Sizing Of System Research Articles

Pre-sizing online tool for photovoltaic water pumping system: development, testing, validation, and evaluation

Renewable energy has become increasingly popular worldwide, and solar energy is one of the most sustainable and widely used forms of renewable energy. However, the lack of precision in system sizing often leads to oversizing and significant financial waste. To address this issue, this paper presents the development, testing, validation, and evaluation of an online educational/industrial standard-based tool for optimizing photovoltaic water pumping systems (PVWPSs). The proposed tool considers statistics on solar irradiance, average temperature, and necessary solar panel specifications to aid in calculating the peak power required to meet demand. Using MATLAB software, the tool enables the sizing of a PVWPS for either centrifugal or submersible pumps, including complete PV sizing for on-grid or off-grid systems. The tool also demonstrates the impact of ignoring temperature, sun irradiation, and pipeline losses on the sizing technique. Results indicate that significant temperature changes can negatively impact sizing, requiring further adjustments. Finally, a questionnaire was administered to various user segments to evaluate the tool's efficiency, yielding satisfactory results. This paper presents a valuable tool for optimizing PVWPSs, enabling more precise and efficient system sizing, and reducing financial waste.

Physical properties and mass models of Deglet Noor and Arichti semi-dry Algerian date fruits: A comparative study.

For thousands of years, date fruit (Phoenix dactylifera L.) has been a popular diet in arid and semi-arid locations. It has religious importance for Muslims and is especially important during the holy month of Ramadan. The global output of date fruits has been continuously expanding, with Arab nations accounting for a sizable portion. The emphasis of this research is on two popular semi-dry Algerian date fruit types, Deglet Noor and Arechti, which are grown in the Ziban region. These fruits' physical parameters, such as size, sphericity, surface area, volumes, and density, were determined. The goal of this study was to create a mass model based on these physical attributes to help in the grading and sorting of date fruits. Fruit mass was shown to be closely connected to linear dimensions, arithmetic and geometric mean diameters, surface area, and volumes. Correlations between mass and physical attributes were established using a variety of mathematical models, including linear, quadratic, S-curve, and power models. The results demonstrated the applicability of specific factors for mass modeling, offering useful insights for the development of system sizing and conservation. With good correlation, multivariate data analysis was employed to correctly estimate the mass of both kinds. This research advances our understanding of the physical features of Algerian date fruits and their connection to mass, allowing for better handling, sorting, and packing processes in the worldwide date market.

Optimal sizing and optimization of financial cost for EVs using SPOA-RBFNN technique

This study proposes a hybrid technique for optimal sizing and cost optimization of hybrid energy storage systems (HESS) integrated into electric vehicles (EVs). The proposed technique, SPOA-RBFNN, combines a student psychology-based optimization algorithm (SPOA) and a radial-basis function neural network (RBFNN). The study aims to minimize the overall cost of the HESS by evaluating two design variables: the super-capacitor (SC) and battery pack size. SPOA is employed to optimize the hybrid HESS design variables, ensuring efficient exploration of solution spaces. The RBFNN method is then used to predict the relationship between these design variables and the overall cost of the HESS in electric vehicles. The results show that the proposed technique is more effective than existing techniques, with an efficiency of 97.99039% compared to 82.137% for GA and 77.26589% for particle swarm optimization (PSO). This work offers a comprehensive and innovative approach to optimizing HESS sizing in EVs, connecting the gap between performance optimization and financial cost analysis.

Design Optimisation Approach of an Outer Rotor Multiphase PM Actuator for Multirotor Aerial Vehicle Applications

The electric urban air mobility sector has gained significant attraction in public debates, particularly with the proliferation of announcements demonstrating new aerial vehicles and the infrastructure that goes with them. In this context, the development of new methodologies for the design and sizing of actuation systems, ensuring high performances of these aerial vehicles, remains an important task in this process. This will allow for better integration within this transport sector. In this paper, a robust design optimisation approach of multiphase fault-tolerant (FT) outer rotor (OR) permanent magnets (PM) for multirotor aerial vehicle applications is proposed. In order to show the effectiveness and the robustness of the proposed design methodology, the number of stator winding phases, with a fractional slot concentrated winding (FSCW) configuration, as well as the PM configuration are considered as variables. Thus, four cases for the number of phases are considered, namely 3, 5, 6 and 7 phases, where for each number of phases case, the PM takes 3 configurations, namely surface PM, interior V-shape PM and interior spoke PM. First, a pre-sizing step is carried out, consisting of selecting the optimal combinations slot/pole, designing the multiphase FSCW layout, and estimating the electric motor (EM) geometry using analytical computations to obtain a preliminary validation of the design specifications. Second, constrained multiobjective optimisation is considered in order to optimise the EM performances, such as motor efficiency and weight, under constraints where the FEMM/Matlab based Finite Element Analysis (FEA) tool is used to perform this optimisation. Finally, results analysis and performance comparisons of different EM configurations are carried out in order to assess the design parameters, such as phases number, PM position, and harmonic currents in the EM design and consequently to select the best configuration for the considered application.

Integrating Firefly and Crow Algorithms for the Resilient Sizing and Siting of Renewable Distributed Generation Systems under Faulty Scenarios

This study aimed to optimize the sizing and allocation of renewable distributed generation (RDG) systems, with a focus on renewable sources, under N-1 faulty line conditions. The IEEE 30-bus power system benchmark served as a case study for us to analyze and enhance the reliability and quality of the power system in the presence of faults. The firefly algorithm (FFA) combined with the crow search (CS) optimizer was used to achieve optimal RDG sizing and allocation through solving the optimal power flow (OPF) under the most severe N-1 faulty line. The reason for hybridization lies in leveraging the global search capabilities of the CS optimizer for the sizing and allocation of RDGs and the local search proficiency of the FFA for OPF. Two severe N-1 faulty conditions—F27-29 and F27-30—were separately applied to the IEEE 30-bus distribution system. The most severe N-1 faulty line of these two faulty lines was F27-30, based on a severity ranking index including both the voltage deviation index and the overloading index. Three candidate buses, namely 27, 29, and 30, were considered in the optimization process. Our methodology incorporated techno-economic multi-objectives, encompassing overall costs, power losses, and voltage deviation. The optimizer can eliminate the impractical buses/solutions automatically while remaining the practical one. The results revealed that optimal RDG allocation at bus 30 effectively alleviated line overloading, ensuring compliance with the line flow limit, reducing costs, and enhancing voltage profiles, thereby improving system performance under N-1 faulty conditions compared to the equivalent case without RDGs.

Optimum sizing of hybrid renewable power systems for on-site hydrogen refuelling stations: Case studies from Türkiye and Spain

One of the main barriers to the adoption of fuel cell vehicles (FCEVs) is the limited availability of hydrogen refuelling stations (HRSs). The presence of these stations is crucial in facilitating the provision of fuel for FCEVs, which rely on hydrogen as a source of power generation. Renewable energy sources offer significant advantages for hydrogen production at these stations, as they are environmentally friendly and can reduce costs. In this study, it is provided a techno-economic analysis of an on-site hydrogen refuelling station powered by a hybrid renewable energy generation system using HOMER software in Niğde, Türkiye, and Zaragoza, Spain. Three different power system scenarios were evaluated to refuel 24 vehicles per day for each region throughout the year. The results of the analysis showed that the most optimal system architecture for Niğde was with a solar panel power generation system, with a levelized cost of hydrogen (LCOH) of 6.15 $/kg and the net present cost (NPC) of $6,832,393. The most optimal system architecture for Zaragoza was a wind turbine-photovoltaic panel power generation system, with an LCOH of 5.83 $/kg and NPC of $6,499,723. The annual amount of CO2 emissions avoided by using renewable resources in hydrogen production was calculated as 2,673,453 kg for Niğde and 2,366,573 kg for Zaragoza. The study also found that the cost of hydrogen production increases with decreasing the HRS production capacity. The use of renewable energy generation systems for hydrogen production will enable countries to achieve net-zero emission targets and reduce the need to import fossil fuels to meet energy demands in the transportation sector. The present study makes several contributions towards the achievement of the United Nations Sustainable Development Goals (3, 7, 11, and 13) and has the potential to facilitate the rapid adoption of FCEVs.

Bi-level optimal sizing, siting and operation of utility-scale multi-energy storage system to reduce power losses with peer-to-peer trading in an electricity/heat/gas integrated network

Adopting multi-carrier energy systems (MES) is vital for a sustainable and eco-friendly energy future. MES integration connects diverse energy networks, prompting the deployment of large-scale multi-energy storage systems (MESS) to support interconnected multi-energy distribution systems. This paper proposes a bi-level mixed-integer linear programming (MILP) model to optimise MESS sizing and location in a peer-to-peer (P2P) supported integrated energy distribution network with energy hubs. The MESS, operated by an energy storage system operator (ESSO), stores various energy carriers and exchanges energy with electricity, gas, and heating networks, enabling cross-product arbitrage in P2P and day-ahead markets. The bi-level methodology aims to minimise costs (maximise profit) for ESSO and energy hubs at the upper-level while reducing network power losses at the lower level. By applying Karush-Kuhn-Tucker (KKT) optimality conditions and the big-M approach, the bi-level problem transforms into a single-level MILP. Case studies on an integrated energy network based on the 16-bus 33 kV UK generic distribution system validate the proposed model and methodology, demonstrating its effectiveness in integrated energy networks.

Modified Harris Hawk algorithm-based optimal photovoltaics for Voltage Stability and Load Flow Analysis

ABSTRACT In the distribution system, proper placement of distributed generation (DG) is still a very challenging issue for getting their maximum potential benefits. Power system stability should be determined through load modeling, hybrid energy storage system (HESS), and photovoltaics (PV) modeling. This paper proposed the optimal sizing and location of photovoltaic using the Modified Harris Hawk Optimization (MHHO) algorithm. The energy generated from the photovoltaic (PV) is stored in the HESS, where the energy’s charging and discharging from the storage unit is framed with a reduced power loss (active and reactive power). The optimal sizing and placement of the PV system will provide better voltage stability. The Modified Harris Hawk Optimization Algorithm (MHHO) frames the system’s voltage stability. The Newton-Raphson load flow method is used to analyze the loading in the power system. The IEEE 33 and 69 bus systems are used to analyze the load flow to the consumers, thus analyzing the power system’s dynamic performance. The performance and voltage stability of the presented model are compared with the existing optimization techniques, which include the Firefly Algorithm (FA), Crow Search Optimization (CSO), Particle Swarm Optimization (PSO), Analytical PSO (APSO), Improved Cayote Optimization Algorithm (COA) and Whale optimization algorithm (WOA) through the MATLAB/Simulink platform.

Optimal sizing of a hybrid microgrid system using solar, wind, diesel, and battery energy storage to alleviate energy poverty in a rural area of Biskra, Algeria

This paper presents a model for designing a stand-alone hybrid system consisting of photovoltaic sources, wind turbines, a storage system, and a diesel generator. The aim is to determine the optimal size to reduce the cost of electricity and ensure the provision of electricity at lower and more reliable prices for isolated rural areas. Three scenarios for five, fifteen, and twenty rural homes were sized and analyzed using actual weather data in the rural and pastoral area of Biskra, Algeria. The SFS and SOS algorithms were used for the first time, in addition to the commonly used PSO algorithm, to compare the performance of each algorithm and achieve the goal of meeting all energy load requirements at the lowest cost. Three factors have been taken into consideration within the proposed objective function, which are the levelized cost of energy (LCOE), loss of power supply probability LPSP, and the amount of energy consumed by the dummy load. The results of the scenarios showed that the SFS algorithm outperformed the other algorithms, with the lowest cost of electricity for each of the mentioned scenarios. The levelized cost of energy (LCOE), respectively, was 0.09138 $/kWh, 0.16588 $/kWh, and 0.24862 $/kWh.

الحجم الأمثل للنظام الهجين المستقل والمتجدد على أساس التكاليف باستخدام تقنية Gray Wolf Optimization

Ensuring low-cost and highly reliable electricity generation while meeting the demand load poses a significant challenge. Power plants operate continuously to produce power, with the Programmable Logic Controller (PLC) control system playing a crucial role in managing all the equipment. Power deficiencies in the PLC rooms can lead to equipment disturbances and potential damage to the plant. To address this problem and utilize the abundant solar energy in Libya, this study introduces the optimal sizing of an autonomous hybrid storage system using an optimization method. The Net Present Costs (NPC), Loss Power Supply Probability (LPSP), and Levelized Cost of Energy (LCOE) are employed to extract a suitable function database. The proposed system generates 7 kW of power to meet demand and is implemented in MATLAB. The Grey Wolf Optimization (GWO) method is applied to determine the optimal number of PV panels and BESS capacity for the autonomous hybrid system. The optimal solution obtained through GWO is determined to be 40 PV panels and a 60Ah BESS capacity.

Optimal siting and sizing of custom power system and smart parking lot in the active distribution network

AbstractNon‐linear loads, electrical vehicles (EVs) and power electronics are the sources of harmonic generation in the power system. Harmonics are the reason for the disturbance in the technical constraints and quality of the power system. These disadvantages are formed in the current and the voltage of the system branches and buses. To reduce these harmonics, active and passive power filters are used. Since active power filters (APFs) include electronic power switching devices, they are used to eliminate or reduce current or voltage harmonics. To properly reduce these harmonics and supply consumer demand, private investors (PIs) are considered to enhance the power quality, by investing in the APF units and the distribution network operator (DNO) coordinating and feeding the EVs, by equipping the network with smart parking lots. Total harmonic distortion, bus voltage profile, active power loss and energy not supplied (ENS) are considered problem attributes. Using techniques for order of preference by similarity to the ideal solution (TOPSIS), it is determined how the addition of photovoltaic (PV), energy storage system, and batteries affects the ranking of attributes from the perspectives of both DNO and PI. The best solutions are obtained in the first stage using a genetic algorithm (GA), and the attributes have been prioritized from a utility perspective in the second stage by TOPSIS. To verify the performance of GA and TOPSIS, all of the obtained results are compared with the other algorithms. As seen clearly, active, reactive power loss and ENS in scenarios with the participation PV are reduced. Furthermore, comparing the results of different algorithms confirms the efficiency of GA and TOPSIS.

Reduction of electricity cost in public administration through a distributed generation strategy

The use of distributed generation as an alternative to reduce energy costs in the city hall of Vitória, capital of state of Espirito Santo in Brazil, is proposed in this paper. Photovoltaic solar energy was considered and the system sizing was carried out based on the total cost of eletricity in 2016 (available at the City’s Transparency Website), resulting in a system with a total power of 78 MW. The financing scenarios were analyzed for acquisition of the system scaled with a horizon of 25 years. The results of the economic-financial analysis indicate that the investment is advantageous for the municipality and can bring great returns to the society

Efficiency Comparison of Grid Side Converters for DC Distribution Systems

This paper aims to study the energy losses in Grid Side Converters (GSCs) used for grid connection of DC residential distribution systems, including renewables and storage. Two different electrical architectures have been considered, the former using an H-bridge as GSC and the latter a PFC active rectifier in association with a storage system. An observation time of one year has been fixed. The analysis is based on the same amount of energy generated by renewables and load demand, in both cases. A detailed formulation of the power losses in each component of the power converter is given. A comparison of the energy lost yearly in both the GSCs is presented, considering different sizing of the storage system.

Probabilistic energy storage sizing for reducing wind power forecast uncertainty

A novel method is proposed for designing an energy storage system (ESS) which is dedicated to reducing the uncertainty of the short term wind power forecast. The investigation focuses on the statistical behaviour of the forecast error and the state of charge (SOC) of the ESS. This approach gives an insight into the influence of the forecast conditions on the distribution of SOC. With this knowledge, an optimised sizing of the ESS can be done with a well defined uncertainty limit. One-year power output data measurements and two types for forecast were used for this study. In addition, different forecast quality degrees are simulated based on the persistence approach. With the forecast data, empirical probability density functions (pdf's) of the SOC are generated which is the base of the proposed method. This approach can lead to a considerable reduction of the ESS and provides important information about the unserved energy. This unserved energy is the remaining forecast error or uncertainty. As a consequence, the proposed probabilistic method permits the sizing of the energy storage system as a function of the desired remaining forecast uncertainty.

Impact of future climate change on energy consumption in residential buildings: A case study for representative cities in Japan

This study examines the impact of future climate change on energy consumption in residential buildings in Japan, taking into account both the current and future typical meteorological year (TMY) database. TMY data is widely used in the building sector for energy performance assessments, system sizing, and optimization. To investigate the impact of current and future TMY databases on energy consumption of buildings, the study predicts the cooling and heating loads of residential buildings in four cities of Japan under the current (2020 ver.) and future (2086 ver.) TMY databases. Results show that the use of future TMY database leads to significant changes in air-conditioning heat loads of residential buildings in Japan. It finds that the annual cooling load in residential buildings of four cites of Japan increases by approximately 12% for Tokyo, approximately 9% for Toyohashi, approximately 8% for Osaka, and approximately 7% for Nagoya, respectively, however the annual heating load decreases by approximately 8% for Tokyo, approximately 9% for Toyohashi, approximately 6% for Osaka, and approximately 5% for Nagoya, respectively, compared to the current TMY database. This finding suggests that climate change will have a significant impact on future building energy consumption, and proposes energy-efficient building design as a solution to mitigate the impact of climate change on building energy consumption.

Sizing and Simulation of a Photovoltaic Hybrid Energy System and Generator for the Electricity Supply of the Residence of the Governor of Mamou, Guinea

Sizing and Simulation of a Photovoltaic Hybrid Energy System and Generator for the Electricity Supply of the Residence of the Governor of Mamou, Guinea

Optimal design and sizing of a hybrid energy system for water pumping applications

AbstractOne of the ways to increase the participation and penetration of renewable energy resources is to bring down the cost of these abundant resources for easy implementation and affordability. In this paper, a generalized reduced gradient (GRG) non‐linear optimization algorithm is implemented to solve a tri‐objective optimal design and sizing of a low‐cost hybrid mix consisting of a photovoltaic (PV) power plant, biomass power plant (BPP), and battery energy system for water pumping load applications in the University of Johannesburg, South Africa considering four different hybrids of biomass‐battery, PV‐battery, PV‐biomass, and PV‐biomass‐battery. The optimization model considers available energy and battery state of charge while minimizing least cost of energy (LCOE), carbon dioxide emission (tCO2eq), and loss of power supply probability (LPSP) including carbon tax incentive and penalty. The results when compared against particle swarm optimization (PSO) show the superiority of GRG over PSO with an optimal combination of PV‐biomass‐battery mix with optimal size of the PV power plant as 360.50 kW, the BPP 181.08 kW, and the battery size of 6,553.60 kWh giving a minimal optimal LCOE, CO2 emission and LPSP of 0.018 $/kWhr (with carbon tax), and 0.016 $/kWhr (without carbon tax), 28,067.73tCO2eq tCO2eq, and 1.7%, respectively. These values give a competitive advantage compared to the unit cost and values of CO2 emission and LPSP currently in the literature.

Solar Energy Systems Course for Energy Engineering Students in the Context of the European Higher Education Area (EHEA)

The Bologna Process is a voluntary intergovernmental European cooperation initiative that led to the creation of the named European Higher Education Area (EHEA). EHEA was formed to promote mobility, increase academic recognition and attract students and staff from around the world to Europe. In this framework, since 2009, the Barcelona College of Industrial Engineering (Escuela Universitaria de Ingeniería Técnica Industrial de Barcelona – EUETIB) of the Technical University of Catalonia – BarcelonaTech (UPC) is offering the 4-year Bachelor Degree in Energy Engineering since 2009 with a total number of ECTS credits of 240. Current article deals with the inclusion of the sizing and design of solar energy systems in the context of this degree. In particular, and although this topic was eventually abandoned in the initial degree curriculum, the paper deals with the development of a 3rd-year course, Energy Integration, that focuses on this topic.

On sizing of battery energy storage systems for PV plants power smoothing

The high variability of solar irradiance causes fluctuations in the generation of photovoltaic (PV) power plants. This characteristic affects power system operation, thus, strategies are necessary to mitigate the intermittent characteristics of PV power plants. Several countries adopt grid codes incorporating ramp rate (RR) limitations for PV power injection into the grid, also known as power smoothing control. In this sense, battery energy storage systems (BESS) with coordinated RR control algorithms are commonly applied to mitigate current fluctuations from the PV system to the grid. Therefore, studies on the effect of local solar irradiance on BESS requirements for PV power smoothing applications are very important. It is also worth highlighting that in the literature there is a gap in the evaluation of aspects of battery lifetime, BESS volume, price and BESS oversizing for selecting an ideal battery model, among a catalog of batteries, constituting an industrial concern. Therefore, this work presents a detailed BESS sizing methodology, evaluating aspects of the energy requirements, power, and discharging rate (C-rate), based on the mission profile (featuring a customized solution for each project). In addition, the effect of the battery temperature control on the BESS sizing is evaluated. The case study is based on a 1 MW PV system, assessed using a one-year mission profile of solar irradiance and ambient temperature from Goiânia-Brazil. The PV plant is connected to a 440 V grid associated with a BESS that mitigates oscillations of 10%/min. The BESS sizing is evaluated in terms of BESS volume, lifetime, and oversizing factor for power and energy. The proposed methodology reduces the BESS volume by 57.14% in relation to the traditional BESS design of literature.

Sizing and cost analysis for integrated renewable energy system in a study area

The renewable energy sources such as micro hydro, biomass, wind, solar photovoltaics can provide clean and sustainable electricity, as a result, many of sources are already proving cost-competitive contributing about 2% of the total electricity supply of the country. However, one of the issues limiting their greater penetration is done to its intermittent and seasonal availability for energy production. The availability of renewable power depends upon the resources potential and size of the system. The sizing for integrated renewable energy systems (IRES) depends on the uses of the system (load on the system) and the tariffs available from the local utility. In this paper, the sizing and cost analysis of MHP, biomass, wind and SPV system has been under taken.