Battery behavior prediction and battery working states analysis of a hybrid solar–wind power generation system

Lead–acid batteries used in hybrid solar–wind power generation systems operate under very specific conditions, and it is often very difficult to predict when the energy will be extracted from or supplied to the battery. Owing to the highly variable working conditions, no battery model has achieved a good compromise between the complexity and precision. This paper presents a simple mathematical approach to simulate the lead–acid battery behaviors in stand alone hybrid solar–wind power generation systems. Several factors that affect the battery behaviors have been taken into account, such as the current rate, the charging efficiency, the self-discharge rate, as well as the battery capacity. Good agreements were found between the predicted results and the field measured data of a hybrid solar–wind project. At last, calculated from 1-year field data with the simulation model, the time-series battery state-of-charge (SOC) has been statistically analyzed considering the monthly and hourly variations as well as the probability distributions. The results have shown the battery working states in the real hybrid solar–wind power generation system.     

Optimal sizing of photovoltaic pumping system with water tank storage using LPSP concept

This paper recommends an optimal sizing model, to optimize the capacity sizes of different components of photovoltaic water pumping system (PWPS) using water tank storage. The recommended model takes into account the submodels of the pumping system and uses two optimization criteria, the loss of power supply probability (LPSP) concept for the reliability and the life cycle cost (LCC) for the economic evaluation.With this presented model, the sizing optimization of photovoltaic pumping system can be achieved technically and economically according to the system reliability requirements. The methodology adopted proposes various procedures based on the water consumption profiles, total head, tank capacity and photovoltaic array peak power. A case study is conducted to analyze one photovoltaic pumping project, which is designed to supply drinking water in remote and scattered small villages situated in Ghardaia, Algeria (32°29′N, 3°40′E, 450 m).     

Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong

This paper describes a simulation model for analyzing the probability of power supply failure in hybrid photovoltaic–wind power generation systems incorporating a storage battery bank, and also analyzes the reliability of the systems. An analysis of the complementary characteristics of solar irradiance and wind power for Hong Kong is presented. The analysis of local weather data patterns shows that solar power and wind power can compensate well for one another, and can provide a good utilization factor for renewable energy applications. For the loss of power supply probability (LPSP) analysis, the calculation objective functions and restraints are set up for the design of hybrid systems and to assess their reliability. To demonstrate the use of the model and LPSP functions, a case study of hybrid solar–wind power supply for a telecommunication system is presented. For a hybrid system on the islands surrounding Hong Kong, a battery bank with an energy storage capacity of 3 days is suitable for ensuring the desired LPSP of 1%, and a LPSP of 0% can be achieved with a battery bank of 5 days storage capacity.     

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.     

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 sizing of stand-alone hybrid systems based on PV/WT/FC by using several methodologies

This paper presents a comparative study of four sizing methods for a stand-alone hybrid generation system integrating renewable energies (photovoltaic panels and wind turbine) and backup and storage system based on battery and hydrogen (fuel cell, electrolyzer and hydrogen storage tank). Two of them perform a technical sizing. In one case, the sizing is based on basic equations, and in the other case, an optimal technical sizing is achieved by using Simulink Design Optimization. The other two methods perform an optimal techno-economical sizing by using the hybrid system optimization software HOMER and HOGA, respectively. These methods have been applied to design a stand-alone hybrid system which supplies the load energy demand during a year. A MATLAB-Simulink model of the hybrid system has been used to simulate the performance of hybrid system designed by each method for the stand-alone application under study in this work. The results are reported and discussed in the paper.     

A novel optimization sizing model for hybrid solar-wind power generation system

This paper develops the Hybrid Solar-Wind System Optimization Sizing (HSWSO) model, to optimize the capacity sizes of different components of hybrid solar-wind power generation systems employing a battery bank. The HSWSO model consists of three parts: the model of the hybrid system, the model of Loss of Power Supply Probability (LPSP) and the model of the Levelised Cost of Energy (LCE). The flow chart of the HSWSO model is also illustrated. With the incorporated HSWSO model, the sizing optimization of hybrid solar-wind power generation systems can be achieved technically and economically according to the system reliability requirements. A case study is reported to show the importance of the HSWSO model for sizing the capacities of wind turbines, PV panel and battery banks of a hybrid solar-wind renewable energy system.     

The system performance of autonomous photovoltaic–wind hybrid energy systems using synthetically generated weather data

The yearly system performance of autonomous photovoltaic–wind hybrid energy systems with battery storage is the subject of this article. The yearly system performance is simulated using synthetically generated solar radiation and wind speed data and compared to that simulated using measured hour-by-hour data. Two different synthetic weather data sets are generated: 3-day month and 4-day month, in which 3 and 4 days represent a month, resulting in a total of 36 and 48 days for a year. The hourly varying solar radiation data are synthesised from the clearness index value for each month. The daily constant wind speed data are synthesised using the Weibull wind speed distribution model, on a monthly basis. Using two different synthetic weather data sets, the effect of number of synthetic days on the system performance estimation is studied. Different sequences of synthetic solar and wind days lead to 36 and 576 combinations for 3- and 4-day months, respectively. Three predetermined combinations for both the 3- and 4-day months are chosen and the system performance of an autonomous photovoltaic–wind hybrid energy system with battery storage is simulated using these predetermined combinations. It is shown that the yearly system performance predicted from the 3- and 4-day synthetic data closely agrees with that obtained from the measured data, varying only slightly for different combinations.     

A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system using energy filter algorithm

In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.     

PV–wind hybrid system performance: A new approach and a case study

Until now, there is no internationally accepted guideline for the measurement, data exchange and analysis of PV–Wind Hybrid Systems. As there is a need for such a tool, so as to overcome the barrier that the lack of confidence due to the absence of reliability means for the development of the market of Hybrid Systems, an effort has been made to suggest one tool for PV–Wind Hybrid Systems. The suggested guidelines presented in this work are based on the existing guidelines for PV Systems, as a PV–Wind Hybrid system can be roughly thought of as a PV System to which wind generation has been added. So, the guidelines for PV Systems are valid for the PV–Wind System, and only the part referred to wind generation should be included. This has been the process followed in this work. The proposed method is applied to a case study, the CICLOPS Project, a 5 kW PV, 7.5 kW Wind Hybrid system installed at the Isolated Wind Systems Test Site that CIEMAT owns in CEDER (Soria, Spain). This system has been fully monitored through a year and the results of the monitoring activity, characterizing the long-term performance of the system are shown in this work.     

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.     

Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

This paper examines optimal control strategies of variable air volume air conditioning system. The control strategies included a base control strategy of fixed temperature set point and two advanced strategies for insuring comfort and indoor air quality (IAQ). The first advanced control adjusts the fresh air supply rate and the supply air temperature to maintain the temperature set point in each zone while assuring indoor air quality. The second strategy controls the fresh air rate and the supply air temperature to maintain an acceptable thermal comfort and IAQ in each zone. The optimization problem for each control strategy is formulated based on the cost of energy consumption and constrained by system and thermal space transient models. The optimization problem is solved using genetic algorithm. The optimization scheme/model is applied to a case study for a building floor in Beirut weather. The thermal space and system component models were validated for the base strategy using Visual DOE 4.0 software [Architectural Energy Cooperation, San Francisco, USA; 2005 〈www.archenergy.com〉]. Energy savings up to 30.4% were achieved during the summer season of four months with the optimized advanced strategies when compared with the conventional base strategy while comfort and IAQ were satisfied.     

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.     

Using hydropower to complement wind energy: a hybrid system to provide firm power

This paper presents a theoretical study of how wind power can be complemented by hydropower. A conceptual framework is provided for a hybrid power station that produces constant power output without the intermittent fluctuations inherent when using wind power. Two hypothetical facilities are considered as case studies. One of them is a hydropower plant located on the “Presidente Benito Juarez” dam in Jalapa del Marques, Oaxaca, Mexico. The other hypothetical facility is a wind farm located near “La Venta”, an area in Juchitan, Oaxaca, Mexico. The wind–hydro-power system is a combined wind and hydro power plant in a region that is rich in both resources. The model shows that the hybrid plant could provide close to 20 MW of firm power to the electrical distribution system. On a techno-economic basis, we obtain the levelized production cost of the hybrid system. Taking into account two different discount rates of 7% and 10%, figures for levelized production cost are developed.     

Optimal sizing of autonomous hybrid energy system using supply‐demand‐based optimization algorithm

Hybrid energy systems (HESs) comprising photovoltaic (PV) arrays and wind turbines (WTs) are remarkable solutions for electrifying remote areas. These areas commonly fulfil their energy demands by means of a diesel genset (DGS). In the present study, a novel computational intelligence algorithm called supply‐demand‐based optimization (SDO) is applied to the HES sizing problem based on long‐term cost analysis. The effectiveness of SDO is investigated, and its performance is compared with that of the genetic algorithm (GA), particle swarm optimization (PSO), gray wolf optimizer (GWO), grasshopper optimization algorithm (GOA), flower pollination algorithm (FPA), and big‐bang‐big‐crunch (BBBC) algorithm. Three HES scenarios are implemented using measured solar radiation, wind speed, and load profile data to electrify an isolated village located in the northern region of Saudi Arabia. The optimal design is evaluated on the basis of technical (loss of power supply probability [LPSP]) and economic (annualized system cost [ASC]) criteria. The evaluation addresses two performance indicators: surplus energy and the renewable energy fraction (REF). The results reveal the validity and superiority of SDO in determining the optimal sizing of an HES with a higher convergence rate, lower ASC, lower LPSP, and higher REF than that of the GA, PSO, GWO, GOA, FPA, and BBBC algorithms. The performance analysis also reveals that an HES comprising PV arrays, WTs, battery banks, and DGS provides the best results: 238.7 kW from PV arrays, 231.6 kW from WTs, 192.5 kWh from battery banks, and 267.6 kW from the DGS. The optimal HES exhibits a high REF (66.4%) and is economically feasible ($104 323.10/year) and environmentally friendly. The entire load demand of the area under study is met without power loss (LPSP = 0%).     

Technical and economic assessment of hybrid photovoltaic/wind system with battery storage in Corsica island

The sizing and techno-economical optimization of a stand-alone hybrid photovoltaic/wind system (HPWS) with battery storage is presented in this paper. The main objective of the present study is to find the optimum size of system, able to fulfill the energy requirements of a given load distribution, for three sites located at Corsica island and to analyze the impact of different parameters on the system size. The methodology used provides a useful and simple approach for sizing and analyzing an HPWS. In the proposed stand-alone system, a new concept such as the supply of wind power via a uninterruptible power supply (UPS) is introduced and therefore the energy produced by the wind generator can be sent directly to the load.     

风电与燃气轮机互补系统发电成本敏感性分析

详细讨论了大型风电场与燃气轮机组成的互补发电系统发电成本的主要影响因子及其对系统的敏感性。通过对互补发电系统发电成本理论公式的研究,推导了互补系统中各项影响因子相对于发电成本的数学方程和影响尺度,得到了影响发电成本几个关键的影响因子。通过采用敏感性分析原理,对这些主要的影响因子在不同变化条件下对互补发电系统发电成本的影响进行了详细的分析与讨论,提出降低系统发电成本的可行性措施及其努力的方向,为在新疆地区实现这种互补发电系统提供经济分析上的基础。     

Optimization of capacity and operation for CCHP system by genetic algorithm

The technical, economical and environmental performances of combined cooling, heating and power (CCHP) system are closely dependent on its design and operation strategy. This paper analyzes the energy flow of CCHP system and deduces the primary energy consumption following the thermal demand of building. Three criteria, primary energy saving (PES), annual total cost saving (ATCS), and carbon dioxide emission reduction (CDER) are selected to evaluate the performance of CCHP system. Based on the energy flow of CCHP system, the capacity and operation of CCHP system are optimized by genetic algorithm (GA) so as to maximize the technical, economical and environmental benefits achieved by CCHP system in comparison to separation production system. A numerical example of gas CCHP system for a hotel building in Beijing is given to ascertain the effectiveness of the optimal method. Furthermore, a sensitivity analysis is presented in order to show how the optimal operation strategy would vary due to the changes of electricity price and gas price.     

Optimal positioning of wind turbines on Gökçeada using multi‐objective genetic algorithm

This paper addresses the problem of optimal placement of wind turbines in a farm on Gokçeada Island located at the north‐east of Aegean Sea bearing full potential of wind energy generation. A multi‐objective genetic algorithm approach is employed to obtain optimal placement of wind turbines by maximizing the power production capacity while constraining the budget of installed turbines. Considering the speed and direction history, wind with constant intensity from a single direction is used during optimization. This study is based on wake deficit model mainly because of its simplicity, accuracy and fast calculation time. The individuals of the Pareto optimal solution set are evaluated with respect to various criteria, and the best configurations are presented. In addition to best placement layouts, results include objective function values, total power output, cost and number of turbines for each configuration. Copyright © 2009 John Wiley & Sons, Ltd.     

Development of an aeroelastic code based on three‐dimensional viscous–inviscid method for wind turbine computations

Aerodynamic and structural dynamic performance analysis of modern wind turbines are routinely estimated in the wind energy field using computational tools known as aeroelastic codes. Most aeroelastic codes use the blade element momentum (BEM) technique to model the rotor aerodynamics and a modal, multi‐body or the finite‐element approach to model the turbine structural dynamics. The present work describes the development of a novel aeroelastic code that combines a three‐dimensional viscous–inviscid interactive method, method for interactive rotor aerodynamic simulations (MIRAS), with the structural dynamics model used in the aeroelastic code FLEX5. The new code, called MIRAS‐FLEX, is an improvement on standard aeroelastic codes because it uses a more advanced aerodynamic model than BEM. With the new aeroelastic code, more physical aerodynamic predictions than BEM can be obtained as BEM uses empirical relations, such as tip loss corrections, to determine the flow around a rotor. Although more costly than BEM, a small cluster is sufficient to run MIRAS‐FLEX in a fast and easy way. MIRAS‐FLEX is compared against the widely used FLEX5 and FAST, as well as the participant codes from the Offshore Code Comparison Collaboration Project. Simulation tests consist of steady wind inflow conditions with different combinations of yaw error, wind shear, tower shadow and turbine‐elastic modeling. Turbulent inflow created by using a Mann box is also considered. MIRAS‐FLEX results, such as blade tip deflections and root‐bending moments, are generally in good agreement with the other codes. Copyright © 2017 John Wiley & Sons, Ltd.