Optimum sizing of photovoltaic battery systems incorporating uncertainty through design space approach

Photovoltaic-battery system is an option for decentralized power generation for isolated locations receiving abundant sunshine. A methodology for the optimum sizing of photovoltaic-battery system for remote electrification incorporating the uncertainty associated with solar insolation is proposed in this paper. The proposed methodology is based on the design space approach involving a time series simulation of the entire system. The design space approach was originally proposed for sizing of the system with deterministic resource and demand. In the present paper, chance constrained programming approach has been utilized for incorporating the resource uncertainty in the system sizing and the concept of design space is extended to incorporate resource uncertainty. The set of all feasible design configurations is represented by a sizing curve. The sizing curve for a given confidence level, connects the combinations of the photovoltaic array ratings and the corresponding minimum battery capacities capable of meeting the specified load, plotted on an array rating vs. battery capacity diagram.The methodology is validated using a sequential Monte Carlo simulation approach with illustrative examples. It is shown that for the case of constant coefficient of variation of solar insolation, the set of sizing curves for different confidence levels may be represented by a generalized curve. Selection of optimum system configuration for different reliability levels based on the minimum cost of energy is also presented. The effect of ambient temperature on sizing a stand-alone photovoltaic-battery system is also illustrated through a representative example.     

Optimum sizing of wind-battery systems incorporating resource uncertainty

The inherent uncertainty of the wind is a major impediment for successful implementation of wind based power generation technology. A methodology has been proposed in this paper to incorporate wind speed uncertainty in sizing wind-battery system for isolated applications. The uncertainty associated with the wind speed is incorporated using chance constraint programming approach. For a pre-specified reliability requirement, a deterministic equivalent energy balance equation may be derived from the chance constraint that allows time series simulation of the entire system. This results in a generation of the entire set of feasible design options, satisfying different system level constraints, on a battery capacity vs. generator rating diagram, also known as the design space. The proposed methodology highlights the trade-offs between the wind turbine rating, rotor diameter and the battery size for a given reliability of power supply. The optimum configuration is chosen on the basis of the minimum cost of energy (US$/kWh). It is shown with the help of illustrative examples that the proposed methodology is generic and flexible to incorporate alternate sub-component models.     

Application of design space methodology for optimum sizing of wind–battery systems

A methodology for optimum sizing of different components (i.e., rotor diameter, electrical generator rating, and battery capacity) of a standalone wind–battery system is proposed in this paper. On the basis of time series simulation of the system performance along with different design constraints, the entire set of feasible design options, also known as the design space, has been identified on a rotor diameter vs. rated power diagram. The design space of a standalone wind–battery system identifies the entire envelope within which a feasible system may be designed. The optimum configuration of the standalone system is identified on the basis of minimum cost of energy (US$/kWh). It is observed that the cost of energy is sensitive to the magnitude of average demand and the wind regime. Sensitivity of the capital cost on the minimum cost of energy is also studied.     

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.     

Optimal green energy management for island resorts in Malaysia

This paper proposes optimum green energy systems for electricity generation of island resorts in Malaysia. A combination of solar energy and wind energy as intermittent renewable energy sources with a fuel cell (FC) system and a battery storage energy system as a backup to the green energy system is introduced for this study. This system is eco-friendly, economical over the long-term, highly sustainable and reliable. In addition, a diesel-based energy system as a non-green system is compared with the proposed green system. National Renewable Energy Laboratory's (NREL) HOMER software is used to determine and compare the optimal configuration green energy system with the diesel-based energy system in terms of net present cost, sensitivity analysis and pollutant gas emission. The feasibility and assessment of the proposed system is evaluated by utilizing the load profile and considering the geographical condition of a village (Juara village in Tioman Island) with approximately 30 chalets located in southern Malaysia. HOMER uses two types of load profiles for each given year. The first load profile is used during the presence of tourists, and the second profile is used when the locals are the main inhabitants of the island. The optimization management for the green energy system is performed through unit sizing to find the optimum power management analysis and to perform cost analysis of the system.The potential of renewable energy as well as a diesel-based energy system to meet the power demand for such a stand-alone system is considered. Technically feasible and economically viable green energy systems as prospective plans are explored in this study.     

Hybrid systems for decentralized power generation in Oman

The main objective of this study is to determine the optimum size of systems able to fulfil the electrical energy requirements of remote sites located in Hajer Bani (HB) Hameed in the North of Oman, Masirah Island and the Mothorah area in the South of Oman. The methodology applied provides a useful and simple approach for sizing and analysing the hybrid systems using Hybrid Optimization Model for Electric Renewables (HOMER). The aim is to identify a configuration among a set of systems that meet the desired system reliability requirements with the lowest energy cost. The results of the analysis are a list of feasible power supply systems, classified according to their net present cost. Actual hourly load data are taken from these sites and are used in the model, and the meteorological readings are used either from the same site or from a nearby one. A comparison between the costs of electricity generated from renewable energy resources in these locations is done and the payback period for renewable energy components is calculated. Moreover, the effects of the temperature on the photovoltaic cells efficiency and energy cost are considered. The cost of energy was found to be 0.206, 0.361 and 0.327 $/kWh for Masirah Island, Mothorah and HB Hameed, respectively.     

State-of-art review of the optimization methods to design the configuration of hybrid renewable energy systems (HRESs)

The current research aims to present an inclusive review of latest research works performed with the aim of improving the efficiency of the hybrid renewable energy systems (HRESs) by employing diverse ranges of the optimization techniques, which aid the designers to achieve the minimum expected total cost, while satisfying the power demand and the reliability. For this purpose, a detailed analysis of the different classification drivers considering the design factors such as the optimization goals, utilized optimization methods, grid type as well as the investigated technology has been conducted. Initial results have indicated that among all optimization goals, load demand parameters including loss of power supply probability (LPSP) and loss of load probability (LLP), cost, sizing (configuration), energy production, and environmental emissions are the most frequent design variables which have been cited the most. Another result of this paper indicates that almost 70% of the research projects have been dedicated towards the optimization of the off-grid applications of the HRESs. Furthermore, it has been demonstrated that, integration of the PV, wind and battery is the most frequent configuration. In the next stage of the paper, a review concerning the sizing methods is also carried out to outline the most common techniques which are used to configure the components of the HRESs. In this regard, an analysis covering the optimized indicators such as the cost drivers, energy index parameters, load indicators, battery’s state of charge, PV generator area, design parameters such as the LPSP, and the wind power generation to load ratio, is also performed.     

SIZING AND TECHNO-ECONOMICAL OPTIMIZATION FOR HYBRID SOLAR PHOTOVOLTAIC/WIND POWER SYSTEMS WITH BATTERY STORAGE

A general methodology is presented for the sizing and optimization of renewable power supply systems, including hybrids such as those with solar photovoltaic and wind power components. The technical and economic optimum configurations are found by reference to periods over which the average resource (e.g. wind/solar) is least or the average load demand is greatest. For stand-alone systems, the annual autonomy is an important further design factor. This is the fraction of time for which the specified load can be met. The optimization seeks the least expensive system configuration which achieves the required autonomy level. It is the autonomy level which largely determines the size of battery storage capacity required. A system performance simulation procedure, with an hourly time-step, is used to obtain the autonomy levels of potentially optimum arrangements as the battery size is varied. Illustrative examples of the use of the method employ annual and monthly averaging periods, although any other period may be used. Data refer to the particular location and load pattern for an existing hybrid system, but the method is quite generally applicable. © 1997 by 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.     

Development of IREOM model based on seasonally varying load profile for hilly remote areas of Uttarakhand state in India

An Integrated Renewable Energy Optimization Model (IREOM) model has been developed for sizing and optimization of renewable energy systems based on seasonal variation in the load profiles of the study area. An attempt has been made to develop correlations between renewable energy system sizes and their capital cost for the user specified system sizes. The developed correlations were used for the analysis of IREOM model using user specified system sizes and compared with manufacturer specified system sizes. The cluster of seven unelectrified villages having micro-hydro power, biomass, wind and solar energy resources in the state of Uttarakhand, India has been considered for the implementation of IREOM model. Based on the results obtained from the proposed model, suitable sizes of renewable energy systems have been suggested.     

Design optimization for the hybrid power system of a green building

This paper proposes an optimal design procedure for a green building equipped with renewable energy, energy storages, and proton exchange membrane fuel cells (PEMFCs). First, we introduce the hybrid power system of the green building and construct a simulation model using Matlab/SimPowerSystem?. The model parameters are tuned so that the system responses can be estimated without extensive experiments in the optimization processes. Second, we define the cost and reliability indexes to optimize the system design using three steps: component selection, component sizing, and power management (PM) adjustment. We further define the safety index to evaluate the system's sustainability under extreme conditions when no renewable energy is available. Last, we apply the proposed procedures to the green building and demonstrate the benefits of the optimal design. The proposed method can be directly applied to develop customized hybrid power systems in the future.     

Modeling of integrated renewable energy system for electrification of a remote area in India

Over the years, renewable energy based power generation has proven to be a cost-effective solution in stand-alone applications in the regions where grid extension is difficult. The present study focused on the development of models for optimal sizing of integrated renewable energy (IRE) system to satisfy the energy needs in different load sectors of four different zones considered in Chamarajanagar district of Karnataka state in India. The objective of the study is to minimize the total cost of generation and cost of energy using genetic algorithm (GA) based approach. Considering optimization power factor (OPF) and expected energy not supplied (EENS), optimum system feasibility has been investigated. Based on the study, it has been found that IRES is able to provide a feasible solution between 1.0 and 0.8 OPF values. However, power deficit occurs at OPF values less than 0.8 and the proposed model becomes infeasible under such conditions. Customer interruption cost (CIC) and deficit energy (DE) for all zones were also computed to quantify the reliability of the systems.     

Optimal operation of DC smart house system by controllable loads based on smart grid topology

From the perspective of global warming mitigation and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all-electric apartment houses or residence such as DC smart houses are increasing. However, due to the fluctuating power from renewable energy sources and loads, supply-demand balancing of power system becomes problematic. Smart grid is a solution to this problem. This paper presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuation. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuation, it is possible to reduce the electric power consumption and the cost of electricity. This system consists of photovoltaic generator, heat pump, battery, solar collector, and load. To verify the effectiveness of the proposed system, results are used in simulation presented.     

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.     

Design of solar thermal systems utilizing pressurized hot water storage for industrial applications

A large number of industrial processes demand thermal energy in the temperature range of 80–240 °C. In this temperature range, solar thermal systems have a great scope of application. However, the challenge lies in the integration of a periodic, dilute and variable solar input into a wide variety of industrial processes. Issues in the integration are selection of collectors, working fluid and sizing of components. Application specific configurations are required to be adopted and designed. Analysis presented in this paper lays an emphasis on the component sizing. The same is done by developing a design procedure for a specific configuration. The specific configuration consists of concentrating collectors, pressurized hot water storage and a load heat exchanger. The design procedure follows a methodology called design space approach. In the design space approach a mathematical model is built for generation of the design space. In the generation of the design space, design variables of concern are collector area, storage volume, solar fraction, storage mass flow rate and heat exchanger size. Design space comprises of constant solar fraction curves traced on a collector area versus storage volume diagram. Results of the design variables study demonstrate that a higher maximum storage mass flow rates and a larger heat exchanger size are desired while limiting storage temperature should be as low as possible. An economic optimization is carried out to design the overall system. In economic optimization, total annualized cost of the overall system has been minimized. The proposed methodology is demonstrated through an illustrative example. It has been shown that 23% reduction in the total system cost may be achieved as compared to the existing design. The proposed design tool offers flexibility to the designer in choosing a system configuration on the basis of desired performance and economy.     

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.     

Minimizing the energy cost for microgrids integrated with renewable energy resources and conventional generation using controlled battery energy storage

This paper presents a methodology to minimize the total cost of buying power from different energy producers including renewable energy generations particularly within the context of a microgrid. The proposed idea is primarily based on the controlled operation of a battery energy storage system (BESS) in the presence of practical system constraints coupled with our proposed cost optimization algorithm. The complex optimization problem with constraints has been solved using the well-known concept of dynamic programming. The methodology has been assessed using actual power and price data from six different power generation sites and cost reduction has been calculated for a number of BESSs by varying their energy and power capacities. Twofold benefits of the proposed methodology lie in minimizing the total cost along with the constraint-based efficient operation of the BESS. Simulation results depict that the given power demand at a particular region can be fulfilled properly at all times using a BESS and multiple power generation.     

Sizing of integrated renewable energy system based on load profiles and reliability index for the state of Uttarakhand in India

In recent years the decentralized rural electrification is becoming cost effective and convenient for areas where grid extension is very difficult. The present paper deals with the electrification of dense forest areas of Uttarakhand state in India by Integrated Renewable Energy Optimization Model (IREOM). The IREOM consists of locally available renewable energy resources such as Micro-Hydropower (MHP), biomass, biogas, wind and solar photovoltaic (SPV) systems have been used to meet electrical energy and cooking energy needs of a cluster of villages. The paper includes the selection of different system components, sizing and development of a general model to find out optimal combination of energy subsystems for the selected study area in order to minimize the cost of energy (COE) generation for a required reliability values. The sizing of different renewable energy system components has been carried out so that they are suitable for four different seasonal load profiles. The two reliability values are considered for the selection of optimum solution of year round application. The model developed for this purpose, has been found to be quite useful in optimizing the renewable energy system sizes that are available in market. The proposed model totally depends on the renewable energy systems and eliminates the use of conventional energy systems.     

An optimal sizing method for stand-alone photovoltaic power systems

The total life-cycle cost of stand-alone photovoltaic (SAPV) power systems is mathematically formulated. A new optimal sizing algorithm for the solar array and battery capacity is developed. The optimum value of a balancing parameter, M, for the optimal sizing of SAPV system components is derived. The proposed optimal sizing algorithm is used in an illustrative example, where a more economical life-cycle cost has been obtained. The question of cost versus reliability is briefly discussed.     

Intelligent optimization of renewable resource mixes incorporating the effect of fuel risk,fuel cost and CO2 emission

Power system planning is a capital intensive investment-decision problem. The majority of the conventional planning conducted since the last half a century has been based on the least cost approach, keeping in view the optimization of cost and reliability of power supply. Recently, renewable energy sources have found a niche in power system planning owing to concerns arising from fast depletion of fossil fuels, fuel price volatility as well as global climatic changes. Thus, power system planning is under-going a paradigm shift to incorporate such recent technologies. This paper assesses the impact of renewable sources using the portfolio theory to incorporate the effects of fuel price volatility as well as CO₂ emissions. An optimization framework using a robust multi-objective evolutionary algorithm, namely NSGA-II, is developed to obtain Pareto optimal solutions. The performance of the proposed approach is assessed and illustrated using the Indian power system considering real-time design practices. The case study for Indian power system validates the efficacy of the proposed methodology as developing countries are also increasing the investment in green energy to increase awareness about clean energy technologies.