of these microgrids is essential. To this end, the Particle Swarm Optimization algorithm was used for optimal power flow management in a multi-source and multi-load system to test the ability of microgrids to achieve this new objective. The obtained results showed that an optimal management of these microgrids guarantees a Loss of Power Supply Probability of 0.18 %, a Levelized Cost of Electricity of US$ 0.0187, and a Maximum Renewable Factor of 98%. Low cost of electricity obtained shows that this solution is a real opportunity for increasing universal access to electricity for low-income populations in rural areas. Similarly, the Maximum Renewable Factor value obtained shows a reduction in the running time of the genset, with the consequence of significantly reducing operating costs and greenhouse gas emissions.

Energy Flow Management in a Smart Microgrid Based on Photovoltaic Energy Supplying Multiple Loads

Optimal sizing of an HRES with probabilistic modeling of uncertainties − a framework for techno-economic analysis

An optimal energy mix of various renewable energy sources and storage devices is critical for a profitable and reliable hybrid microgrid system. This work proposes a hybrid optimization method to assess the optimal energy mix of wind, photovoltaic, and battery for a hybrid system development. This study considers the hybridization of a Non-dominant Sorting Genetic Algorithm II (NSGA II) and the Grey Wolf Optimizer (GWO). The objective function was formulated to simultaneously minimize the total energy cost and loss of power supply probability. A comparative study among the proposed hybrid optimization method, Non-dominant Sorting Genetic Algorithm II, and multi-objective Particle Swarm Optimization (PSO) was performed to examine the efficiency of the proposed optimization method. The analysis shows that the applied hybrid optimization method performs better than other multi-objective optimization algorithms alone in terms of convergence speed, reaching global minima, lower mean (for minimization objective), and a higher standard deviation. The analysis also reveals that by relaxing the loss of power supply probability from 0% to 4.7%, an additional cost reduction of approximately 12.12% can be achieved. The proposed method can provide improved flexibility to the stakeholders to select the optimum combination of generation mix from the offered solutions.

/pdf/multi-objective-hybrid-optimization-for-optimal-sizing-of-a-3gee9b5v.pdf

Multi-Objective Hybrid Optimization for Optimal Sizing of a Hybrid Renewable Power System for Home Applications

According to the Federal Communications Commission (FCC), the spectrum utilization has been increasing in a rapid manner. In order to overcome the shortage of spectrum that caused by increased network capacity and the mobile services needed to carry over the spectrum, CRN has been introduced for accomplishing the temporary wireless communication tasks. In CRN secondary users can operate the idle channels those are not engaged by the primary users. Therefore, in CRN for utilizing those idle channels Medium Access Control (MAC) protocols faces some challenges, such as spectrum sensing, spectrum sharing, spectrum management, spectrum mobility, maximize throughput, maximize data transmission and minimize channel rendezvous time. In general, neighbor discovery and channel rendezvous is the main challenge in CRN. To overcome these types of issues, many protocols have been proposed for CRN. However, these protocols are short-off to provide efficient channel rendezvous in many scenarios. In this paper, we have come up with an Efficient Sequence Based Receiver Initiated MAC named as SB-RIM for CRN using Latin Square Sequence Based Technique. This new approach allows the secondary users in CRN to discover neighbor(s), share spectrum and access the available channel(s). Finally, we have evaluated and implemented through simulation and it provides better performance in terms of number of iteration and different performance metrics.

An Efficient Sequence Based Receiver Initiated Multi-Channel Medium Access Control Protocol for Cognitive Radio Network

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Multi-Objective Hybrid Optimization for Optimal Sizing of a Hybrid Renewable Power System for Home Applications

An Efficient Sequence Based Receiver Initiated Multi-Channel Medium Access Control Protocol for Cognitive Radio Network