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This paper focuses on development of optimal sizing model based on an iterative approach to optimize the capacity sizes of various stand-alone PV/wind/diesel/battery hybrid system components for zero load energy deficit. The suggested model takes into consideration the hybrid system submodels, the Total Energy Deficit (TED), the Total Net Present C...
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... this study, Fig. 1 shows the configuration considered in this paper. This configuration consists of PV subsystem, wind power subsystem, battery bank storage, charge controller, converter, diesel generator and an inverter which is used to interface the DC voltage to the consumer load AC requirements. The operation mode of the studied system is as follows: ...
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... the rate of 0% of TED are achieved from the simulation results. After the technical criteria, the Total Net Present Cost (TNPC) and Energy Cost (EC) are used as an excellent indicators measuring economical profitability. The simulation results are established and the relationships between TNPC, EC and system configurations are scrutinized. In Figs. 9 and 10, curves given by solid symbols (cost curves) represent the Total Fig. 4. Hourly load ...
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... the selected configurations. Visibly, one point with the minimum value of TNPC and EC occurs in each curve which reveals the best configuration for zero load rejection. This configuration is considered as the optimal one which insures the system reliability requirement with the lowest value of TNPC and EC. In addition, a careful observation into Figs. 9 and 10 shows that the lowest TNPC and EC are found when the wind turbine capacity and the PV modules number are both moderate. ...
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... relationship between the amount of CO 2 emitted by the DG, Energy Cost (EC) and system configurations for zero failure rate has been presented in Fig. 11. It can be seen from this figure that the lowest values of energy cost and the amount of CO 2 emitted correspond to the configuration with the lowest number of wind turbines (01 wind turbine, Fig. 11(a)) and the largest number of photovoltaic modules (53 PV modules, Fig. 11(b)). This is mainly due to strong solar potential in the ...
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... relationship between the amount of CO 2 emitted by the DG, Energy Cost (EC) and system configurations for zero failure rate has been presented in Fig. 11. It can be seen from this figure that the lowest values of energy cost and the amount of CO 2 emitted correspond to the configuration with the lowest number of wind turbines (01 wind turbine, Fig. 11(a)) and the largest number of photovoltaic modules (53 PV modules, Fig. 11(b)). This is mainly due to strong solar potential in the Ghardaı¨aGhardaı¨a region. This potential promotes good energy production leading to the reduction on the one hand, the energy cost produced and secondly the amount of CO 2 emitted (a high penetration of ...
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... and system configurations for zero failure rate has been presented in Fig. 11. It can be seen from this figure that the lowest values of energy cost and the amount of CO 2 emitted correspond to the configuration with the lowest number of wind turbines (01 wind turbine, Fig. 11(a)) and the largest number of photovoltaic modules (53 PV modules, Fig. 11(b)). This is mainly due to strong solar potential in the Ghardaı¨aGhardaı¨a region. This potential promotes good energy production leading to the reduction on the one hand, the energy cost produced and secondly the amount of CO 2 emitted (a high penetration of renewable energy (solar and wind) in the energy mix decreases the operating ...
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Citations
... There are many optimization studies for sizing renewable energy systems based on the economic and environmental effects. Kaabeche and Ibtiouen [12] used an iterative technique to optimize an To decrease the equipment cost of the PV and battery integrated system and increase its environmental benefits, the proper size of the PV and the capacity of storage batteries should be customized based on the real-time electricity load of buildings. The experience methods directly use the average daily electricity load to estimate the size of storage batteries and solar PV [11], which can cause a waste of resources. ...
... There are many optimization studies for sizing renewable energy systems based on the economic and environmental effects. Kaabeche and Ibtiouen [12] used an iterative technique to optimize an integrated solar PV, wind turbines, diesel generator, and battery system with a given capacity for the battery and varying numbers of PV panels and wind turbines. Ssheb-Koussa et al. [13] optimized the size of a hybrid renewable energy system for four various sites in Algeria using MATLAB/Simulink (version 7.14) using a deterministic approach. ...
With the deteriorating environment and excessive consumption of primary energy, solar energy has become used in buildings worldwide for renewable energy. Due to the fluctuations of solar radiation, a solar photovoltaic (PV) power system is often combined with a storage battery to improve the stability of a building’s energy supply. In addition, the real-time energy consumption pattern of the residual houses fluctuates; a larger size for a PV and battery integrated system can offer more solar energy but also bring a higher equipment cost, and a smaller size for the integrated system may achieve an energy-saving effect. The traditional methods to size a PV and battery integrated system for a detached house are based on the experience method or the traversal algorithm. However, the experience method cannot consider the real-time fluctuating energy demand of a detached house, and the traversal algorithm costs too much computation time. Therefore, this study applies Nondominated Sorting Genetic Algorithm-II (NSGA-II) to size a PV and battery integrated system by optimizing total electricity cost and usage of the grid electricity simultaneously. By setting these two indicators as objectives separately, single-objective genetic algorithms (GAs) are also deployed to find the optimal size specifications of the PV and battery integrated system. The optimal solutions from NSGA-II and single-objective GAs are mutually verified, showing the high accuracy of NSGA-II, and the rapid convergence process demonstrates the time-saving effect of all these deployed genetic algorithms. The robustness of the deployed NSGA-II to various grid electricity prices is also tested, and similar optimal solutions are obtained. Compared with the experience method, the final optimal solution from NSGA-II saves 68.3% of total electricity cost with slightly more grid electricity used. Compared with the traversal algorithm, NSGA-II saves 94% of the computation time and provides more accurate size specifications for the PV and battery integrated system. This study suggests that NSGA-II is suitable for sizing a PV and battery integrated system for a detached house.
... In the literature, the hybrid system's techno-economic analysis has been studied in several research papers to improve the capacity sizes of the different parts of the hybrid system and to find the ideal model in terms of total net present and cost COE [15]- [18]. To provide effective and sustainable solutions to preserve fossil energy resources and protect the environment, Algeria plans to launch an ambitious program to develop renewable energies [19]. ...
Exploiting natural sun and wind resources in remote and isolated areas is undoubtedly an excellent decision to generate electrical energy due to their availability and cleanliness. Various systems were used to generate this energy, such as photovoltaics (PV), wind turbine sand other energy systems. Moreover, for optimum energy use, some of these systems are combined either with each other or with other conventional systems, such as diesel generators with PV systems (i.e., hybrid systems). This work aims to present a technical-economic study of PV/diesel autonomous hybrid systems to supply electrical power for an isolated house located in a hot desert climate, Adrar. For optimizing the hybrid systems, hourly input data of solar radiation and load were used according to two configurations, where the annual load is 11.2 kWh/day. The findings showed that the diesel system had a high cost, with a cost for energy of $0.407/kWh and a fuel price of $0.140/l. Among the hybrid power systems but with significant pollution, the proposed hybrid system 2 kw photovoltaic and diesel generator with 2.3 kW has important economic feasibility, where the energy cost amounted to $0.172/kWh. In addition, CO2 emissions are reduced by approximately 5 tons every year compared to an independent diesel generator system.
... The battery's energy storage capacity is known as its state of charge (SoC) and its energy consumption is known as its depth of discharge (DoD) [42,43,45,46]. Additionally, the minimum depth of discharge and the value of DOD, which is set at 80%, may be computed using Equation (6) [47]. SoC min ≤ SoC batt ≤ SoC max represents the SoC's border. ...
... The authors would like to thank Universiti Teknologi Malaysia (UTM) for the library facility and scholarship awarded through UTMPGIS by the vote of UTM.J.08.02.01/13.14/1/1 JId.2 (47). ...
Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid (E SOLD). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × 10 −2 USD/kWh, the GCF is equal to 7.34 × 10 −5 kWh, and the E SOLD is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development.
... While evaluating the relevant literature, it was observed that there exists several research on the potential of mini-grids in different electricity system configurations (Kaabeche and Ibtiouen 2014, Maleki and Askarzadeh 2014, Baneshi and Hadianfard 2016, Moner-Girona et al 2016, Ramli et al 2016, Das et al 2017, Shahzad et al 2017, Ahmad et al 2018, Chang et al 2021, González-García et al 2022, Guillou and Girard 2023. Detailed reviews of hybrid renewable energy system considering mini-grids are presented in Bhattacharyya(2018), Come Zebra et al (2021). ...
As developing countries like Nigeria strive to reduce carbon emissions while expanding energy access, mini-grids' role has gained recognition. However, limited analysis exists regarding the role of interconnected mini-grids (IMGs) in the transition to net-zero emissions electricity generation systems. Here, we employ a bottom-up energy system optimization modeling framework to explore various net-zero emissions electricity system scenarios and generate insights on the techno-economic implications of deploying IMGs in net-zero electricity systems, using Nigeria as a case study. We find that IMGs can contribute to modest cost reductions in net-zero emissions electricity systems. The analysis reveals that IMGs can help minimize stranded electricity generation assets and decrease the reliance on negative emissions technologies in scenarios aiming for net-zero emissions electricity systems by 2050. In scenarios where the net-zero target is delayed until 2070, the widespread deployment of comparatively affordable cleaner generators and the phaseout of fossil fuel power plants may render negative emission technologies unnecessary. The model results further indicate that IMGs can help reduce the use of captive diesel/gasoline gen-sets quickly, and nuclear power has a role in the electricity generation mix in all net-zero emissions scenarios. Moreover, in order to achieve the median per capita electricity consumption observed in high-income countries by the year 2050, Nigeria must undertake a formidable expansion of its current electricity generation capacity at a rate approximately six times greater than that dictated by a business-as-usual trajectory. The study also provides recommendations to address the policy, regulatory, and financial considerations crucial for implementing IMGs successfully
... This table provides a summary of the IC, OM, RC, PSV, and useful life of HRES components. The cost of the components was estimated taking into account current market prices [41,42]. ...
... In addition, the power deficit remains within a certain range. Photovoltaic-wind systems with battery storage and diesel generator backup sources have been investigated in [37] aiming to eliminate the load energy deficit and reduce the initial cost of the system as well as energy expenditures. ...
... Therefore, these concepts are used to develop the system reliability model, which also serves as the basis for the operating principles of the system. Thus, the system's reliability model should include the outage of the equipment [37,38]. The equipment failure repair rate is expressed as the number of repairs per year. ...
... As part of the reliability evaluation process, the forced outage rate (FOR) of the energy-producing units (e.g., panels) is assumed. It is determined that the operation probability of the system will be affected by photovoltaic loss due to outages of photovoltaic sources as described in [37,38]: ...
Due to the importance of the allocation of energy microgrids in the power distribution networks, the effect of the uncertainties of their power generation sources and the inherent uncertainty of the network load on the problem of their optimization and the effect on the network performance should be evaluated. The optimal design and allocation of a hybrid microgrid system consisting of photovoltaic resources, battery storage, and a backup diesel generator are discussed in this paper. The objective of the problem is minimizing the costs of power losses, energy resources generation, diesel generation as backup resource, battery energy storage as well as load shedding with optimal determination of the components energy microgrid system include its installation location in the 33-bus distribution network and size of the PVs, batteries, and Diesel generators. Additionally, the effect of uncertainties in photovoltaic radiation and network demand are evaluated on the energy microgrid design and allocation. A Monte Carlo simulation is used to explore the full range of possibilities and determine the optimal decision based on the variability of the inputs. For an accurate assessment of the system’s reliability, a forced outage rate (FOR) analysis is performed to calculate potential photovoltaic losses that could affect the operational probability of the system. The cloud leopard optimization (CLO) algorithm is proposed to optimize this optimization problem. The effectiveness of the proposed algorithm in terms of accuracy and convergence speed is verified compared to other state-of-the-art optimization methods. To further improve the performance of the proposed algorithm, the reliability and uncertainties of photovoltaic resource production and load demand are investigated.
... Uncertainty of load demand and renewable resource has been neglected. In [13], techno-economic optimization of a HES composed of PV, wind, diesel, and BSS has been investigated in a stand-alone power system. In this study, total energy deficit, total net present cost, and energy cost have been considered. ...
... In these conditions, BSS's state of charge (SOC) should be updated. Although there are various models to show the behaviour of ESS [13,18,19], the model used in this study is one of the popular models which is usually employed in HESs. Based on this model, when P p v (t ) is more than load demand (P L (t )), there is surplus energy and SOC is updated as follows [13]: ...
... Although there are various models to show the behaviour of ESS [13,18,19], the model used in this study is one of the popular models which is usually employed in HESs. Based on this model, when P p v (t ) is more than load demand (P L (t )), there is surplus energy and SOC is updated as follows [13]: ...
This paper focuses on risk‐averse‐based optimal operation of a grid‐connected hybrid energy system (HES) composed of photovoltaic (PV), diesel generator, and battery storage system (BSS). For this goal, information gap decision theory (IGDT) is used to model load demand uncertainty. The aim of the optimal operation is to minimize cost of PV/diesel/BSS by optimal determination of the power purchased from the electricity grid. Since in the risk‐averse strategy, load demand has an undesirable impact on the objective function, the decision maker attempts to maximize the uncertainty radius in a way that any deviation of the uncertain parameter leads to an objective function value which is not worse than the critical value. Over the case studies (considering different radiations), simulation results indicate that in the risk‐neutral strategy, at high, medium, and low radiations, the operation cost is 28.88, 36.10, and 42.63$, respectively. In the risk‐averse strategy, when the radiation is high, by increase of the deviation factor from 0.1 to 0.25, the optimal uncertainty radius increases from 6.98% to 15.72% (increase of around 125%) and the operation cost increases from 31.768 to 36.101$. When the radiation is low, by increase of the deviation factor from 0.1 to 0.25, the uncertainty radius increases from 8.64% to 16.9% (increase of around 96%) and the operation cost increases from 46.895 to 53.291$.
... 16 The simultaneous attention to the increase in the price of fossil fuels and action to reduce greenhouse gas emissions is also a factor in increasing the demand for replacing biofuel instead of diesel fuel in electricity generation systems in susceptible regions with proper access to biofuel generation sources. [17][18][19] This increase in demand in providing electricity to remote rural regions with proper access to renewable energy sources is also observed by hybrid power generation systems separate from the power grid 1 ; In such a way that most of the rural communities in developing countries are not connected to the electricity grid and the generation of combined energy from existing renewable sources is considered as a suitable economic and environmentally friendly option for electricity in these regions. 20 Abed et al. ...
Today, using systems based on renewable resources is a suitable alternative to fossil fuels. However, due to problems such as the lack of access in all the times needed to supply cargo and high‐investment cost, it has not been well‐received. In this research, in addition to maintaining the technical specifications and increasing the reliability of the system due to the addition of the hydroelectric power plant to other wind and solar systems, it has been tried to use biodiesel fuel (biofuel) as an alternative to fossil fuel in the diesel generator. To identify the most economical combination of the system with the application of social costs and the limit of pollutant and greenhouse gas emission in independent mode with the help of Homer software. the results showed that adding biodiesel to the designed system, the investment costs will increase by $282,038, which has a direct impact on the cost of energy and causes an increase of 0.0115 $/kWh. While the use of biodiesel reduces the emission of carbon dioxide by 28,947 kg/year.
... deficits (LPS(t)) to the daily power requirement P load−dm (t) as follows [24]: ...
The present paper introduced a collaboration of techno-economic optimization of a PV-Battery system based on a hybrid iterative evolutionary algorithm. The major aim was to conceive the most effective design of the PV-battery system components based on an on-line Power Management Strategy (PMS) and considering the desired required energy reliability LPSPd\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left({LPSP}_{d}\right)$$\end{document} with the lowest installation cost. The PMS control algorithm enables the proposed management control to highlight the optimal sizing methodology. In fact, the data base collected from the PMS strategy affects the convergence of the proposed sizing optimization design by considering them, for each day of the month, as a new physical constraint to the next economic optimization process. Indeed, the deployed optimization approach is considered as dynamic taking into account at each step, the previous states of optimization and management algorithms. To this end, an original modeling tool dedicated to techno-economic co-optimization approach was investigated and implemented to characterize the PV/Battery system performance. To highlight the effectiveness of the proposed economic optimization approach, a comparative study between Particle Swarm Optimization (PSO) algorithm and the Accelerated Particle Swarm Optimization (APSO) algorithm was performed. The obtained simulation results showed the robustness of the APSO algorithm in terms of speed of convergence and optimum system configuration.
