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Due to the fluctuation and intermittency of distributed PV generation, battery energy storage is required with higher renewable installation towards carbon neutrality. Thus, the photovoltaic battery (PVB) system receives increasing attention. This study provides a critical review on PVB system design optimization, including system component sizing and strategy improvement studies, from mathematical modeling, evaluation system establishment to feasibility and optimization studies. Several PVB simulation software packages are compared and evaluated, and acknowledged system models are presented. The evaluation indicators are summarized from various aspects with cases of various evaluation systems combining different indicators or using the Pareto front for multi-criteria system designing. The PVB system feasibility study is analyzed from system configuration variation, critical technical and economic parameter analyses, rule-based operation strategies to future expectations like large-scale energy storage profitability, grid parity, and energy community trading platform. The targets, methods, tariff and time resolution influences, and PVB system capacity optimization design recommendations are critically discussed. The research directions for system operation development and future expectations are analyzed from system feasibility, flexibility to resilience. The co-planning of PVB system capacity and operation design optimization makes the problem complicated, leading to relatively short time resolution but more flexibility to system operation strategy. This study could provide guidance and references to distributed PVB system future design and optimization studies. [ABSTRACT FROM AUTHOR]

Based on the Sustainable Development Goals outlined in the 2030 agenda of the United Nations, affordable and clean energy is one of the most relevant goals to achieve the decarbonization targets and break down the global climate change effects. The use of renewable energy sources, namely, solar energy, is gaining attention and market share due to reductions in investment costs. Nevertheless, it is important to overcome the energy storage problems, mostly in industrial applications. The integration of photovoltaic power plants with hydrogen production and its storage for further conversion to usable electricity are an interesting option from both the technical and economic points of view. The main objective of this study is to analyse the potential for green hydrogen production and storage through PV production, based on technical data and operational considerations. We also present a conceptual model and the configuration of a PV power plant integrated with hydrogen production for industry supply. The proposed power plant configuration identifies different pathways to improve energy use: supply an industrial facility, supply the hydrogen production and storage unit, sell the energy surplus to the electrical grid and provide energy to a backup battery. One of the greatest challenges for the proposed model is the component sizing and water electrolysis process for hydrogen production due to the operational requirements and the technology costs. [ABSTRACT FROM AUTHOR]

This paper aims to enhance the design and operation of a Combined Cooling, Heating, and Power (CCHP) system utilizing a gas engine as the primary energy source for a residential building in China. An Energy, Exergy, Economic, and Environment (4E) analysis is employed to assess the system's performance and impact based on energy, exergy, economic, and environmental criteria. The effectiveness of the DNGO algorithm is evaluated on a case study site and compared with Northern Goshawk Optimization (NGO) and Genetic Algorithm (GA). The findings demonstrate that the DNGO algorithm identifies the optimal gas engine size of 130 kW. The algorithm's search capabilities are greatly enhanced by this unique blend, surpassing what traditional methods can offer. The DNGO algorithm brings several advantages, including unparalleled energy efficiency, reduced exergy destruction, and a substantial decrease in CO2 emissions. This not only supports environmental sustainability but also aligns with global standards. Economically, the algorithm enhances the performance of the CCHP system, evident through a reduced payback period and increased annual profit. Additionally, the algorithm's rapid convergence rate allows it to reach the optimal solution faster than its counterparts, making it advantageous for time-sensitive applications. Incorporating innovative methods like chaos theory, the DNGO algorithm effectively avoids local optima, enabling a broader search for the best solution. The utilization of Lévy flight further enhances the algorithm's ability to escape local optima and navigate the search space more efficiently. Additionally, swarm intelligence is employed to simulate the collective behavior of decentralized systems, aiding in problem-solving. This research represents a significant advancement in optimization techniques for CCHP systems and offers a fresh perspective to the field of swarm-based optimization algorithms.

The advent of the COVID-19 pandemic puts stress on the requirements of indoor air quality. Significant improvements in the design of building ventilation systems have become necessary, as this allows for the supply of higher quantities of outdoor air in buildings. Additional capital investment is necessary for increases in the size of ventilation fans and ducts, as well as for the installation of efficient air-to-air recuperators, to recover the enthalpy of the rejected air. To address the increased operation costs, smart strategies are necessary to make rational use of the ventilation system. The required modifications are studied in the example of an 18-zone office building located in Volos, Greece. The building's energy performance is studied by means of transient simulation. Operation of the ground-coupled heat pump, the upgraded ventilation system and the high-performance recuperators and filters' interactions is presented in detail at various time scales. The results show the effect of increased ventilation requirements of new and renovated office and commercial buildings in the post-COVID era. The added capital equipment and operation costs must be met with a strong and sustained engineering effort. Especially in the case of nZEB buildings, the protection of public health must be attained, with reduction of the added electricity consumption penalties, in order to keep the nZEB character of the building. [ABSTRACT FROM AUTHOR]

Integrated energy systems are one of the potential options for buildings that can reduce emission. In this research study, the energetic and economic performance of a micro-gas turbine combined heating and cooling plant coupled with a solar PV is analyzed for an office building in Iran. For each analysis, two different scenarios have been performed. System sizing parameters defined in a way that renewable to fossil fuel share is correlated to plant performance and economy. To model the studied system, a time-dependent method is used, which is the inherent characteristic of renewable energies. The renewable energies used here are solar heaters and solar panels. Contours of Net Present Value (NPV) are evaluated as a function of solar heating share and different economic parameters. In addition, optimal system sizing for a typical building is obtained and the results are provided. Effect of various major parameters shows that under the current condition and despite the supportive incentive for renewable energies, strategies and plans even without solar energy are not economically viable due to the high discount rates. In addition, results provide that, in reasonable and normal discount rate, fuel and grid electricity prices, governmental subsidization for conventional combined heat, and power (CHP) and combined cooling, heat, and power(CCHP) is not necessary, and only in this condition solar electricity selling price (i.e. governmental support program) is effective to increase renewable penetration. The results show that if the interest rate is less than 5%, the NPV becomes positive. Also, when the electricity price reaches $0.07/kWh or higher, the NPV becomes positive. [ABSTRACT FROM AUTHOR]

Energy management strategy (EMS) of hybrid energy storage systems has an essential mission of ensuring safety, enhancing reliability and improving system efficiency. This paper focuses on optimizing sizing of HESS and parameters of EMS simultaneously. Firstly, an improved model is employed in adaptive predictive model control (AMPC). Secondly, in order to minimize the cost of supercapacitors and the capacity degradation of batteries at the same time, the multiple objective optimization problems are solved by Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). The nine variables are decided including seven parameters of AMPC and series-parallel number of supercapacitors. Subsequently, the support vector machine combined with the gray wolf optimization algorithm (GWO-SVM) is employed to enhance the applicability of EMS. Finally, in order to prove the superiority of the proposed EMS, a combined cycle and a real cycle are performed for validation. The results illustrate that the proposed method can improve the efficiency of the system and enhance the life span of the battery. Comparing with AMPC-only, the total energy loss can be reduced by at least 17.9%. A reduction of not less than 8.8% in RMS of battery current is obtained. The Ah-throughput can be reduced by at least 2.5%. In further discussions, the superiority of MOEA/D and GWO-SVM is proved by comparing with other methods. [ABSTRACT FROM AUTHOR]

Summary: Employing renewable resources, which act as an alternative energy source for desalination plants, has become one of the promising solutions for overcoming the water crisis. The various experimental, pilot, and research desalination projects powered by renewable resources have validated its practical feasibility in the past decade. An optimal planning scheme must be adopted to enhance these new resources' competitiveness in terms of cleanness, reliability, and affordability. Accordingly, this paper proposes a potable water production system based on water desalination. The desalination unit is supplied by a synergistic wind‐PV system integrated with an electrical energy storage system and a water tank. Also, a diesel generator is considered for power production during periods of critical power production and power/water storage. The resultant air pollution is modeled and controlled to ensure the system's cleanliness. The size of the desalination unit, water tank, associated pumps, and power supply components are optimized simultaneously to ensure a minimum‐cost plan. The proposed model exhibits linearity while preserving a predefined level of water supply reliability and a yearly emission cap. The model is implemented on a test case, and a comprehensive sensitivity analysis is performed to evaluate its effectiveness to obtain optimal results. [ABSTRACT FROM AUTHOR]

This paper aims to enhance the design and operation of a Combined Cooling, Heating, and Power (CCHP) system utilizing a gas engine as the primary energy source for a residential building in China. An Energy, Exergy, Economic, and Environment (4E) analysis is employed to assess the system's performance and impact based on energy, exergy, economic, and environmental criteria. The effectiveness of the DNGO algorithm is evaluated on a case study site and compared with Northern Goshawk Optimization (NGO) and Genetic Algorithm (GA). The findings demonstrate that the DNGO algorithm identifies the optimal gas engine size of 130 kW. The algorithm's search capabilities are greatly enhanced by this unique blend, surpassing what traditional methods can offer. The DNGO algorithm brings several advantages, including unparalleled energy efficiency, reduced exergy destruction, and a substantial decrease in C O 2 emissions. This not only supports environmental sustainability but also aligns with global standards. Economically, the algorithm enhances the performance of the CCHP system, evident through a reduced payback period and increased annual profit. Additionally, the algorithm's rapid convergence rate allows it to reach the optimal solution faster than its counterparts, making it advantageous for time-sensitive applications. Incorporating innovative methods like chaos theory, the DNGO algorithm effectively avoids local optima, enabling a broader search for the best solution. The utilization of Lévy flight further enhances the algorithm's ability to escape local optima and navigate the search space more efficiently. Additionally, swarm intelligence is employed to simulate the collective behavior of decentralized systems, aiding in problem-solving. This research represents a significant advancement in optimization techniques for CCHP systems and offers a fresh perspective to the field of swarm-based optimization algorithms., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

[Display omitted] • The tolerable water probability shortage threshold is the key parameter. • About 10% of the total power is used to fulfill the yearly water needs. • To fulfill the water needs, no need to maximize the annual electric production. • Minimizing the overall size of the PV array may not minimize the cost of the system. • Minimizing the selected PV panel power may not minimize the cost of the system. The United Nations estimates that about 25% of the earth's population will live in countries where access to water will be a recurrent problem by 2025. This article proposes a methodology and open-access software tool for rural off-grid communities and users with little knowledge about solar photovoltaic water pumping systems (SPVWPS) to provide access to safe water for consumption. The proposed methodology assists in all stages of the project: conducting a prefeasibility study, sizing and optimizing, maintenance and financial analysis. It includes components selection, optimal dimensioning of the SPVWPS, behavior prediction, yearly distribution of the water shortage probability (WSP) and a basic financial analysis. The tool suggests a water tariff to help ensure the project's financial viability. The most interesting findings of this research is that the size – hence the feasabilty – of a project depends mostly on the population tolerance to water shortage. The concept of water shortage probability (WSP) is introduced to help in defining the appropriate size and cost of the systems. This WSP is calculated for each day of the year. A comprehensive literature review is presented and two case studies were used to validate its potential. It is found that only about 10% of the total energy produced by the PV modules is effectively used to fulfill the water needs. [ABSTRACT FROM AUTHOR]

Delivering fast response times for user transactions is a critical requirement for Web services. Often, a Web service has Service Level Agreements (SLA) with its users that quantify how quickly the service has to respond to a user transaction. Typically, SLAs stipulate requirements for Web service response time percentiles, e.g., a specified target for the 95th percentile of response time. Violating SLAs can have adverse consequences for a Web service operator. Consequently, operators require systematic techniques to predict Web service response time percentiles. Existing prediction techniques are very time consuming since they often involve manual construction of queuing or machine learning models. To address this problem, we propose Prospective, a data-driven approach for predicting Web service response time percentiles. Given a specification for workload expected at the Web service over a planning horizon, Prospective uses historical data to offer predictions for response time percentiles of interest. At the core of Prospective is a lightweight simulator that uses collaborative filtering to estimate response time behaviour of the service based on behaviour observed historically. Results show that Prospective significantly outperforms other baseline techniques for a wide variety of workloads. In particular, the technique provides accurate estimates even for workload scenarios not directly observed in the historical data. We also show that Prospective can provide a Web service operator with accurate estimates of the types and numbers of Web service instances needed to avoid SLA violations.

This paper considered the design of a stand-alone PV system that would be adequate to power a single residence and estimate the appropriate size of the solar panel. This system converts solar energy directly into electricity using photovoltaic principle in PV panel arrays. The electricity produced can be used to power most ac and dc electrical appliances. Inverter is used to convert the dc generated by the PV panels to ac for most domestic and industrial use. For continuous availability of power during days of autonomy (low insolation or cloudy days), battery storage system and charge controller (for battery charge and discharge control) are required. inverter, charge controller, battery, components interconnection wires. The sizing processes considered the quality of solar irradiation of the geographical location, effect of temperature de-rating, efficiency of components, system voltage selection, days of autonomy and load demand (in watt-hour). A residence in Gaza town was chosen as a case study. The minimum electrical load of 7.875kWh per day, household, Finally excel program simulation was designed to satisfy calculation equations process and generalize the program.

Countries with limited natural resources and high energy prices, such as Jordan, face significant challenges concerning energy consumption and energy efficiency, particularly in the context of climate change. Residential buildings are the most energy-consuming sector in Jordan. Photovoltaic (PV) systems on the rooftops of residential buildings can solve the problem of increasing electricity demands and address the need for more sustainable energy systems. This study calculated the potential electricity production from PV systems installed on the available rooftops of residential buildings and compared this production with current and future electricity consumption for residential households. A simulation tool using PV*SOL 2021 was used to estimate electricity production and a comparative method was used to compare electricity production and consumption. The results indicated that electricity production from PV systems installed on single houses and villas can cover, depending on the tilt angle and location of the properties, three to eight times their estimated future and current electricity use. PV installation on apartment buildings can cover 0.65 to 1.3 times their future and current electricity use. The surplus electricity produced can be used to mitigate urban energy demands and achieve energy sustainability.

This paper presents a novel design and control method of an active suspension system using a linear pump control–based hydraulic system for a cost-effective application. Various active suspension systems have been proposed and applied to vehicles due to its ability to improve ride comfort and handling performance even though these active suspension systems are not popular because of their complexity, high cost, heavyweight, and low power efficiency. A new type of active suspension actuator system was designed and validated herein based on the methods of actuator sizing and modified control scheme to address the aforementioned issues. System power capability has been analyzed under various dynamics and road conditions. Active suspension actuator components have been designed based on the results. The electro-hydraulic system is powered by a battery to reduce the energy consumption of the system; hence, it is operated by torque on demand. A double-acting linear hydraulic motor pump with a dual rack and pinion has been proposed for hydraulic force control with a simple on/off switch operation. The actuator force has been controlled by continuous linear motor pump displacement control via torque control using a three-phase synchronous brushless alternative current motor. Dynamic performance evaluation of the actuator system has been conducted using AMESIM and actual rig test. Active height and roll control algorithms for the enhancement of vehicle dynamics considering actuator dynamics have also been developed and validated through the rig and real vehicle tests. The evaluation results showed that the linear motor pump–based active suspension system performs as well as the previous complicated hydraulic active suspension system. The new active system proposed in this study was able to improve the vehicle dynamics using cost-effective actuation system significantly. [ABSTRACT FROM AUTHOR]

A novel solar-assisted heat pump heating system including the latent heat thermal energy storage component that enables flexible switching between different connection modes was developed in this study to provide a cost-effective and energy-efficient solution for hot water supply. The feasibility, energy efficiency, and economic performance of the system under different design parameters and operation modes were evaluated via the experimental validated numerical model of the heating system. The end-user loads and meteorological parameters highly affected the system performance under the same design scheme. The optimal system configuration and component size for promoting renewable energy penetration and decreasing electricity cost were further determined. A certain increment in the collection area substantially benefits system performance, resulting in an approximately 56.6 % reduction in energy consumption. The larger capacity of the heat pump reflects a slight improvement in the system performance; however, it would require a longer payback period. Compared with the single solar and air heat source, the energy consumption of the hybrid heat source system declined by 26.6 % and 68.0 %, respectively. The system implementing the demand-side management proved to be a more profitable solution, exhibiting a low carbon emission of 188.1 kg, significant potential to flatten peak load, and a large lifecycle cost saving of $1834.64. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for designing and sizing high-efficient hydrostatic transmissions (HTs) for heavy duty propulsion applications such as agricultural and construction machinery. The proposed method consists in providing cost effective HT architectures that maximizes efficiency at the most frequent operating conditions of the transmission, as opposed to the traditional HT design methods based on the most demanding requirements of the system. The sizing method is based on a genetic optimization algorithm for calculating the optimal displacement of the main units of the HT to maximizes the efficiency in the most frequent operating conditions of the vehicle. A simulation model for HTs is built in MATLAB/Simulink® environment to test three different circuit alternatives for basic HTs. Considering a particular 250 kW heavy-duty application for which drive cycle data were available, this study shows great improvement in energy efficiency (14%) and power saving (20.1%) at frequent operating conditions while still achieving the corner power condition.

Afghanistan is a key country between energy surplus areas (Central Asian Republics andIran) and energy deficit regions (Pakistan and India). It is in a position that can facilitate and launchregional electricity trade for the benefit of the region also derive significant gains for its own economyfrom energy imports and exports. On the other hand, Afghanistan is endowed with large renewableenergy resources (RERs), which it could exploit not only to satisfy its domestic power demand butalso to earn significant export revenue. This paper firstly explains the methodology and framework forthe power trade and then presents an optimization framework for profit maximization in the short-runtrading and cost minimization in the long-run trading. The proposed methodology is applied to a realcase between Afghanistan and Pakistan. The objective functions, parameters, variables and constraintsare described for both optimization models. System sizing, simulation and optimization are carriedout using genetic algorithm (GA) technique. The results in the short-run model represent optimalityof about 2654 MW electricity export from Afghanistan to Pakistan during summer. Moreover, resultsderived from running long-run model depict that by utilizing its RERs such as solar, wind and hydro,Afghanistan can not only meet its power demand but also can export to Pakistan during its deficitperiods and gain remarkable energy profits.

The shortage of sufficient available fresh water resources in Jordan to meet water needs forces the nation to look for new water supply sources also to meet the increasing demand for fresh water. In this manuscript, a case study for designing, optimizing and implementing an off-grid water desalination system using photovoltaic (PV) power generation system is introduced. The system is installed on a farm in Southern Ghore of Jordan valley where the access to the grid is not reliable enough to guarantee the desalination of the amount of water for the farm’s irrigation needs. The study offers a framework to aid in designing similar pilot plants where the classic power generation prediction is greatly affected by the environmental conditions. An off-grid PV system with a total nominal power of 10.4 kWp was designed, procured and installed in the southern part of Jordan Valley near Karma town. The system operates the pumping system as well as the reverse osmosis based desalination unit. A measurement system has been collection relevant data like temperature, radiation, voltage, current, water quality, pressure, etc. continuously for the last 4 years. In this paper we will present the sizing procedure used, the system design and evaluate the design using the collected data of the run-time of 4 years. Data about the water quality and amount of desalinated water will equally be used to evaluate the system. The paper will end with recommendations to adapt the system design in different part of the Middle East and North Africa (MENA) region.

This paper considered the design of a stand-alone PV system that would be adequate to power a single residence and estimate the appropriate size of the solar panel. This system converts solar energy directly into electricity using photovoltaic principle in PV panel arrays. The electricity produced can be used to power most ac and dc electrical appliances. Inverter is used to convert the dc generated by the PV panels to ac for most domestic and industrial use. For continuous availability of power during days of autonomy (low insolation or cloudy days), battery storage system and charge controller (for battery charge and discharge control) are required. inverter, charge controller, battery, components interconnection wires. The sizing processes considered the quality of solar irradiation of the geographical location, effect of temperature de-rating, efficiency of components, system voltage selection, days of autonomy and load demand (in watt-hour). A residence in Gaza town was chosen as a case study. The minimum electrical load of 7.875kWh per day, household, Finally excel program simulation was designed to satisfy calculation equations process and generalize the program.

The use of air source heat pump systems for space heating and cooling is a convenient retrofitting strategy for reducing building energy costs. This can be combined with the rooftop installation of photovoltaic panels, which can cover, to a significant degree—or even significantly exceed the building’s electricity needs, moving towards the zero energy building concept. Alternatively, increased capacity for rooftop photovoltaic (PV) installation may support the ongoing process of transforming the Greek power system away from the reliance on fossil fuels to potentially become one of the leaders of the energy transition in Europe by 2030. Standard building energy simulation tools allow good assessment of the Heating, Ventilation and Air Conditioning (HVAC) and PV systems’ interactions in transient operation. Further, their use enables the rational sizing and selection of the type of panels type for the rooftop PV installation to maximize the return on investment. The annual performance of a three-zone residential building in Volos, Greece, with an air-to-water heat pump HVAC system and a rooftop PV installation, are simulated in a TRNSYS environment. The simulation results are employed to assess the expected building energy performance with a high performance, inverter driven heat pump with scroll compressor and high efficiency rooftop PV panels. Further, the objective functions are developed for the optimization of the installed PV panels’ area and tilt angle, based on alternative electricity pricing and subsidies. The methodology presented can be adapted to optimize system design parameters for variable electricity tariffs and improve net metering policies.

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• Using 1-s data instead of 1-h data is beneficial. • Nordic conditions increase the optimal sizing ratio. • We find an optimal array-to-inverter sizing ratio of 1.6–2.17. • The ratio is higher on smaller system sizes. The amount of installed solar power in Finland is increasing as a result of decreasing photovoltaic (PV) system component prices. The growth is especially noticeable in residential systems, and ways to make PV electricity a more competitive choice for Finnish residents are studied. One of these ways is to decrease the solar PV electricity production costs by decreasing the investment costs by undersizing the inverter of the PV system. The objective of undersizing is to find the optimal array-to-inverter sizing ratio (AISR) where the ratio of the economic loss from the clipped energy to the economic gain from the decreased system investment achieved by an undersized inverter is lowest. In this paper, the economically most optimal AISRs are determined for different residential array sizes, orientations, and inclinations when operating in Finnish locations and conditions. Calculations for each inverter size are carried out by using recorded Finnish meteorological data and the current Finnish PV system cost distribution, and by analyzing existing 1-s resolution production measurement data of a Finnish PV system. It is concluded that it is necessary to use 1-s resolution data as the use of 1-h resolution production data would lead to more significant undersizing caused by the power clipping occurring within an hour. The optimal AISRs presented in this study are higher than the optimal ratios reported in previous studies for locations further south than Finland. This can be explained by the northern location of Finland, where the irradiance above Standard Test Conditions (STC) is lower than in central Europe, for example. This allows more significant undersizing as less energy is clipped even at higher ratios. In the case of south-oriented arrays in a 30° installation angle, the optimal AISRs for the 10 kW, 6 kW, and 3 kW inverters were 1.6, 1.8, and 2.08, respectively. Again, the AISRs for the southwest-southeast facade installations were 1.8, 1.9, and 2.17 for the inverters under study. They do not clip the produced energy as much as rooftop systems because their production is more evenly distributed throughout the day, yet they do not achieve as low production costs either. It is pointed out that if the PV self-consumption is optimized by using PV to heat water or batteries as a storage, limitation of the PV generation might not be the correct solution. [ABSTRACT FROM AUTHOR]

Abstract This paper is based on a hybrid PV and fuel cell system designed to meet energy requirements of 100000 customers of Southern California in a sustainable way. Solar roof-top PV system is turning out to be a boon to the mankind with its positive effects of reducing Green House Gas (GHG) emission, lowering stress on conventional coal-fired or natural gas generators and even reducing costs associated with electricity pricing for consumers. However, with increased penetration from the grid tied PV systems, there is an inevitable rise in stress faced by conventional generators in terms of meeting and balancing the energy requirements during early morning and late afternoon hours which requires precise switching and control mechanisms. This paper addresses the ramping issues and offers an integrated solution in the form of fuel cells that can complement the existing PV system during intermittent times of energy production and even by reducing the ramp up and ramp down slopes of power production by conventional generators, in a promising way. [ABSTRACT FROM AUTHOR]

Highlights • A system sizing method is proposed for nearly/net ZEBs under uncertainty. • Response surface models are developed to evaluate performance of each design option. • Number of Monte Carlo simulations is reduced by order(s) of magnitude. • Proposed method robustly sorts out top 1.1% design option in expectation. Abstract Properly treating uncertainty is critical for robust system sizing of nearly/net zero energy buildings (ZEBs). To treat uncertainty, the conventional method conducts Monte Carlo simulations for thousands of possible design options, which inevitably leads to computation load that is heavy or even impossible to handle. In order to reduce the number of Monte Carlo simulations, this study proposes a response-surface-model-based system sizing method. The response surface models of design criteria (i.e., the annual energy match ratio, self-consumption ratio and initial investment) are established based on Monte Carlo simulations for 29 specific design points which are determined by Box-Behnken design. With the response surface models, the overall performances (i.e., the weighted performance of the design criteria) of all design options (i.e., sizing combinations of photovoltaic, wind turbine and electric storage) are evaluated, and the design option with the maximal overall performance is finally selected. Cases studies with 1331 design options have validated the proposed method for 10,000 randomly produced decision scenarios (i.e., users’ preferences to the design criteria). The results show that the established response surface models reasonably predict the design criteria with errors no greater than 3.5% at a cumulative probability of 95%. The proposed method reduces the number of Monte Carlos simulations by 97.8%, and robustly sorts out top 1.1% design options in expectation. With the largely reduced Monte Carlo simulations and high overall performance of the selected design option, the proposed method provides a practical and efficient means for system sizing of nearly/net ZEBs under uncertainty. [ABSTRACT FROM AUTHOR]

Hydrogen is becoming increasingly popular as a clean, secure, and affordable energy source for the future. This study develops an approach for designing a PV–battery–electrolyzer–fuel cell energy system that utilizes hydrogen as a long-term storage medium and battery as a short-term storage medium. The system is designed to supply load demand primarily through direct electricity generation in the summer, and indirect electricity generation through hydrogen in the winter. The sizing of system components is based on the direct electricity and indirect hydrogen demand, with a key input parameter being the load sizing factor, which determines the extent to which hydrogen is used to meet seasonal imbalance. Technical and financial indicators are used to assess the performance of the designed system. Simulation results indicate that the energy system can effectively balance the seasonal variation of renewable generation and load demand with the use of hydrogen. Additionally, guidelines for achieving self-sufficiency and system sustainability for providing enough power in the following years are provided to determine the appropriate component size. The sensitivity analysis indicates that the energy system can achieve self-sufficiency and system sustainability with a proper load sizing factor from a technical perspective. From an economic perspective, the levelized cost of energy is relatively high because of the high costs of hydrogen-related components at this moment. However, it has great economic potential for future self-sufficient energy systems with the maturity of hydrogen technologies. • An approach is proposed to size a PV–battery–electrolyzer–fuel cell energy system. • Hydrogen is considered the long-term energy storage medium. • Techno-economic performance of the energy system is analyzed with a case study. • The introduction of hydrogen increases the reliability of energy supply. • Load sizing factor of <1 is sufficient. [ABSTRACT FROM AUTHOR]

The solar photovoltaic water pumping system (SPVWPS) is increasingly popular in non-electrified population in fulfilling the irrigation and drinking water demand. It can be a potential option than conventional pumps to draw down water in developing countries like India. However, to gain wider acceptance, scientific information and results are needed with the system installation and sizing. In this study, the performance of SPVWPS is investigated with helical rotor pump. The effect of solar radiation and total head on water output of SPVWPS has been analyzed with the optimized PV array configuration. Four pumping head have been analyzed (4 bar, 6 bar, 8 bar and 10 bar). The experiments have been performed for various heads on clear sunny daylight hours in an artificial well at VNIT campus Nagpur (India). The effect of variation of radiation on the performance of pump has also been studied. The best system efficiency is founded for the total head of 10 bar which is suggested for helical rotor submersible pump. Also, for Nagpur (India), the system should be sized as per the irradiance range 400–800 W/m 2 , as more than 60% of the total solar energy falls in this range. [ABSTRACT FROM AUTHOR]

Global climate change has driven many manufacturing organizations to consider renewable energy as an alternative source of power for their operations. However, the instability and unpredictability of renewable energy has made it difficult to design an optimal solution. This is particularly critical for food manufacturing which is constrained by timing and seasonable fluctuations. This paper describes a feasibility study of offsetting grid supplied power by local generation using a roof top photovoltaic system. The study shows that the company can significantly reduce their carbon emitting energy usage by a 100 kW photovoltaic solar system that helps to reduce the annual electricity consumption by 39%. The system sizing methodology has taken into account the load profile of the food manufacturing plant and seasonal solar energy availability with the constrain to consume all solar power immediately.

Afghanistan is a key country between energy surplus areas (Central Asian Republics and Iran) and energy deficit regions (Pakistan and India). It is in a position that can facilitate and launch regional electricity trade for the benefit of the region also derive significant gains for its own economy from energy imports and exports. On the other hand, Afghanistan is endowed with large renewable energy resources (RERs), which it could exploit not only to satisfy its domestic power demand but also to earn significant export revenue. This paper firstly explains the methodology and framework for the power trade and then presents an optimization framework for profit maximization in the short-run trading and cost minimization in the long-run trading. The proposed methodology is applied to a real case between Afghanistan and Pakistan. The objective functions, parameters, variables and constraints are described for both optimization models. System sizing, simulation and optimization are carried out using genetic algorithm (GA) technique. The results in the short-run model represent optimality of about 2654 MW electricity export from Afghanistan to Pakistan during summer. Moreover, results derived from running long-run model depict that by utilizing its RERs such as solar, wind and hydro, Afghanistan can not only meet its power demand but also can export to Pakistan during its deficit periods and gain remarkable energy profits. [ABSTRACT FROM AUTHOR]

In agricultural remote areas where electrical energy is required to supply water pumping plants, photovoltaic modules are considered a good option to generate electricity. The reliability of autonomous Photovoltaic water pumping plants depends essentially on the system components size, which should meet the criteria related to the plant autonomy and the water volume required for irrigation. In this context, this research paper proposes an approach to size the elements of an autonomous photovoltaic system equipped with an energy storage device (a battery bank), and which is used to supply a water-pumping plant with electricity. The proposed approach determines the optimal surface of the photovoltaic modules, the optimal capacity of the battery bank and the volume of the water storage tank. The optimization approach takes into account the monthly average solar radiation, the fulfillment of the water needed for the crops’ irrigation and the number of the days of autonomy. Measured climatic data of 10 ha situated in Northern Tunisia and planted with tomato are used in the optimization process, which is conducted during the tomato vegetative cycle (from March to July). The optimal results achieved for this farm are 101.5 m 2 of photovoltaic modules’ surface, 1680 A h/12 V of the battery bank and 1800 m3 of the volume of the water storage tank. Then, to verify the reliability of the proposed optimization approach, the results of the proposed sizing algorithm are compared with those of a commercial optimization tool named HOMER, which shows better results using the proposed approach. Finally, the economic reliability of the obtained size is studied and compared with systems that include a diesel generator, and a diesel generator- photovoltaic panels, respectively, using climatic and economic parameters in three countries: Tunisia, Spain and Jordan. The economic analysis for these water pumping systems showed that photovoltaic- batteries/Pump system is the optimum solution in the three countries. However, the initial cost of the system can be recuperated faster in Spain than in Tunisia and Jordan due to high prices of the diesel these two countries. [ABSTRACT FROM AUTHOR]

Solar and wind are inexhaustible, abundant, environmentally friendly and freely available renewable energy sources. Integration of these two sources has always been a complex optimization problem which requires efficient planning, designing and control strategies. Many researchers have designed cost effective and efficient hybrid solar-wind energy systems by using various available software tools and optimization algorithms. With the advancement in artificial intelligence methods, various new optimization techniques have been developed in the last few decades. This paper presents state of the art optimization methods applied to hybrid renewable based energy systems. A brief introduction of each technique is presented along with papers published in different reputed journals. This article also reviews different power management, control strategies and multi-objective optimization methods used for hybrid wind-solar systems. A case study is presented to demonstrate the efficacy of some of the algorithms. [ABSTRACT FROM PUBLISHER]

Net-zero energy buildings (NZEBs) are considered as an effective solution to current environmental and energy problems. To achieve expected performance, system sizes in a NZEB must be properly selected. Parameter uncertainties have been proved to have significant impacts on system sizing and need to be systematically considered. Due to complex uncertainty impacts, proper system sizing in a NZEB with multi-criteria performance is always a real challenge. To deal with the challenge, this study presents a genetic algorithm-GA based system sizing method for NZEBs. Taking users’ multi-criteria performance requirements as constraints, the proposed method aims to minimize total system initial costs by selecting proper sizes of five different systems under uncertainties. The five systems include an air-conditioning system, photovoltaic panels, wind turbines, a thermal energy storage system and an electrical energy storage system. The performance requirements come from three diverse criteria which are zero energy, thermal comfort and grid independence. Using real weather data of 20 years in Hong Kong, the case studies demonstrate the effectiveness of the proposed method in selecting proper system sizes corresponding to user specified performance requirements. In addition, the results indicate conventional descriptions of parameter uncertainties need to be improved for better system sizing of NZEBs. [ABSTRACT FROM AUTHOR]

• An overview of PVB system study from modelling, simulation, sizing and control strategy is conducted. • Two main research focuses lie in model predictive control (MPC) and demand side management (DSM). • Large system scale, various market participants and multi-energy flows are PVB system study research major trends. • Perspectives in PVB research including DC distribution system and carbon trading integration are presented. Due to the target of carbon neutrality and the current energy crisis in the world, green, flexible and low-cost distributed photovoltaic power generation is a promising trend. With battery energy storage to cushion the fluctuating and intermittent photovoltaic (PV) output, the photovoltaic battery (PVB) system has been getting increasing attention. This study is conducted to comprehensively review the PVB system studies with experimental and simulation studies, concerning mathematical modelling, system simulation, evaluation, capacity and operation strategy optimization. The system profitability, storage system choice and grid influence are also discussed, with the multi-objective optimization in large-scale systems with various participants expected as the future trend. In addition, several highlights of this topic are discussed in detail, including model predictive control, demand-side management, community energy storage system, peer-to-peer energy market scheme and mutual impacts on grid and system, emphasizing system flexibility, optimization complexity, large-scale simulation and the utility grid influences. Furthermore, some challenges and perspectives for future research are presented, with respect to DC distribution system revolution, large-scale vehicle to grid designs and impacts, multi-energy network operation and participation in the carbon transaction market. It is expected that this study could provide useful references and suggestions for researchers in this field of system design and power management of distributed solar PV. [ABSTRACT FROM AUTHOR]

Uncertainties have significant impacts on system sizing in net zero energy building (NZEB) clusters and they have to be well considered. Through Monte Carlo simulation and statistical analysis, the impacts of three typical types of parameter uncertainties have been investigated in the study. Considering the uncertainty impacts, this study aims to compare the multi-criteria performance of two design approaches for system sizing of a NZEB cluster. The first one is the conventional separated design in which dedicated systems are separately designed in individual buildings. The second one is the integrated design in which integrated systems are designed to provide services to all buildings. The study results show that the integrated design approach can achieve significant system size reductions and large initial cost savings as compared with the conventional separated design. The initial costs of the air-conditioning, PV and wind turbine systems can be reduced by 14.4%, 13.7% and 11.8% respectively. The integrated design also achieves improved grid friendliness and equivalently good indoor thermal comfort in comparison with the conventional separated design. With such improved performance, the integrated design should replace the conventional separated design for system sizing in NZEB clusters as uncertainties considered. [ABSTRACT FROM AUTHOR]

Off-grid renewable systems can play a pivotal role in the process of rural electrification, thus promoting local development. Moreover, scientific literature is increasingly addressing this issue through the concept of sustainability and appropriate technologies. With regards to this topic, we present a sizing methodology which better relates the results and the sizing process itself to the local context. Specifically, we address the research area of sizing methodologies for off-grid PV systems. Typically, the Loss of Load Probability (LLP) is a key parameter in these methodologies, but is difficult to set as regards the specific context. The proposed methodology employs the concept of Levelized Cost of Supplied and Lost Energy, it is based on the estimate of an economic Value of Lost Load, and eventually, the LLP results to be an output of the process. Therefore, the methodology uses only data characterizing the local situation and results better fit with population conditions. We also propose a simple approach to compute the Value of Lost Load and we apply the methodology for a rural area of Uganda. The results show that the methodology identifies a reliable system which supplies electricity with a fair cost while minimizing the energy bill of the consumers. [ABSTRACT FROM AUTHOR]