A new perspective in optimum sizing of hybrid renewable energy systems: Consideration of component performance degradation issue

The ever increasing demand for energy and the concerns on the environmental sustainability issue all around the world lead to more interest in alternative sources for energy production. However, as the current costs of the alternative sources such as solar, wind energy conversion systems etc. are relatively higher as compared to the conventional means of energy production, an optimum sizing approach is quite necessary in order to avoid over-sizing of such systems without lowering the reliability of load demand supply in all possible conditions including the variability of meteorological conditions or the changing power demand of load. There are many research papers available in the literature dealing with this optimum sizing issue. Even the mentioned papers significantly contribute to the wider penetration of such sources, none of them consider the power output degradation of alternative energy sources due to aging during their pre-defined operating life time. Besides, there are a few studies utilizing detailed dynamic models of energy sources apart from first-degree linear equations based models that may fall short in presenting the exact dynamics of the related system. Thus, an “observe and focus” algorithm based optimization of a hybrid alternative energy system considering the power output degradation and detailed models of each hybrid system component is performed in this study. Related details presented within the paper can provide a new perspective in optimum sizing of such hybrid systems and may further be considered in future updates of famous sizing software programs commercially or freely available in websites of several laboratories or universities.     

Dynamic modeling of hybrid energy storage systems coupled to photovoltaic generation in residential applications

A model of a photovoltaic (PV) powered residence in stand-alone configuration was developed and evaluated. The model assesses the sizing, capital costs, control strategies, and efficiencies of reversible fuel cells (RFC), batteries, and ultra-capacitors (UC) both individually, and in combination, as hybrid energy storage devices. The choice of control strategy for a hybrid energy storage system is found to have a significant impact on system efficiency, hydrogen production and component utilization. A hybrid energy storage system comprised of batteries and RFC has the advantage of reduced cost (compared to using a RFC as the sole energy storage device), high system efficiency and hydrogen energy production capacity. A control strategy that preferentially used the RFC before the battery in meeting load demand allows both grid independent operation and better RFC utilization compared to a system that preferentially used the battery before the RFC. Ultra-capacitors coupled with a RFC in a hybrid energy storage system contain insufficient energy density to meet dynamic power demands typical of residential applications.     

Optimum sizing of battery-integrated diesel generator for remote electrification through design-space approach

Battery integrated diesel generation is one of the options for decentralized power production. They are particularly suitable for loads with significant variation in the daily demand. A methodology for the optimum sizing of integrated system involving diesel generator and battery bank for an isolated electrical power generation is proposed in this paper. The proposed methodology is based on the design-space approach involving a time series simulation of the entire system. Based on the proposed approach, for a given load demand, characteristics of the diesel generator and battery bank, a sizing curve is identified on the diesel generator rating vs. storage capacity diagram. The sizing curve helps in identifying all possible feasible system configurations or the design space. Based on the minimum capital cost and the minimum operating cost of the system, the Pareto optimum curve is identified on the system-sizing curve. Optimum system configuration is identified based on the minimum cost of energy through optimal dispatch strategy. Two operating strategies, involving continuous and intermittent operation of the diesel generator are studied and compared. Effect of the load profile on the system sizing is also presented in this paper.     

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.     

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.     

Design and control strategies of PV-Diesel systems using genetic algorithms

Hybrid photovoltaic systems (PV-hybrid) use photovoltaic energy combined with other sources of energy, like wind or Diesel. If these hybrid systems are optimally designed, they can be more cost effective and reliable than PV-only systems. However, the design of hybrid systems is complex because of the uncertain renewable energy supplies, load demands and the non-linear characteristics of some components, so the design problem cannot be solved easily by classical optimisation methods. When these methods are not capable of solving the problem satisfactorily, the use of heuristic techniques, such as the Genetic Algorithms, can give better results.The authors have developed the HOGA program (Hybrid Optimisation by Genetic Algorithms), a program that uses a Genetic Algorithm (GA) to design a PV-Diesel system (sizing and operation control of a PV-Diesel system). The program has been developed in C++.In this paper a PV-Diesel system optimised by HOGA is compared with a stand-alone PV-only system that has been dimensioned using a classical design method based on the available energy under worst-case conditions. In both cases the demand and the solar irradiation are the same. The computational results show the economical advantages of the PV-hybrid system. HOGA is also compared with a commercial program for optimisation of hybrid systems.Furthermore, we show a number of results and conclusions about hybrid systems optimised by HOGA.     

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.     

Hybrid fuel cell and battery propulsion system modelling and multi-objective optimisation for a coastal ferry

Efforts from all sectors of society including the shipping industry are needed to limit the overall global temperature rise to within 2°C of pre-industrial levels by 2050. The hybridisation of Proton Exchange Membrane Fuel Cells (PEMFC) and Lithium-ion batteries for coastal ship propulsion systems may potentially offer beneficial emission performance. However, such hybrid systems are constrained by power and energy density limitations, lifetime; and costs as well as life-cycle emissions of alternative fuel/energy. There is a lack of holistic design methodology dealing with these uncertainties in the literature. This paper proposes a holistic design methodology for coastal hybrid ships based upon a developed model. The power source sizing problem is solved using constrained mixed-integer multi-objective optimisation in the external layer. The global optimum energy management strategies for an averaged operating profile are obtained from deterministic dynamic programming in the inner layer, while considering power source degradations in the sizing algorithm. The proposed methodology was applied to a coastal ferry to investigate the feasibility and benefit potential of adopting the hybrid PEMFC and battery propulsion system in Matlab. The case studies indicate that the proposed propulsion system can achieve at least a 65% life-cycle greenhouse gas reduction for the considered two cases.     

Autonomous hybrid photovoltaic power plant using a back-up generator: A case study in a Mediterranean island

Using a stand-alone photovoltaic array as a unique source of supply for a local electric demand generally induces a significant excess in energy production. A solution to the problem appears through the use of a hybrid system, which gives a good way to improve the energy balance together with minimum investment. A sizing method starting from meteorological conditions in Corsica was extended to a twin-source system: solar/fuel electric generator with each source contribution being optimized. The results obtained from such an approach show that a 75% solar rate is an optimal value to obtain an energy balance fitted to the local demand when compared to other systems for decentralized electricity generation. The methodology was tested and validated, through an existing hybrid PV system in Corsica (44 kW). This paper does not present a general sizing method for the hybrid system, but is just a case study.     

Experimental investigation on the online fuzzy energy management of hybrid fuel cell/battery power system for UAVs

The hybrid powerplant combining a fuel cell and a battery has become one of the most promising alternative power systems for electric unmanned aerial vehicles (UAVs). To enhance the fuel efficiency and battery service life, highly effective and robust online energy management strategies are needed in real applications.In this work, an energy management system is designed to control the hybrid fuel cell and battery power system for electric UAVs. To reduce the weight, only one programmable direct-current to direct-current (dcdc) converter is used as the critical power split component to implement the power management strategy. The output voltage and current of the dcdc is controlled by an independent energy management controller. An executable process of online fuzzy energy management strategy is proposed and established. According to the demand power and battery state of charge, the online fuzzy energy management strategy produces the current command for the dcdc to directly control the output current of the fuel cell and to indirectly control the charge/discharge current of the battery based on the power balance principle.Another two online strategies, the passive control strategy and the state machine strategy, are also employed to compare with the proposed online fuzzy strategy in terms of the battery management and fuel efficiency. To evaluate and compare the feasibility of the online energy management strategies in application, experiments with three types of missions are carried out using the hybrid power system test-bench, which consists of a commercial fuel cell EOS600, a Lipo battery, a programmable dcdc converter, an energy management controller, and an electric load. The experimental investigation shows that the proposed online fuzzy strategy prefers to use the most power from the battery and consumes the least amount of hydrogen fuel compared with the other two online energy management strategies.     

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.     

An improved energy management strategy for FC/UC hybrid electric vehicles propelled by motor-wheels

The hybridization of the fuel-cell electric-vehicle (FCEV) by a second energy source has the advantage of improving the system's dynamic response and efficiency. Indeed, an ultra-capacitor (UC) system used as an energy storage device fulfills the FC slowest dynamics during fast power transitions and recovers the braking energy. In FC/UC hybrid vehicles, the search for a suitable power management approach is one of the main objectives. In this paper, an improved control strategy managing the active power distribution between the two energy sources is proposed. The UC reference power is calculated through the DC link voltage regulation. For the FC power demand, an algorithm with five operating modes is developed. This algorithm, depending on the UC state of charge (SOC) and the vehicle speed level, minimizes the FC power demand transitions and therefore ameliorates its durability. The traction power is provided using two permanent magnetic synchronous motor-wheels to free more space in the vehicle. The models of the FC/UC vehicle system parts and the control strategy are developed using MATLAB software. Simulation results show the effectiveness of the proposed energy management strategy.     

Autonomous hybrid system and coordinated intelligent management approach in power system operation and control using hydrogen storage

Autonomous hybrid power systems are attractive research questions that deliver electricity to isolated consumers without being connected to the power grid. The deployment of autonomous hybrid power systems is considered as an option to improve energy security. For this reason, the main objective is to ensure the efficient production of electricity without interruption. To achieve this goal, we have proposed an accurate simulation system in which a solar energy component serves as a primary load supply, and an energy recovery component is based on a fuel cell. A long-term energy storage component comprises a water electrolyzer which is considered a primary storage and an ultracapacitor storage component deployed as a short-term storage of energy. To achieve the correct system operation, a new schema approach for intelligent energy management based on a multi-agent system is developed and discussed. The main task is to define the architecture of the multi-agent system and to define the functions of all the agents according to the characteristics of the energy needs and the production costs. Thus, in order to prove the reliability and effectiveness of the applied control strategy and its impact on the operation of the system, the proposed system is simulated using the Matlab/Simulink environment by referring to an extracted experimental database of the Tunisian Meteorological Service.     

Hierarchical energy management for PV/hydrogen/battery island DC microgrid

This research presents an optimum design scheme and a hierarchical energy management strategy for an island PV/hydrogen/battery hybrid DC microgrid (MG). In order to efficiently utilize this DC MG, the optimum structure and sizing scheme are designed by HOMER pro (Hybrid Optimization of Multiple Energy Resources) software. The designed structure of hydrogen MG includes a PV generation, a battery as well as a hydrogen subsystem which composes a fuel cell (FC) system, an electrolyzer and hydrogen tank. To improve the robustness and economy of this DC MG, this study schedules a hierarchical energy management method, including the local control layer and the system control layer. In the local control layer, the subsystems in this DC MG are controlled based on their inherent operating characteristics. And the equivalent consumption minimization strategy (ECMS) is applied in the system control layer, the power flow between the battery and FC is allocated to minimum the fuel consumption. An island DC MG hardware-in-loop (HIL) Simulink platform is established by RT-LAB real-time simulator, and the simulation results are presented to validate the proposed energy management strategy.     

Modelling of hybrid energy system—Part II: Combined dispatch strategies and solution algorithm

Computer simulation is an increasingly popular tool for determining the most suitable hybrid energy system type, design and control for an isolated community or a cluster of villages. This paper presents the development of the optimum control algorithm based on combined dispatch strategies, to achieve the optimal cost of battery incorporated hybrid energy system for electricity generation, during a period of time by solving the mathematical model, which was developed in Part I of this tri-series paper.The main purpose of the control system proposed here is to reduce, as much as possible, the participation of the diesel generator in the electricity generation process, taking the maximum advantage of the renewable energy resources available.The overall load dispatch scenario is controlled by the availability of renewable power, total system load demand, diesel generator operational constraints and the proper management of the battery bank. The incorporation of a battery bank makes the control operation more practical and relatively easier.     

Optimum design of hybrid renewable energy systems: Overview of different approaches

Public awareness of the need to reduce global warming and the significant increase in the prices of conventional energy sources have encouraged many countries to provide new energy policies that promote the renewable energy applications. Such renewable energy sources like wind, solar, hydro based energies, etc. are environment friendly and have potential to be more widely used. Combining these renewable energy sources with back-up units to form a hybrid system can provide a more economic, environment friendly and reliable supply of electricity in all load demand conditions compared to single-use of such systems. One of the most important issues in this type of hybrid system is to optimally size the hybrid system components as sufficient enough to meet all load requirements with possible minimum investment and operating costs. There are many studies about the optimization and sizing of hybrid renewable energy systems since the recent popular utilization of renewable energy sources. In this concept, this paper provides a detailed analysis of such optimum sizing approaches in the literature that can make significant contributions to wider renewable energy penetration by enhancing the system applicability in terms of economy.     

Hybrid energy storage systems for stand-alone electric power systems: optimization of system performance and cost through control strategies

The development of remote, renewable-based energy is hindered in part by the lack of affordable energy storage. Requiring power-on-demand from an energy system powered by intermittent or seasonal sources may necessitate one-month’s energy storage—an expensive proposition using conventional storage technologies. If multiple energy storage devices with complementary performance characteristics are used together, the resulting ‘hybrid energy-storage system’ can dramatically reduce the cost of energy storage over single storage systems. The coupling of conventional storage batteries with emerging hydrogen technologies provides one such hybrid system. Hydrogen energy storage in this context includes an electrolyzer, hydrogen storage tank, and a fuel cell. An additional component that must be considered is the control system that determines when the various components are used. Since the control system has an effect on component sizes and thus system and operating costs, the control algorithm must be carefully considered for any system with energy storage. For this study, a time-dependent model of a stand-alone, solar powered, battery-hydrogen hybrid energy storage system was developed to investigate energy storage options for cases where supply and demand of energy are not well matched daily or seasonally. Simulations were performed for residential use with measured solar fluxes and simulated hourly loads for a site at Yuma, Arizona, USA, a desert climate at 32.7 N latitude. Renewable-based power not needed to satisfy the load is stored for later use. Two hybrid energy-storage algorithms were considered. The first is a conventional ‘state-of-charge’ control system that uses the current state of the storage system for control. The second control system presumes knowledge of future demand through a feed-forward, neural net or other ‘intelligent’ control systems. Both algorithms use battery storage to provide much of the daily energy shifting and hydrogen to provide seasonal energy shifting, thus using each storage technology to its best advantage. The cost of storing energy with a hybrid energy-storage scheme was found to be much less expensive than either single storage method, with a hybrid system storage costing 48% of the cost of a hydrogen-only system and only 9% of the cost of a conventional, battery-only system. In addition, the neural-net control system is compared to a standard battery state-of-charge control scheme, and it is shown that neural-net control systems better utilize expensive components and result in less expensive electric power than state-of-charge control systems.     

A model for optimal sizing of photovoltaic irrigation water pumping systems

The previous methods for optimal sizing of photovoltaic (PV) irrigation water pumping systems separately considered the demand for hydraulic energy and possibilities of its production from available solar energy with the PV pumping system. Unlike such methods, this work approaches the subject problem systematically, meaning that all relevant system elements and their characteristics have been analyzed: PV water pumping system, local climate, boreholes, soil, crops and method of irrigation; therefore, the objective function has been defined in an entirely new manner. The result of such approach is the new mathematical hybrid simulation optimization model for optimal sizing of PV irrigation water pumping systems, that uses dynamic programming for optimizing, while the constraints were defined by the simulation model. The model was tested on two areas in Croatia, and it has been established that this model successfully takes into consideration all characteristic values and their relations in the integrated system. The optimal nominal electric power of PV generator, obtained in the manner presented, are relatively smaller than when the usual method of sizing is used. The presented method for solving the problem has paved the way towards the general model for optimal sizing of all stand-alone PV systems that have some type of energy storage, as well as optimal sizing of PV power plant that functions together with the storage hydroelectric power plant.     

Sizing optimization,dynamic modeling and energy management strategies of a stand-alone PV/hydrogen/battery-based hybrid system

This paper presents a sizing method and different control strategies for the suitable energy management of a stand-alone hybrid system based on photovoltaic (PV) solar panels, hydrogen subsystem and battery. The battery and hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as energy storage and support system. In order to efficiently utilize the energy sources integrated in the hybrid system, an appropriate sizing is necessary. In this paper, a new sizing method based on Simulink Design Optimization (SDO) of MATLAB was used to perform a technical optimization of the hybrid system components. An analysis cost has been also performed, in that the configuration under study has been compared with those integrating only batteries and only hydrogen system. The dynamic model of the designed hybrid system is detailed in this paper. The models, implemented in MATLAB-Simulink environment, have been designed from commercially available components. Three control strategies based on operating modes and combining technical-economic aspects are considered for the energy management of the hybrid system. They have been designed, primarily, to satisfy the load power demand and, secondarily, to maintain a certain level at the hydrogen tank (hydrogen energy reserve), and at the state of charge (SOC) of the battery bank to extend its life, taking into account also technical-economic analysis. Dynamic simulations were performed to evaluate the configuration, sizing and control strategies for the energy management of the hybrid system under study in this work. Simulation results show that the proposed hybrid system with the presented controls is able to provide the energy demanded by the loads, while maintaining a certain energy reserve in the storage sources.