Size optimization of a PV/wind hybrid energy conversion system with battery storage using response surface methodology

This paper aims to show the use of the response surface methodology (RSM) in size optimization of an autonomous PV/wind integrated hybrid energy system with battery storage. RSM is a collection of statistical and mathematical methods which relies on optimization of response surface with design parameters. In this study, the response surface, output performance measure, is the hybrid system cost, and the design parameters are the PV size, wind turbine rotor swept area and the battery capacity. The case study is realized in ARENA 10.0, a commercial simulation software, for satisfaction of electricity consumption of the global system for mobile communications (GSM) base station at Izmir Institute of Technology Campus Area, Urla, Turkey. As a result, the optimum PV area, wind turbine rotor swept area, and battery capacity are obtained to be 3.95 m², 29.4 m², 31.92 kWh, respectively. These results led to $37,033.9 hybrid energy system cost, including auxiliary energy cost. The optimum result obtained by RSM is confirmed using loss of load probability (LLP) and autonomy analysis.     

Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing

In this paper, we perform Simulated Annealing (SA) algorithm for optimizing size of a PV/wind integrated hybrid energy system with battery storage. The proposed methodology is a heuristic approach which uses a stochastic gradient search for the global optimization. In the study, the objective function is the minimization of the hybrid energy system total cost. And the decision variables are PV size, wind turbine rotor swept area and the battery capacity. The optimum result obtained by SA algorithm is compared with our former study’s result. Consequently, it is come up with that the SA algorithm gives better result than the Response Surface Methodology (RSM). The case study is realized for a campus area in Turkey.     

风光互补发电系统的优化设计(I) CAD设计方法

给出了一整套利用CAD进行风光互补发电系统优化设计的方法。为了精确确定系统每小时的运行状态,采用了更精确地表征组件特性及评估实际获得的风光资源的数学模型。为了寻找出以最小设备投资成本满足用户用电要求的系统配置,首先在风力发电机容量固定不变的前提下,计算了与该容量风力发电机匹配的不同容量的PV方阵和蓄电池所组成的风/光/蓄组合的全年功率供给亏欠率LPSP,根据总的设备投资成本最小化的原则筛选出一组与该容量风力发电机对应的满足用户给定系统供电可靠性即LPSP值的风/光/蓄组合;然后通过改变风力发电机的容量,优选出多个与不同容量风力发电机对应的既能满足用户用电要求同时总的设备购置成本又是最低的风/光/蓄组合,比较它们的成本最终唯一确定出以最小投资成本满足用户用电要求的优化的系统配置。     

Assessment of economic viability for PV/wind/diesel hybrid energy system in southern Peninsular Malaysia

This paper analyzed the potential implementation of hybrid photovoltaic (PV)/wind turbine/diesel system in southern city of Malaysia, Johor Bahru. HOMER (hybrid optimization model for electric renewable) simulation software was used to determine the technical feasibility of the system and to perform the economical analysis of the system. There were seven different system configurations, namely stand-alone diesel system, hybrid PV–diesel system with and without battery storage element, hybrid wind–diesel system with and without battery storageelement, PV–wind–diesel system with and without storage element, will be studied and analyzed. The simulations will be focused on the net present costs, cost of energy, excess electricity produced and the reduction of CO₂ emission for the given hybrid configurations. At the end of this paper, PV–diesel system with battery storage element, PV–wind–diesel system with battery storage element and the stand-alone diesel system were analyzed based on high price of diesel.     

The importance of detailed data utilization on the performance evaluation of a grid-independent hybrid renewable energy system

In this study, a multi-source hybrid power system consisting of wind turbine (WT), photovoltaic (PV) solar unit, proton exchange membrane (PEM) FC and battery is proposed. The WT and PV generation systems are considered as the main power sources for utilizing the available renewable energy. The FC system is proposed as the back-up generation combined with electrolyzer unit and battery picks up the fast load transients and ripples. In such a hybrid system, energy management plays an important role for the overall system performance and durability. From this perspective, a fuzzy logic based intelligent controller is considered in this study. Besides, a detailed minute-scale meteorological and load demand data is utilized in the simulation process and the importance of utilization of such detailed data is presented. This detailed analysis may be valuable for evaluating the feasibility of grid-independent hybrid renewable energy units for upcoming power systems.     

Optimal design and techno-economic analysis of a hybrid solar–wind power generation system

Solar energy and wind energy are the two most viable renewable energy resources in the world. Good compensation characters are usually found between solar energy and wind energy. This paper recommend an optimal design model for designing hybrid solar–wind systems employing battery banks for calculating the system optimum configurations and ensuring that the annualized cost of the systems is minimized while satisfying the custom required loss of power supply probability (LPSP). The five decision variables included in the optimization process are the PV module number, PV module slope angle, wind turbine number, wind turbine installation height and battery capacity. The proposed method has been applied to design a hybrid system to supply power for a telecommunication relay station along south-east coast of China. The research and project monitoring results of the hybrid project were reported, good complementary characteristics between the solar and wind energy were found, and the hybrid system turned out to be able to perform very well as expected throughout the year with the battery over-discharge situations seldom occurred.     

Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage

This paper presents a novel strategy, optimized by genetic algorithms, to control stand-alone hybrid renewable electrical systems with hydrogen storage. The strategy optimizes the control of the hybrid system minimizing the total cost throughout its lifetime. The optimized hybrid system can be composed of renewable sources (wind, PV and hydro), batteries, fuel cell, AC generator and electrolyzer. If the renewable sources produce more energy than the one required by the loads, the spare energy can be used either to charge the batteries or to produce H₂ in the electrolyzer. The control strategy optimizes how the spare energy is used. If the amount of energy demanded by the loads is higher than the one produced by the renewable sources, the control strategy determines the most economical way to meet the energy deficit. The optimization of the various system control parameters is done using genetic algorithms. This paper explains the strategy developed and shows its application to a PV–diesel–battery–hydrogen system.     

Modeling,design, and optimization of a cost‐effective and reliable hybrid renewable energy system integrated with desalination using the division algorithm

People in the Middle East are facing the problem of freshwater shortages. This problem is more intense for a remote region, which has no access to the power grid. The use of seawater desalination technology integrated with the generated energy unit by renewable energy sources could help overcome this problem. In this study, we refer a seawater reverse osmosis desalination (SWROD) plant with a capacity of 1.5 m³/h used on Larak Island, Iran. Moreover, for producing fresh water and meet the load demand of the SWROD plant, three different stand‐alone hybrid renewable energy systems (SAHRES), namely wind turbine (WT)/photovoltaic (PV)/battery bank storage (BBS), PV/BBS, and WT/BBS are modeled and investigated. The optimization problem was coded in MATLAB software. Furthermore, the optimized results were obtained by the division algorithm (DA). The DA has been developed to solve the sizing problem of three SAHRES configurations by considering the object function's constraints. These results show that this improved algorithm has been simpler, more precise, faster, and more flexible than a genetic algorithm (GA) in solving problems. Moreover, the minimum total life cycle cost (TLCC = 243 763$), with minimum loss of power supply probability (LPSP = 0%) and maximum reliability, was related to the WT/PV/BBS configuration. WT/PV/BBS is also the best configuration to use less battery as a backup unit (69 units). The batteries in this configuration have a longer life cycle (maximum average of annual battery charge level) than two other configurations (93.86%). Moreover, the optimized results have shown that utilizing the configuration of WT/PV/BBS could lead to attaining a cost‐effective and green (without environmental pollution) SAHRES, with high reliability for remote areas, with appropriate potential of wind and solar irradiance.     

Optimization of hybrid solar energy sources/wind turbine systems integrated to utility grids as microgrid (MG) under pool/bilateral/hybrid electricity market using PSO

This study presents an optimized design of microgrid (MG) in distribution systems with multiple distributed generation (DG) units under different market policies such as pool/hybrid electricity market.Proposed microgrid includes various energy sources such as photovoltaic array and wind turbine with energy storage devices such as battery bank.In this study, microgrid is considered as independent power producer company (IPP) in power system. Price of selling/buying power in on-peak or off-peak for MG, DG and upstream power system (DISCO) under pool/bilateral/hybrid electricity market are different. In this study, particle swarm optimization (PSO) algorithm has been implemented for the optimization of the microgrid cost. The costs include capital cost, replacement cost, operation and maintenance costs and production cost for microgrid and DGs. Then, an objective function to maximize total net present worth (NPW) is presented. PSO approach is employed to obtain the minimum cost of microgrid, during interconnected operation by optimizing the production of local DGs and power exchanges with the main distribution grid. The optimization algorithm is applied to a typical LV network operating under different market policies.     

Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system

As non-polluting reliable energy sources, stand-alone photovoltaic/wind/fuel cell (PV/wind/FC) hybrid systems are being studied from various aspects in recent years. In such systems, optimum sizing is the main issue for having a cost-effective system. This paper evaluates the performance of different artificial intelligence (AI) techniques for optimum sizing of a PV/wind/FC hybrid system to continuously satisfy the load demand with the minimal total annual cost. For this aim, the sizing problem is formulated and four well-known heuristic algorithms, namely, particle swarm optimization (PSO), tabu search (TS), simulated annealing (SA), and harmony search (HS), are applied to the system and the results are compared in terms of the total annual cost. It can be seen that not only average results produced by PSO are more promising than those of the other algorithms but also PSO has the most robustness. As another investigation, the sizing is also performed for a PV/wind/battery hybrid system and the results are compared with those of the PV/wind/FC system.     

Performance analysis of various hybrid renewable energy systems using battery,hydrogen, and pumped hydro‐based storage units

The aim of this research is to analyze the techno‐economic performance of hybrid renewable energy system (HRES) using batteries, pumped hydro‐based, and hydrogen‐based storage units at Sharurah, Saudi Arabia. The simulations and optimization process are carried out for nine HRES scenarios to determine the optimum sizes of components for each scenario. The optimal sizing of components for each HRES scenario is determined based on the net present cost (NPC) optimization criterion. All of the nine optimized HRES scenarios are then evaluated based on NPC, levelized cost of energy, payback period, CO₂ emissions, excess electricity, and renewable energy fraction. The simulation results show that the photovoltaic (PV)‐diesel‐battery scenario is economically the most viable system with the NPC of US$2.70 million and levelized cost of energy of US$0.178/kWh. Conversely, PV‐diesel‐fuel cell system is proved to be economically the least feasible system. Moreover, the wind‐diesel‐fuel cell is the most economical scenario in the hydrogen‐based storage category. PV‐wind‐diesel‐pumped hydro scenario has the highest renewable energy fraction of 89.8%. PV‐wind‐diesel‐pumped hydro scenario is the most environment‐friendly system, with an 89% reduction in CO₂ emissions compared with the base‐case diesel only scenario. Overall, the systems with battery and pumped hydro storage options have shown better techno‐economic performance compared with the systems with hydrogen‐based storage.     

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.     

Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm

System power reliability under varying weather conditions and the corresponding system cost are the two main concerns for designing hybrid solar–wind power generation systems. This paper recommends an optimal sizing method to optimize the configurations of a hybrid solar–wind system employing battery banks. Based on a genetic algorithm (GA), which has the ability to attain the global optimum with relative computational simplicity, one optimal sizing method was developed to calculate the optimum system configuration that can achieve the customers required loss of power supply probability (LPSP) with a minimum annualized cost of system (ACS). The decision variables included in the optimization process are the PV module number, wind turbine number, battery number, PV module slope angle and wind turbine installation height. The proposed method has been applied to the analysis of a hybrid system which supplies power for a telecommunication relay station, and good optimization performance has been found. Furthermore, the relationships between system power reliability and system configurations were also given.     

Sizing of hybrid photovoltaic-wind energy systems

A procedure is described which determines the sizes of the PV array and wind turbine in a PV/wind energy hybrid system. Using the measured values of solar and wind energy at a given location, the method employs a simple graphical construction to determine the optimum configuration of the two generators that satisfies the energy demand of the user throughout the year.     

Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration

The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.     

An overview of the environmental,economic, and material developments of the solar and wind sources coupled with the energy storage systems

There is a constant growth in energy consumption and consequently energy generation around the world. During the recent decades, renewable energy sources took heed of scientists and policy makers as a remedy for substituting traditional sources. Wind and photovoltaic (PV) are the least reliable sources because of their dependence on wind speed and irradiance and therefore their intermittent nature. Energy storage systems are usually coupled with these sources to increase the reliability of the hybrid system. Environmental effects are one of the biggest concerns associated with the renewable energy sources. This study summarizes the last and most important environmental and economic analysis of a grid‐connected hybrid network consisting of wind turbine, PV panels, and energy storage systems. Focusing on environmental aspects, this paper reviews land efficiency, shaded analysis of wind turbines and PV panels, greenhouse gas emission, wastes of wind turbine and PV panels' components, fossil fuel consumption, wildlife, sensitive ecosystems, health benefits, and so on. A cost analysis of the energy generated by a hybrid system has been discussed. Furthermore, this study reviews the latest technologies for materials that have been used for solar PV manufacturing. This paper can help to make a right decision considering all aspects of installing a hybrid system. Copyright © 2017 John Wiley & Sons, Ltd.     

Techno‐economic optimization of hybrid power system using genetic algorithm

This paper presents an optimum sizing methodology to optimize the hybrid energy system (HES) configuration based on genetic algorithm. The proposed optimization model has been applied to evaluate the techno‐economic prospective of the HES to meet the load demand of a remote village in the northern part of Saudi Arabia. The optimum configuration is not achieved only by selecting the combination with the lowest cost but also by finding a suitable renewable energy fraction that satisfies load demand requirements with zero rejected loads. Moreover, the economic, technical and environmental characteristics of nine different HES configurations were investigated and weighed against their performance. The simulation results indicated that the optimum wind turbine (WT) selection is not affected only by the WT speed parameters or by the WT rated power but also by the desired renewable energy fraction. It was found that the rated speed of the WT has a significant effect on optimum WT selection, whereas the WT rated power has no consistent effect on optimal WT selection. Moreover, the results clearly indicated that the HES consisting of photovoltaics (PV), WT, battery bank (Batt) and diesel generator (DG) has superiority over all the nine systems studied here in terms of economical and environmental performance. The PV/Batt/DG hybrid system is only feasible when wind resource is very limited and solar energy density is high. On the other hand, the WT/Batt/DG hybrid system is only feasible at high wind speed and low solar energy density. It was also found that the inclusion of batteries reduced the required DG and hence reduced fuel consumption and operating and maintenance cost. Copyright © 2014 John Wiley & Sons, Ltd.     

Long-term optimization based on PSO of a grid-connected renewable energy/battery/hydrogen hybrid system

This paper presents and evaluates three energy management systems (EMSs) based on Particle Swarm Optimization (PSO) for long-term operation optimization of a grid-connected hybrid system. It is composed of wind turbine (WT) and photovoltaic (PV) panels as primary energy sources, and hydrogen system (fuel cell –FC–, electrolyzer and hydrogen storage tank) and battery as energy storage system (ESS). The EMSs are responsible for making the hybrid system produce the demanded power, deciding on the energy dispatch among the ESS devices. The first PSO-based EMS tries to minimize the ESS utilization costs, the second one to maximize the ESS efficiency, and the third one to optimize the lifetime of the ESS devices. Long-term simulations of 25 years (expected lifetime of the hybrid system) are shown in order to demonstrate the right performance of the three EMSs and their differences. The simulations show that: 1) each EMS outperforms the others in the designed target; and 2) the third EMS is considered the best EMS, because it needs the least ESS devices, and presents the lowest total acquisition cost of hybrid system, whereas the rest of parameters are similar to the best values obtained by the other EMSs.     

Techno-economic valuation and optimization of integrated photovoltaic/wind energy conversion system

Decentralized electricity generation by renewable energy sources offer greater security of supply for consumers while respecting the environment. But the random nature of these sources requires us to develop sizing rules and use these systems to exploit them. This paper proposes an integrated PV/wind hybrid system optimization model, which utilizes the iterative optimization technique following the Deficiency of Power Supply Probability (DPSP), the Relative Excess Power Generated (REPG), the Total Net Present Cost (TNPC), the Total Annualized Cost (TAC) and Break-Even Distance Analysis (BEDA) for power reliability and system costs. The flow chart of the hybrid optimal sizing model is also illustrated. With this merged model, the optimal size of PV/wind hybrid energy conversion system using battery bank can be performed technically and economically according to the system reliability requirements. Additionally, a sensitivity analysis was carried out in order to appreciate the most important parameters influencing the economic performances of the hybrid system. A case study is conducted to analyze one hybrid project, which is designed to supply small residential household situated in the area of the Center for Renewable Energy Development (CDER) localized in Bouzaréah, Algeria (36°48′N, 3°1′E, 345 m).