Optimal sizing study of hybrid wind/PV/diesel power generation unit

In this paper, a methodology of sizing optimization of a stand-alone hybrid wind/PV/diesel energy system is presented. This approach makes use of a deterministic algorithm to suggest, among a list of commercially available system devices, the optimal number and type of units ensuring that the total cost of the system is minimized while guaranteeing the availability of the energy. The collection of 6 months of data of wind speed, solar radiation and ambient temperature recorded for every hour of the day were used. The mathematical modeling of the main elements of the hybrid wind/PV/diesel system is exposed showing the more relevant sizing variables. A deterministic algorithm is used to minimize the total cost of the system while guaranteeing the satisfaction of the load demand. A comparison between the total cost of the hybrid wind/PV/diesel energy system with batteries and the hybrid wind/PV/diesel energy system without batteries is presented.The reached results demonstrate the practical utility of the used sizing methodology and show the influence of the battery storage on the total cost of the hybrid system.     

Unit sizing and cost analysis of stand-alone hybrid wind/PV/fuel cell power generation systems

An economic evaluation of a hybrid wind/photovoltaic/fuel cell (FC) generation system for a typical home in the Pacific Northwest is performed. In this configuration the combination of a FC stack, an electrolyser, and hydrogen storage tanks is used as the energy storage system. This system is compared to a traditional hybrid energy system with battery storage. A computer program has been developed to size system components in order to match the load of the site in the most cost effective way. A cost of electricity, an overall system cost, and a break-even distance analysis are also calculated for each configuration. The study was performed using a graphical user interface programmed in MATLAB.     

Energy management hypothesis for hybrid power system of H2/WT/PV/GMT via AI techniques

This paper aims to attain an efficient and optimized energy management operation of Hybrid Power System (HPS) by using Artificial Intelligent (AI) controllers. The HPS comprises Wind Turbines (WTs) and Photovoltaic (PV) panels such as primary Renewable Energy Sources (RESs) in addition to both Fuel Cells (FCs) and Gas Micro–Turbines (GMTs) which are used as Backup Sources (BKUSs).To avoid the undesired negative impacts on the HPS functionality because of the RESs intermittency, the Hydrogen Storage System (HSS) is integrated into the system. Two different energy management strategies based on Neural Networks (NN) and Fuzzy Logic Control (FLC) respectively are applied to the HPS for minimizing the energy production cost and keeping the buffer role of HSS. Using MATLAB^?, the proposed two AI introduced solutions are used for reaching adequate energy management operation performance for the overall HPS during 24 h load variation. From the numerical simulations, the superiority of the FLC over the NN control approach is discussed. The proposed HSS can positively act as a buffer solution to avoid drawbacks of RESs during unexpected load peaks and/or discontinuous energy production.     

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.     

Optimal hybrid PV/WT/FC sizing and distribution system reconfiguration using multi-objective artificial bee colony (MOABC) algorithm

In this paper, a novel multi-objective artificial bee colony algorithm is presented to solve the distribution system reconfiguration and hybrid (photo voltaic/wind turbine/fuel cell) energy system sizing. The purposes of the multi-objective optimization problem include the total power loss, the total electrical energy cost, and the total emission produced by hybrid energy system and the grid minimization, and the voltage stability index (VSI) of distribution system maximization. In the proposed algorithm, an external archive of non-dominated solutions is kept which is updated in each iteration. In addition, for preserving the diversity in the archive of Pareto solutions, the crowding distance operator is used. This algorithm is tested on 33 bus distribution systems and obtained non-dominated solutions are compared with the well-known NSGA-II and MOPSO methods. The solutions obtained by the MOABC algorithm have a good quality and a better diversity of the Pareto front compared with those of NSGA-II and MOPSO methods.     

Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems

In this paper we address the optimal sizing and scheduling of isolated hybrid systems using an optimization framework. The hybrid system features wind and photovoltaic conversion systems, batteries and diesel backup generators to supply electricity demand. A Mixed-Integer Linear Programming formulation is used to model system behavior over a time horizon of one year, considering hourly changes in both the availability of renewable resources and energy demand. The optimal solution is achieved with respect to the minimization of the levelized cost of energy (LCOE) over a lifetime of 20 years. Results for a case study show that the most economical solution features all four postulated subsystems.     

Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions

The optimal design of the renewable energy system can significantly improve the economical and technical performance of power supply. In this paper, the technical-economic optimization study of a stand-alone hybrid PV/wind system (HPWS) in Corsica Island is presented.

Therefore, the primary objective of this study is to estimate the appropriate dimensions of a stand-alone HPWS that guarantee the energy autonomy of a typical remote consumer with the lowest levelised cost of energy (LCE). A secondary aim is to compare the performance and the optimal sizing of two system configurations. Finally, to study the impact of the renewable energy potential quality on the system size, the optimum dimensions of system are defined for five sites in Corsica Island. In this context, a complete sizing model is developed, able to predict the optimum system configuration on the basis of LCE. Accordingly, an integrated energy balance analysis is carried out for the whole time period investigated.

The simulation results indicate that the hybrid system is the best option for all the sites considered in this study, yielding lower LCE. Thus, it provides higher system performance than PV or wind systems alone. The choice of the system configuration type affects the state of charge variation profile, especially at low wind potential sites, while the system size and the LCE are significantly influenced. It is shown that the LCE depends largely on the renewable energy potential quality. At high wind potential site, more than 40% of the total production energy is provided by the wind generator, while at low wind potential sites, less than 20% of total production energy is generated by the wind generator.     

Optimal energy management system for stand-alone wind turbine/photovoltaic/hydrogen/battery hybrid system with supervisory control based on fuzzy logic

This paper presents a novel hourly energy management system (EMS) for a stand-alone hybrid renewable energy system (HRES). The HRES is composed of a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and two energy storage systems (ESS), which are a hydrogen subsystem and a battery. The WT and PV panels are made to work at maximum power point, whereas the battery and the hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as support and storage system. The EMS uses a fuzzy logic control to satisfy the energy demanded by the load and maintain the state-of-charge (SOC) of the battery and the hydrogen tank level between certain target margins, while trying to optimize the utilization cost and lifetime of the ESS. Commercial available components and an expected life of the HRES of 25 years were considered in this study. Simulation results show that the proposed control meets the objectives established for the EMS of the HRES, and achieves a total cost saving of 13% over other simpler EMS based on control states presented in this paper.     

Optimal sizing for a wind-photovoltaic-hydrogen hybrid system considering levelized cost of storage and source-load interaction

Hydrogen energy storage system (HESS) has excellent potential in high-proportion renewable energy systems due to its high energy density and seasonal storage characteristics. After detailing the volatility of wind speed, irradiance and load, this paper proposes a bi-level optimization model to analyze the economic operation of the wind-photovoltaic-hydrogen hybrid system (WPH-HS). First, the relationship between the source-load output matching and operating conditions of HESS is studied, two evaluation indicators are described, which can be adjusted by wind-solar complementarity on the source side and demand response on the load side. Second, considering the levelized cost of storage (LCOS), the total annual cost (TAC) calculation method of WPH-HS is presented, and this paper provides a new hybrid optimization technology of chaotic search, particle swarm optimization and non-dominated sorting genetic algorithm2. Finally, the system is simulated with the MATLAB software to determine the optimal sizing of components and minimize the LCOS while ensuring the optimal TAC. The simulation results are elaborated in detail. In particular, the added source-load interaction reduces the TAC and LCOS by 7.3% and 10.3%. When two indicators reach 0.03 and 0.1745, the system is economically viable with the LCOS of 0.276 USD/kWh. The hybrid optimization algorithm can achieve better result in fewer iterations.     

Optimum sizing of wind-pumped-storage hybrid power stations in island systems

Pumped storage is generally viewed as the most promising technology to increase renewable energy source (RES) penetration levels in power systems and particularly in small autonomous island grids. Combined wind and pumped-storage “virtual power plants”, called hybrid power stations (HPS), constitute a realistic and feasible option to achieve high penetrations, provided that their components are properly sized. In this paper, the optimum sizing is investigated for a pumped storage HPS operating in an island system. The analysis addresses the sizing of the main HPS components (hydro turbines, pumps, wind farm, reservoirs), adopting either the investor’s perspective, where the objective is to maximize the return on the HPS investment, or a system perspective, where the optimization target is the maximization of RES penetration, along with maintaining the lowest possible generation cost in the system. Genetic Algorithms (GAs) are applied for the optimization and a real isolated island power system is used as a study case. The adopted operating policy and pricing principles, which critically affect the optimal sizing of an HPS project, are based on the existing regulatory framework for storage stations in Greek islands.     

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 a hybrid wind-diesel stand-alone system on the basis of minimum long-term electricity production cost

Hybrid wind-diesel systems are an interesting solution for the electrification of isolated consumers. The proposed system, including a properly sized battery, leads to a significant reduction of the fuel consumption, in comparison with a diesel-only installation, also protecting the diesel generator from excessive wear. On the other hand, a properly designed wind-diesel installation remarkably reduces the required battery capacity, in relation to a wind-only based stand-alone system, especially in medium-low wind potential areas. In this context, a complete sizing model, based on a long-term energy production cost analysis is developed, able to predict the optimum configuration of a hybrid wind-diesel stand-alone system on the basis of minimum long-term cost. According to the application results obtained for representative wind potential cases, the proposed hybrid system guarantees one year’s long energy autonomy of a typical remote consumer, presenting a significant cost advantage in relation either to a diesel-only or to a wind-based stand-alone system.     

不停电独立光伏系统的优化设计

为零缺电率负载供电的独立光伏系统是对设计要求最高的光伏系统,必须慎重地进行优化设计。研究表明,如果采用一般的独立光伏系统优化设计程序来进行设计,只要用蓄电池维持天数等于零代入,即可确定太阳电池方阵的容量,同时可以用当地辐照量最低的月份得到最大辐照量所对应的倾角作为方阵的最佳倾角。确定蓄电池容量时应以当地最长连阴雨天数作为蓄电池维持天数的依据。通过实例分析,取得了良好的效果。     

A novel forecasting method based on the economic and demand response for FC/WT/PV unit and a 3 in 1 TES energy storage

Due to the lack of distribution resources and increasing demand in the daily market, the use of renewable resources is increasing. But renewable sources and market prices are uncertain behavior and cause economic problems. This paper introduces a novel market participation model include wind turbine, photovoltaic, fuel cell integrated with a novel hybrid TES energy storage system (3 in 1 concept) to minimize cost and improve load demand reliability. Also, to solve he mentioned problem a novel forecasting method are proposed. This model is a new multi artificial neural network based on the complete ensemble empirical mode decomposition which is coupled with Tanh function and using RMSE, MAPE and NMAE method the error rate of the proposed method is calculated. By using this method, the forecasting accuracy is improved and also with a novel energy storage the economic issue and market reliability are improved. Also, using the stochastic model the uncertainty system's behavior are modeled to obtain an accurate results of market participation and increase demand supply. Finally, a testing system includes wind turbine/photovoltaic/fuel cell/storage system and demand response are used to prove the superiority of the proposed model in comparison to other models.     

A mobile renewable house using PV/wind/fuel cell hybrid power system

A photovoltaic/wind/fuel cell hybrid power system for stand-alone applications is proposed and demonstrated with a mobile house. This concept shows that different renewable sources can be used simultaneously to power off-grid applications. The presented mobile house can produce sufficient power to cover the peak load. Photovoltaic and wind energy are used as primary sources and a fuel cell as backup power for the system. The power budgeting of the system is designed based on the local data of solar radiation and wind availability. Further research will focus on the development of the data acquisition system and the implementation of automatic controls for power management.     

A methodology for optimal sizing of autonomous hybrid PV/wind system

The present paper presents a methodology to perform the optimal sizing of an autonomous hybrid PV/wind system. The methodology aims at finding the configuration, among a set of systems components, which meets the desired system reliability requirements, with the lowest value of levelized cost of energy.     

Economic analysis of PV/diesel hybrid system with flywheel energy storage

This paper analyzes a hybrid energy system performance with photovoltaic (PV) and diesel systems as the energy sources. The hybrid energy system is equipped with flywheel to store excess energy from the PV. HOMER software was employed to study the economic and environmental benefits of the system with flywheels energy storage for Makkah, Saudi Arabia. The analysis focused on the impact of utilizing flywheel on power generation, energy cost, and net present cost for certain configurations of hybrid system. Analyses on fuel consumption and carbon emission reductions for the system configurations were also presented in this paper.     

Rapid sizing of a hydrogen-battery storage for an offshore wind farm using convex programming

This paper carries out a comprehensive analysis on an offshore wind farm equipped with a hybrid storage comprised of hydrogen and battery, from the perspective of economic effectiveness. To rapidly evaluate the system economy, a computationally efficient convex program that takes the nonlinear storage efficiencies into account is provided, which can simultaneously and synergistically optimize the storage sizing and energy management over a long offshore wind cycle. In the analysis, a case study on the optimal configuration and operation of the hybrid storage is thoroughly investigated, answering what the scalings are and how the storage functions in the offshore wind farm. Comparisons to other offshore wind farms with none or only one storage type further demonstrate the advantage of combining hydrogen plant and battery. Influences of the offshore wind electricity price of grid parity and hydrogen price on the system economies, in the terms of total annual cost, net annual profit and hydrogen production cost, are also discussed, revealing sensitivity and dependency of the scalings. Finally, this paper presents the future potential of applying hydrogen plant in the offshore wind farm, from the angles of hydrogen production cost and energy saving.     

Global analysis of the techno-economic potential of renewable energy hybrid systems on small islands

Globally, small islands below 100,000 inhabitants represent a large number of diesel based mini-grids. With volatile fossil fuel costs which are most likely to increase in the long-run and competitive renewable energy technologies the introduction of such sustainable power generation system seems a viable and environmental friendly option. Nevertheless the implementation of renewable energies on small islands is quite low based on high transaction costs and missing knowledge according to the market potential.Our work provides a global overview on the small island landscape showing the respective population, economic activity, energy demand, and fuel costs for almost 1800 islands with approximately 20 million inhabitants currently supplied by 15 GW of diesel plants. Based on these parameters a detailed techno-economic assessment of the potential integration of solar PV, wind power, and battery storage into the power supply system was performed for each island. The focus on solar and wind was set due to the lack of data on hydro and geothermal potential for a global island study. It revealed that almost 7.5 GW of photovoltaic and 14 GW of wind power could be economically installed and operated on these islands reducing the GHG-emissions and fuel consumption by approximately 50%. In total numbers more than 20 million tons of GHG emissions can be reduced by avoiding the burning of 7.8 billion liters of diesel per year. Cost savings of around 9 USDct/kWh occur on average by implementing these capacities combined with 5.8 GWh of battery storage. This detailed techno-economic evaluation of renewable energies enables policy makers and investors to facilitate the implementation of clean energy supply systems on small islands. To accelerate the implementation of this enormous potential we give specific policy recommendations such as the introduction of proper regulations.     

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.