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... this work, the individual of the considered optimization problem contains three variables (or genes), which are: A PV , A w , and C b . The used GA is based upon using the flowchart of Figure 7, to yield the optimal solution. Initially, the GA selects individuals at random from the current population to be parents and uses them to produce the children for the next generation by using the three main operations, which are the selection, crossover, and mutation operations. ...
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Die vorliegende Studie geht der Frage nach, welche Lehren aus den aktuellen Erfahrungen mit Ausschreibungssystemen für Windenergie in Argentinien, Brasilien, Deutschland, Italien, Spanien und Südafrika sowie den historischen in Großbritannien und Irland für Länder gezogen werden können, in denen ebenfalls über die Einführung von EE-Ausschreibungen...
Cost efficient deployment of wind energy is in focus for reaching ambitious targets for renewable energy and transforming the energy supply to one based on renewables. However, as more wind is being deployed the available sites onshore become less attractive in terms of wind conditions and capacity factor and more resistance from population groups...
Citations
... Kasaeian et al. [12] looked into the use of a hybrid PV, biomass, and diesel system to supply an Iranian community with grid-connected electricity, while Santos et al. [13] studied two hybrid plants in Brazil and found that PV/wind/battery energy systems were the most cost-effective and reliable choice for supplying electricity to remote loads. Ramoji et al. [14] optimized a PV/wind/battery energy system to lower the overall cost of components and ensure dependable load supply. Halabi et al. [15] conducted performance analyses on two operational decentralized power plants in Malaysia and found that renewable energy in conjunction with storage systems could help lower energy costs. ...
... To achieve an optimal hybrid system design, it is crucial to consider and fulfill all operational constraints. These constraints are represented by (9)- (14), which restricts the limits and requirements of the objective function. By incorporating these constraints into the design process, the hybrid system can be optimized to meet operational demands while adhering to the specified limitations. ...
In rural areas, grid expansions and diesel generators are commonly used to provide electricity, but their high maintenance costs and CO2 emissions make renewable energy sources (RES) a more practical alternative. Traditional methods such as analytical, statistical, and numerical-based techniques are inadequate for designing an energy-efficient RES. Therefore, this study utilized the bat algorithm (BA) to optimize the use of hybrid RES for rural electrification. A feasibility study was conducted in the village of Kalema to assess energy consumption, and a diesel-only system was modeled to serve the entire community. The BA was used to determine the optimal size and cost-effectiveness of the hybrid RES, with MATLAB R (2021a) utilized for simulation. The BA's performance was compared with diesel only and GA using cost of energy (COE) and CO2 emissions as metrics. Diesel generators only produced a COE of $6,562,000 and 1679.6 lb/hr of CO2 emissions. COE with BA was $356,9781.37 (a 45.6% reduction) and CO2 emissions were 635.29 lb/hr (a 62.2% drop). Genetic algorithm (GA) resulted in $364,3122.46 COE and 652.69 lb/hr CO2 emissions, indicating 61.1% and 44.5% decreases, respectively. BA significantly reduced COE and CO2 emissions over GA, according to the analysis.
... It is assumes in this section that the PV array operates at its maximum power point and the effects of temperature are negligible [57]. The model of the solar PV system is a stand-alone off-grid system consisting of solar panels, batteries, inverters, and a charge controller. ...
This article aims to compare the efficiency and costs of four autonomous energy production systems, including organic Rankine cycle systems in the Cameroonian context. As the national electricity distribution operator (ENEO-Cameroon) is experiencing difficulties in meeting customer demand, there has been a significant increase in the use of these SAPE in households. It was essential to carry out a study to propose the optimal SAPE for different types of households. To achieve this goal, three main types of households have been established: Then, an energy balance of each category was carried out to determine the appropriate SAPE. The results show that the Organic Rankine Cycle system offers a better compromise for High Standing Households (HSH), with a net present value of $20,000, a levelized energy cost of $0.13 per kWh and a total life cycle cost of $10,000. The photovoltaic system is suitable for all categories of households, with an energy conversion rate of 36.45%, a PBP of 2.5 years, but a levelized energy cost of 0.19 dollars/kWh, higher than that of the Rankine organic cycle. This study highlighted the impact that an informed choice of autonomous energy production systems can have on the overall energy bill of Cameroonian households.
... Since the problem under consideration consists of integer decision variables, numbers of wind turbines, solar panels and batteries conventional Optimization methods such as probabilistic methods, Analytical methods and Iterative method can effectively give the local extremum values [4]. But due to stochastic nature of the wind and solar system, employing nature inspired meta-heuristic Algorithms may lead to the global extremum [8,[13][14][15][16][17][18]. Here the researchers apply iterative method to solve the problem and left for further research for the application and comparison of different nature inspired algorithms to solve this hybrid solar and wind renewable energy system including its cost analysis. ...
Because of depletion of fossil fuel, increasing energy demand, and increasing number of population, world has entered in to the new phase of energy extracting from alternating sources. These renewable energy sources are abundant, free from greenhouse gas and will become an alternative of fossil fuel. In this paper iteration method was involved to optimize the designed hybrid Wind and solar renewable energy system. As a result all the components are properly sized in order to meet the desired annual load with the minimum possible total annual cost.
... Matlab yazılımı kullanılarak geliştirilen algoritmanın verimli olduğu sonucuna ulaşılmıştır. Bu teknik ile maliyetler düşürülmüştür [14]. Sangeetha ve Suja yaptıkları çalışmada, rüzgâr türbini, güneş panelleri ve bataryalardan oluşan karma enerji sistemi Simulink programı ve programda yapılan optimizasyon tahminleri Matlab programı kullanılarak modellenmiştir. ...
Günümüzde enerjiye olan ihtiyaç teknolojik gelişmeler, nüfus artışı, sanayileşme ve küreselleşme gibi nedenlerden dolayı artış göstermektedir. Fosil kaynakların yetersiz oluşu ve tükenebilir olması yenilenebilir enerji kaynaklarının kullanımını ve önemini arttırmaktadır. Yenilenebilir enerji kaynaklarından daha fazla faydalanmak için hibrit sistemler geliştirilmiştir. Hibrit sistemler birden fazla kaynağın verimli şekilde kullanıldığı sistemlerdir. Türkiye’de rüzgâr ve güneş enerjisi bakımından yeterli potansiyele sahip birçok alan mevcuttur. Bu çalışmada PVSol programı kullanılarak Balıkesir İli için hibrit sistem tasarımı yapılmıştır. Hibrit sistemlerin kurulu güç kapasitesi 7-50 KW arasında değişen 10 farklı senaryo için tasarım yapılmıştır. Çalışmalarda kurulu güç kapasitesi 7-15 KW arası 5 senaryo şebekeden bağımsız, 20-50 KW arası 5 senaryo şebekeye bağlı olarak tasarlanmıştır. Şebekeden bağımsız sistemlerde kurulu güce ve üretilen enerjiye bağlı olarak akümülatör ile üretilen enerjiyi depolamak için şarj regülatörü seçimleri yapılmıştır. Çalışma temiz ve güvenilir enerji üretim sistemleri güneş ve rüzgâr enerjisini hibrit olarak kullanması yönüyle diğer yenilenebilir enerji sistemlerinden üstünlük göstermektedir.
... M.Amer et al. [16] presented a particle swarm optimization method for reducing the levelized energy cost of an hybrid renewable energy system. In [17] S.K.Ramoji et al. considered a genetic algorithm to design the hybrid photovoltaic/ wind/ storage system where the objectives was minimizing the total cost which included initial costs, yearly replacement cost, yearly operating cost and maintenance costs. Three scenarios were proposed by M.Elsied et al. [18] for developing an energy management system to determine the optimal operating strategies that minimize the energy costs, pollutant emissions, and hence maximizing the consumption energy produced from the available renewable energy resources by using the genetic algorithm. ...
... Grey wolf algorithm has been combined with fuzzy logic for optimal sizing of battery in HRES [8]. The authors [23] applied GA on cost optimization of the hybrid PhotoVoltaic/Wind system. ...
Two popular renewable energy sources of solar irradiation and wind speed usually offer amiable intervention, especially for rural electrification. They are useful in rural areas where the supply of electricity by the national grid infrastructure is not a viable option economically. By the gift of nature, multiple renewable energy sources are often available in those areas. Optionally, these renewable energy sources can be combined to help minimize the cost of energy production contingent on the cost of operation, the amount of energy produced, the load demand, and the environmental factors. The objective of this research task is to propose a framework for meeting the power load demand of consumers while optimizing the operational costs of hybrid renewable energy from solar and wind power. A nature-inspired/meta-heuristic optimization method is proposed in this framework, to minimize the cost of the hybrid energy subject to the required constraints from the renewable energy system. The proposed algorithm was applied to solve a hybrid energy problem. Experimentation with empirical data is conducted, and KSA is evaluated against other nature-inspired algorithms such as BAT and WSAMP with minus previous steps. The real-life data were collected in Ghana from energy farms in Accra, Kumasi and Navrongo. The efficacy of the energy optimization is found to be sensitive to the meta-heuristic algorithms (KSA, BAT and WSAMP with minus previous step). The experiment result shows that by using KSA algorithm in hybridizing solar and wind energy, the cost of electricity could be minimized and adequately meet the demand of consumers.KeywordsEdge computing deviceHybrid renewable energy systemIoT deviceKestrel-based search algorithmKestroidMeta-heuristic algorithm
... With the rapid development of multi-objective evolutionary algorithms, many researches used them in finding the optimal size of HRES. In [16]- [18] a multi-objective genetic algorithm (GA) was used for sizing a HRES. The optimization aimed to minimize costs of the system (ASC, TNPC, and COE). ...
... are the installation annual capital cost of the PV system, wind system, DG, battery bank, and inverter, respectively. The annual capital cost for each component can be calculated using equation (17), (18) [34], [37], [46], [47]. ...
This paper proposes a relatively new optimization algorithm namely the Turbulent Flow Water-Based Optimization (TFWO) to find the optimal size of a hybrid isolated microgrid generation. Moreover, validation of the proposed algorithm is proved through a comprehensive comparison with three robust performance and fast convergence algorithms which are the Harris Hawks Optimization (HHO), Whale Optimization Algorithm (WOA) and Jellyfish Search Optimizer (JSO). Two topologies with different renewable sources were considered in studying which are based on the meteorological data of the Zafarana area, a site located on the eastern coast of Egypt. The study minimizes the annual system cost (ASC) and CO
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emissions of the proposed hybrid system while considering the following constraints: Loss of Power Supply Probability (LPSP), Fraction Renewable (FR) and System Excess Energy Ratio (EER). Violation of constraints is penalized by including a penalty factor into the objective function that varies according to the amount of the violation. Moreover, a sensitivity study is presented at the end of the paper through Load variation, irradiance variation, wind speed variation, and diesel generator efficiency decreasing. Results show not only the robustness and the fast convergence of the TFWO algorithm but also its ability to minimize the annual system cost and emission costs to values better than the aforementioned optimization techniques.
... GA techniques are subsets of evolutionary algorithms characterised as global search heuristics [6]. Although containing an elitist approach, they are considered as dynamic search techniques, with a simulation where the best individual in a generation is transferred without degradation to the next generation [40]. GA use Darwin's theory (referring to the survival of the fittest among a population) consisting of three main operations (namely selection, crossover, and mutation) and three main controlling parameters (namely population size and crossover and mutation rates) [41,42]. ...
... A random selection of individuals from the initial population ("the parents") concludes with using them to generate the "children" for the next generation based on the three main operations. After that, the procedure moves on with repeated modifications of individual solutions leading towards the desired optimum population evolution over successive generations [40]. The extensive crossover and mutation processes that generate new population in every stage of the process help GA not to jeopardise adhering to the local optimum as conventional optimisation techniques can do. ...
To help stakeholders plan, research, and develop Hybrid Renewable Energy Systems (HRES), the elaboration of numerous modelling techniques and software simulation tools has been reported. The thorough analysis of these undoubtedly complex systems is strongly correlated with the efficient utilisation of the potential of renewable energy and the meticulous development of pertinent designs. In this context, various optimisation constraints/targets have also been utilised. This specific work initially carries out a thorough review of the modelling techniques and simulation software developed in an attempt to define a commonly accepted categorisation methodology for the various existing HRES simulation methods. Moreover, the widely utilised optimisation targets are analysed in detail. Finally, it identifies the sensitivity of two commercial software tools (HOMER Pro and iHOGA) by examining nine case studies based on different wind and solar potential combinations. The results obtained by the two commercial tools are compared with the ESA Microgrid Simulator, a software developed by the Soft Energy Applications and Environmental Protection Laboratory of the Mechanical Engineering Department of the University of West Attica. The evaluation of the results, based on the diversification of the renewable energy potential used as input, has led to an in-depth assessment of the deviances detected in the software tools selected.
... They are considered as dynamic search techniques containing an elitist approach. This approach is translated as a simulation step where the best individual of a generation is transferred without degradation to the next generation (Ramoji et al., 2014). GA use the theory of Darwin (referred to the survival of the fittest among a population) and consist of three main operations (namely selection, crossover and mutation) and three main controlling parameters (namely population size and crossover and mutation rates) (Rao et al., 2011;Kalogirou, 2004). ...
... They select randomly individuals from the initial population as "parents" and use them to generate the "children" for the next generation based on the three main operations. Then, they proceed with repeated modifications of individual solutions in order to lead towards the desired optimum population evolution over successive generations (Ramoji et al., 2014). Based on their extensive crossover and mutation processes which generate new population during each process step, GA don't jeopardize to adhere to the local optimum as is possible for conventional optimization techniques. ...
This chapter introduces the reader to the definition and special features of wind-based stand-alone hybrid energy systems. The introduction emphasizes on the basic characteristics of stand-alone and hybrid energy systems including also representative application examples in different sectors. After a short reference to the historic development of wind stand-alone systems, the contribution of wind energy in distributed generation is analyzed. Furthermore, a short description of the energy storage systems’ available is carried out as an essential part of hybrid energy systems. The most common commercial system configurations of stand-alone systems are discussed in detail through case studies’ results which help the reader to obtain a comprehensive view of the opportunities provided by the different combinations. Finally, an overview of wind-based hybrid energy systems optimization techniques is presented, along with the most widely adopted optimization process indicators and a short reference to the most well-known free software tools which have been extensively used for design and optimize hybrid energy systems.
... If P g (t) = P PV + P mhp ≤ P l (t) η , the generated renewable power would not be enough to meet the load demand, and the excess power requirement is provided from the battery bank. In this case, the battery is said to be in discharging stage, and SOC(t) is expressed as Equation (4) [32]: ...
Stand-alone hybrid energy systems are an enticing option for electrification in remote areas in several aspects such as grid extension difficulty, economic feasibility and reliability. The use of existing micro-hydropower (MHP) with other renewable resources in rural areas has not been well studied. Moreover, it is challenging to use mathematical optimization algorithms for these kinds of real-world problems, so the derivative-free algorithm is highly sought. In this paper, a methodology has been proposed to perform the optimal sizing, financial and generation uncertainty analysis of solar photovoltaic (SPV) based on an MHP that is proposed to handle the intermittent power output of the SPV. The analysis is performed in two cases: using storage and without storage. The optimal sizing is performed using the least present value cost and reliability constraint using different derivative-free algorithms. The storage-based hybrid system has been found to generate reliable electricity at minimal cost than without a storage-based one. This study would be helpful to propose electrification and existing micro-hydro reinforcement policies to provide reliable electricity in rural areas.
