Solar Insolation Data Research Articles

On the Performance Limits of Agrivoltaics—From Thermodynamic to Geo‐Meteorological Considerations

As the world strives toward its net‐zero targets, innovative solutions are required to reduce carbon emissions across all industrial sectors. One approach that can reduce emissions from food production is agrivoltaics—photovoltaic devices that enable the dual‐use of land for both agricultural and electrical power‐generating purposes. Optimizing agrivoltaics presents a complex systems‐level challenge requiring a balance between maximizing crop yields and on‐site power generation. This balance necessitates careful consideration of optics (light absorption, reflection, and transmission), thermodynamics, and the efficiency at which light is converted into electricity. Herein, real‐world solar insolation and temperature data are used in combination with a comprehensive device‐level model to determine the annual power generation of agrivoltaics based on different photovoltaic material choices. It is found that organic semiconductor‐based photovoltaics integrated as semitransparent elements of protected cropping environments (advanced greenhouses) have comparable performance to state‐of‐the‐art, inorganic semiconductor‐based photovoltaics like silicon. The results provide a solid technical basis for building full, systems‐level, technoeconomic models that account for crop and location requirements, starting from the undeniable standpoint of thermodynamics and electro‐optical physics.

Investigation of the Influence of Inner Geometries of the Receiver Tube of a Parabolic Trough Collector System Used for Water Heating

Solar collectors are devices that help to harvest solar thermal radiation and convert into other forms of energy. Because of its low fabrication cost and simple design, the Parabolic Trough Collector (PTC) is one of the finest alternatives for medium-temperature (i.e., in 80°𝐶𝐶-250°𝐶𝐶 range) needs among all types of concentrated solar collectors. The absorber tube or the receiver tube is one of the main critical components of a PTC. Thermal radiation of the sun falling onto a parabolic reflector is reflected to its focal line where the receiver tube is placed. Therefore, the performance of a PTC system significantly depends on Receiver Geometries (RGs). A locally developed PTC system with a new and accurate tracking system was designed and fabricated in the current study and steam generation inside the receiver was considered in the performance analysis. The experimental analysis was performed using seven different RGs. The experiments were carried out by measuring generated steam every 10 minutes for all the RGs, and simultaneously, solar insolation data was taken by a domestic solar Photovoltaic (PV) system with a capacity of 5 kW. The steam generation data was taken only when the power output of the reference solar PV system was ≥ 4kW. Having tested seven different RGs, the researchers were able to improve the steam generation to a maximum of 10.0% compared to the reference geometry using direct experimental data. This was 8.1% in accordance with the statistical approach via multiple linear regression model. A three-dimensional mathematical model for two-phase flow was formulated for a closed domain. Restricting this model into twodimensional geometry, the steam generation process was simulated as a TPF problem using ANSYS Fluent software. The volume fraction profiles clearly show the phase transition, which leads to evaporation and condensation inside the tube.

Simulation modeling of a power supply system taking into account the stochastic nature of energy generation and consumption processes

This paper presents the calculation of parameters and simulation modeling of the power supply system based on solar panels, taking into account the stochastic nature of the processes of energy generation and consumption. Through simulation in MATLAB® Simulink, the performance of the power supply system under the change of solar insolation and load power was evaluated. The method of controlling a bidirectional converter based on the calculation of the difference in Shannon entropy of energy generation and consumption flows is described. This method allows for increasing the efficiency of energy use in the system by reducing the difference between the entropy values at the input and output of the system. It also allows for reducing the duration of time intervals when the energy storage in the system is uncontrollable while being fully charged or fully discharged. Modeling of electrical processes in the power supply system was carried out with the implementing the control either considering the entropy difference or without it. To evaluate the impact of the accuracy of determining the entropy values on the modeling results, the entropy for different interval durations was calculated. The results of modeling the power supply system were analyzed using solar insolation and load power data with a 1-minute discreteness.

THERMODYNAMIC AND ECONOMIC ANALYSIS OF A BIOGAS -FUELED MICRO GAS TURBINE WITH COMPRESSOR PHOTOVOLTAIC DRIVE

The increase in global and Brazilian energy demand plus environmental concern due to pollutant emissions are motivating investigation and development of sustainable energy sources and the interaction between them. In this context, electricity generation through solar and solid urban waste energy harnessing has become an effective option for Brazilian energy matrix diversification. Therefore, in order to ratify this trend, a thermodynamic analysis of a 200 kWe micro gas turbine using biogas as fuel and photovoltaic panels to drive compressor shaft is presented in this paper. In terms of methodology, Engineering Equation Solver (EES) Demo was used to run a classic steady state thermodynamic model and a parametric analysis to evaluate MGT performance with a PV system integrated in order to assess specific fuel consumption reduction (SFC) at Belo Horizonte, Minas Gerais, Brazil, operation. Radiasol 2 was the software used to acquire solar insolation data over the year. The fuel economy occurs since power produced in turbine does not need to be discounted to drive compressor shaft during periods when solar insolation is present or when energy generation during the day is sufficient to be credited as Brazilian legislation allows grid integrated systems. In cases that solar energy is not enough or absent, a transmission mechanism similar to a clutch should be considered as well as proposed in other studies to guarantee uninterrupted system operation. Futhermore, an economic analysis was performed to evaluate kWh cost for conventional and hybrid systems. Interest rate, inflation, construction period and amortization period are important parameters taken into account to calculated annuity factor that must be evaluated to predict energy cost. The thermodynamic results showed that SFC=0,718 kg/kWh for conventional operation and SFC=0,266 kg/kWh for hybrid operation for the best operating compressor pressures ratio. The economic results showed that payback time for MGT and MGT with compressor photovoltaic drive are lower than lifetime systems, and hybrid MGT electricity cost is lower when compared to paid ones nowadays.

Optimal sizing of grid‐connected rooftop photovoltaic and battery energy storage for houses with electric vehicle

AbstractA practical optimal sizing model is developed for grid‐connected rooftop solar photovoltaic (PV) and battery energy storage (BES) of homes with electric vehicle (EV) to minimise the net present cost of electricity. Two system configurations, (1) PV‐EV and (2) PV‐BES‐EV, are investigated for optimal sizing of PV and BES by creating new rule‐based home energy management systems. The uncertainties of EV availability (arrival and departure times) and its initial state of charge, when arrives home, are incorporated using stochastic functions. The effect of popular EV models in the market is investigated on the optimal sizing and electricity cost of the customers. Several sensitivity analyses are adopted based on variations in the grid constrains, retail price and feed in tariff. Uncertainty analysis is provided based on the variations of insolation, temperature, and load to approve the optimal results of the developed model. A practical guideline is presented for residential customers in a typical grid‐connected household to select the optimal capacity of PV or PV‐BES system considering the model of EV. While the proposed optimization model is general and can be used for various case studies, real annual data of solar insolation, temperature, household's load, electricity prices, as well as PV and BES market data are used for an Australian case study. The developed optimal sizing model is also applied to residential households in different Australian States.

A Design Tool for Solar Thermal Remediation Using Borehole Heat Exchangers.

Low temperature heating of the subsurface (increases of about 5-20 °C) can substantially increase rates of biotic and abiotic destruction of dissolved contaminants such as chlorinated solvents. Low-temperature heating can be sustainably and cost-effectively achieved using solar thermal collectors coupled with closed-loop borehole heat exchangers. This technology has been implemented at several sites in the United States and abroad with favorable results. The design of a solar thermal remediation system requires a quantitative understanding of heat transfer from the array of borehole heat exchangers. We present an easy-to-use design tool that is based on a transient three-dimensional analytical heat transfer solution and is programmed in Visual Basic in Excel. This tool can be used to quickly explore the effect of design variables on the forecast temperature field. Typical design variables would include the site-specific average and monthly solar insolation data, solar collector configuration, borehole heat exchanger geometry and spacing, and the effects of environmental variables such as groundwater velocity, background subsurface temperature, and thermal conductivity. The design tool has been verified by comparisons with the TOUGH2 multiphase heat transfer code for a three-dimensional multi-heater system with seasonally variable thermal power rates. The code has been validated by comparisons to observed temperatures measured at a solar thermal field remediation application at a site in Colorado.

Sizing of Rooftop PV Array and Community-Run Battery Storage for an Energy Cooperative in Prosumer Cluster

A standalone system can address the problem of uncovered electricity from the grid. The cost of energy storage for installing renewable energy systems is one of the issues of such a system. This paper introduces and investigates the optimal capacity of a novel energy cooperative system with prosumer clusters and a community battery bank as typical energy storage. The system’s function is formulated to minimize the investor’s annual expenditure. The proposed energy cooperative system uses actual annual solar insolation data and the electric load demand of houses in the optimization process. The model, as mentioned above, is applied to two system configurations – energy cooperative without and with Prosumer to Prosumer (P2P) energy sharing. The reliability factor Loss of Power Supply Probability (LPSP) from the Cooperative Energy Sharing algorithm is taken as a constraint in the formulation. The comparison of the two configurations brings out the importance of P2P energy sharing in a standalone Energy Cooperative system. Particle Swarm Optimization (PSO) algorithm is used to achieve this optimization. The PSO results show that the proposed Energy Cooperative configurations are promising to facilitate the system’s reliability.

Techno-Economic Feasibility of a Solar-Wind-Fuel Cell Energy System in Duqm, Oman

Duqm is located in the Al Wasta Governorate in Oman and is currently fed by 10 diesel generators with a total capacity of around 76 MW and other rental power sources with a size of 18 MW. To make the electric power supply come completely from renewables, one novel solution is to replace the diesel with hydrogen. The extra energy coming from the PV-wind system can be utilized to produce green hydrogen that will be utilized by the fuel cell. Measured data of solar insolation, hourly wind speeds, and hourly load consumption are used in the proposed system. Finding an ideal configuration that can match the load demand and be suitable from an economic and environmental point of view was the main objective of this research. The Hybrid Optimization Model for Multiple Energy Resources (HOMER Pro) microgrid software was used to evaluate the technical and financial performance. The findings demonstrated that the suggested hybrid system (PV-wind-fuel cell) will remove CO2 emissions at a cost of energy (COE) of USD 0.436/kWh and will reduce noise. With a total CO2 emission of 205,676,830 kg/year, the levelized cost of energy for the current system is USD 0.196/kWh. The levelized cost for the diesel system will rise to USD 0.243/kWh when taking 100 US dollars per ton of CO2 into account. Due to system advantages, the results showed that using solar, wind, and fuel cells is the most practical and cost-effective technique. The results of this research illustrated the feasibility and effectiveness of utilizing wind and solar resources for both hydrogen and energy production and also suggested that hydrogen is a more cost-effective long-term energy storage option than batteries.

Multiobjective Long-Period Optimal Planning Model for a Grid-Connected Renewable-Battery System

This article develops a practical framework for the multiobjective optimal planning of a grid-connected renewable-battery system considering a long-period operation. The capacities of wind turbine, solar photovoltaic (PV), and battery storage are optimized by minimizing three objective functions: cost of electricity (COE), grid dependence (GD), and total curtailed energy (TCE). A new rule-based energy management is developed for the long-period operation, where: 1) the capacity degradations of PV and battery are applied; 2) purchase and sell electricity prices are updated for each year using interest and escalation rates; and 3) the salvation value of the components is considered to achieve a realistic economic analysis of the planning problem. The developed multiobjective optimal planning model is examined using the long-period (ten years) real data of wind speed, solar insolation, ambient temperature, and load consumption for a grid-connected household in Australia. It is found that a household with the minimum GD (0.008%) results in a COE of 116 ¢/kWh with a TCE of 100 MWh in ten years. The proposed optimal planning framework based on the long-period operation is compared with the short-period operation.

Energy and latency aware mobile task assignment for green cloudlets

Edge computing places cloudlets with high computational capabilities near mobile devices to reduce the latency and network congestion encountered in cloud server-based task offloading. However, many cloudlets are required in such an edge computing network, leading to a tremendous increase in carbon emissions of computing networks globally. This increase in carbon emission envisages the need to employ green energy resources to power these cloudlets. This need has led to the concept of Green Cloudlet Networks (GCNs). But GCNs must deal with the problem of the unpredictability of green energy available to them while optimizing the performance (in terms of latency) delivered to the mobile user. This paper proposes a novel task-assignment called Green Energy and Latency Aware Task Assignment (Ge-LATA) for GCNs to address this issue. The primary aim of Ge-LATA is to optimize the latency and the green energy consumed in processing the offloaded tasks from the mobile devices. In this GCN, the cloudlets are connected in a network to process the incoming tasks cooperatively to ensure load-balancing at the cloudlets. Ge-LATA considers various factors like the current load, available green energy, service rate offered by cloudlets, and the distance from the mobile user, leading to optimal decisions in terms of latency and green energy consumed. Simulations are performed using the actual solar insolation data taken from the NREL database. Ge-LATA is tested with other offloading schemes for latency in processing the offloaded tasks and green-energy consumed under different solar insolation scenarios in these simulations. Simulation results show that Ge-LATA achieves up to 31.87% of reduction in the latency while ensuring up to 50.15% of reduction in the energy consumption than other comparable task-assignment schemes.Thus, Ge-LATA suggests that it leads to an optimal task assignment by considering the various factors mentioned above during the task assignment process. Thus, Ge-LATA considers the above-mentioned extensive set of parameters during the task allotment process. It also proposes an efficient green energy allotment scheme that adapts itself to actual weather and network conditions, leading to optimal task assignment decisions in GCNs.

Performance Evaluation of a MW-Size Grid-Connected Solar Photovoltaic Plant Considering the Impact of Tilt Angle

This paper presents a study for the estimation of generation from a large-scale, grid-interfaced solar PV plant using the PVsyst software. This study aims to investigate the effect of tilt angle on the performance of the grid-integrated solar PV plant. Two types of tilt angle test plants, i.e., a fixed tilt angle of 30° (1 MW) and two seasonal tilt angles, in summer 13° and in winter 30° (2.5 MW), have been selected at the same location in Bikaner, India. The performance of the proposed test solar power plants, rated at 1 MW (fixed tilt angle) and 2.5 MW (two seasonal tilt angles), is established by comparing the results obtained using the PVsyst software with the practical data of annual solar insolation. It is established that the radiation incident on PV modules will increase by 2.41% if two seasonal tilt angles are considered. Hence, the annual capacity utilization factor (CUF) has increased by 0.26%. Furthermore, it is established that the proposed method’s performance is superior compared to the statistical methods reported in the literature.

Small scale wind & solar photovoltaic energy conversion system for DC microgrid applications

The rise in demand for electrical energy throughout the globe gives a significant rise in new power generating sources. The Wind and Solar Photovoltaic energy sources are the most propitious power generating sources among them. Nowadays, these sources play an important role to form a Micro Grid with the incorporation of conventional grid and energy storage facilities. This article comprises of the simulations analysis for Wind Energy Conversion System and Photovoltaic Energy System incorporated with DC load for the applications of DC Microgrid. The mathematical model of the WECS and PVES are incorporated and proposed with the Gain Scheduled Proportional Integral controller is proposed in the paper. The WECS and PVES are simulated with interfacing units for the DC load. The results are obtained for Ahmedabad, Gujarat, India for the input solar insolation and wind speed data. The materials used in small wind energy conversion systems and photovoltaic energy systems are discussed for microgrid applications. The performance for the WECS and PVES is analyzed for change in wind speed and change in solar insolation. The incorporation of GSPI controller provides stable results to maintain the voltage regulation. The results are stable over an extensive range under the unpredictable atmospheric conditions the dynamic scheduling is proposed.

Optimal planning of solar photovoltaic and battery storage for electric vehicle owner households with time‐of‐use tariff

This paper presents a practical optimal planning of solar photovoltaic (SPV) and battery storage system (BSS) for electric vehicle (EV) owner households with time of use (TOU) electricity pricing. The main aim of the optimisation problem is to minimize the Cost of Electricity (COE) while satisfying the design constraints over 20-year project lifespan. Novel rule-based home energy management systems are created to investigate the optimal sizing of two system configurations: (1) SPV-EV, and (2) SPV-BSS-EV. The arrival and departure times of the EV's availability, as well as its initial state-of-charge are incorporated into the energy management system via stochastic functions. Sensitivity analyses of the feed in tariff, grid constraint, electricity demand, and available rooftop area are provided to investigate the variations of cost of electricity and capacities of SPV and BSS. From the study results, practical guidelines for grid-connected households, based on TOU energy pricing, are provided to select the optimal capacity of SPV and BSS to accommodate the existing EV. The optimisation method is general and applicable to any household owning EV; however, in this study realistic data of solar insolation and temperature as well as household electricity demand and electricity prices are implemented for South Australia. Uncertainty analysis is investigated based on 10-year real and stochastic data to prove the optimal results. It is found that the optimal configuration for a typical SA household utilising TOU pricing with an EV requires a 10-kW SPV with a 10-kWh capacity of BSS.

Variations in seasonal solar insolation are associated with a history of suicide attempts in bipolar I disorder

BackgroundBipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries.MethodsData analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries).ResultsThis analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p < 0.01.ConclusionA large change in solar insolation, both between winter and summer and between the minimum and maximum monthly values, may increase the risk of suicide attempts in bipolar I disorder. With frequent circadian rhythm dysfunction and suicidal behavior in bipolar disorder, greater understanding of the optimal roles of daylight and electric lighting in circadian entrainment is needed.

Анализ влияния способов построения временных рядов солнечной инсоляции и скорости ветра на точность прогноза режима энергетических систем

Two different approaches to obtaining the time series of solar insolation and wind velocity data for engineering analyzes of power systems are considered. A stochastic model for obtaining solar insolation and wind velocity at daily sampling intervals based on monthly average parameters is described. A comparative analysis of calculating various combinations of complex power systems based on the use of photovoltaic converters (PVC), windmills, and fuel generators by applying different approaches to obtaining stochastic solar insolation and wind velocity data in the VizProRES software package is carried out. Based on the simulated data, a probabilistic assessment of systems with different equipment compositions is given. A comparison of the average costs of kWh obtained proceeding from long-term climatic data and generated based on the monthly averaged parameters has shown that the difference in the results for the “PVC + fuel generator” and “windmill + fuel generator” systems was less than one percent, and for the PVC + windmill + fuel generator was slightly more than 3%, which shows the possibility of using each approach for design analysis of power systems consisting of one or more probabilistic sources.

Performance optimization of a photovoltaic-diesel hybrid power system for Yanbu, Saudi Arabia

&lt;abstract&gt; &lt;p&gt;In the rural areas of Saudi Arabia, which are not connected to the national grid, electricity is supplied mainly from diesel generators. This is not just a non-renewable energy source, but it has also resulted in environmental damage and may be hazardous to human health. In order to mitigate the problem, integration with a solar photovoltaic system is proposed. A Photovoltaic-Diesel Hybrid System (PvDHS) was designed, analyzed, and optimized based on the climate data of Yanbu, Saudi Arabia. Measured local solar insolation and climate data were used in the Hybrid Optimization Model for Electric Renewables (HOMER) software with different system components and configurations in order to optimize the design that yields the best energy cost. A system consisting of a 3 kW photovoltaic system, a 2 kW diesel engine, a 1 kW converter, and 14 kWh batteries were identified to be the most cost-effective for the average daily electricity demand of 10.5 kWh. The total Net Present Cost (NPC) of this system is ＄17, 800, a reduction of 50% over the ＄35, 770 cost of the diesel-only system. The PvDHS useful electrical energy is found to be ＄0.36/kWh, while the Cost of Energy (COE) of the diesel-only system is ＄0.72/kWh. The system is expected to pay for itself in 2.8 years and reduce CO&lt;sub&gt;2&lt;/sub&gt; emissions by 8110 kg per year.&lt;/p&gt; &lt;/abstract&gt;

Исследование способов повышения энергетической эффективности сетевой фотоэлектрической станции в программном обеспечении PVsyst

The paper presents a classification of solar tracking systems used in photovoltaic power stations (PVS) and their operating principles. A simulation model of a grid-connected 5-kW PVS has been developed in PVsyst, to which end the researchers selected PVS equipment and optimized the PV cell tilt angles. The paper further analyzes a grid-connected PVS in Orenburg Oblast in PVsyst under the following configurations: static PV cells, not tilted vs seasonally varied tilts; single-axis solar trackers with vertical and horizontal axes of rotation vs a dual-axis solar tracker. The analysis is based on solar insolation data for 2019 obtained from the research team’s HP-2000 weather station. Dual-axis solar tracker and single-axis vertical trackers are shown to have the best year-round generation, providing an increase of 13.2% and 11.5%, respectively, against the static PV cells (no change in tilt).

Mathematical evaluation of sloped solar chimney power plant for power generation in different regions of Nepal

Abstract Sloped solar chimney power plant (SSCPP) could be one of the appropriate technologies for powering Nepalese communities. The main components of the plant are chimney, collector and power-generating unit. In this study, the mathematical evaluation of the SSCPP has been conducted for the estimation of the power generation in Nepalese context. For the analysis, the mathematical models have been developed from the governing equations. The parameters such as chimney height and radius, collector radius, ambient temperature and solar insolation have been taken as inputs for simulation of the overall system. The output parameters such as overall system efficiency, chimney efficiency, air velocity, power output from the turbine and electrical power from the proposed system have been evaluated. The results showed that power developed by air, turbine power and electrical power is 120, 66 and 44 kW, respectively. The developed power is estimated when the height and the radius of the chimney were 190 and 5 m, respectively. It is seen that ambient temperature and velocity of air also play an important role in the power generation. The performance influencing the power output based on turbine pressure ratio, thermal conductivity and specific heat capacity of soil and the mass flow rate have also been estimated. Besides, the solar insolation data were taken for five different regions of Nepal to find the power generation and collector efficiency.

МОДЕЛИРОВАНИЕ ЗАКОНОВ РАСПРЕДЕЛЕНИЙ МОЩНОСТИ ВЕТРОЭНЕРГЕТИЧЕСКИХ И СОЛНЕЧНЫХ СТАНЦИЙ

Актуальность. Мощность, выдаваемая генерирующими станциями на возобнов­ляемых источниках энергии, ветроэнергетическими и солнечными, зависит от состояния природной среды в конкретной географической точке, доминирующих скоростей ветра и уровня солнечной инсоляции. Закономерности, характеризующие скорости ветра и солнечную инсоляцию, зависят от местности, времени года и носят вероятностный характер. Это значит, что вероятностный характер имеет и мощность, выдаваемая генерирующими станциями на возобнов­ляемых источниках энергии. Риски, связанные с неточным знанием вероятностных закономерностей, описывающих эти источники, а также непредсказуемость (неопределённость) природной среды являются причинами, из-за которых системные операторы не учитывают такие станции в расчетах баланса мощности. Это, в свою очередь, не позволяет рассматривать генерирующие станции на возобновляемой энергии как полноценных участников рынка, прикрывая поток инвестиций в подобные проекты. Уточнение законов распределения вероятностей скорости ветра и солнечной инсоляции на основании статистического анализа соответствующих рядов измерений, а также уточнение на их основе законов распределения вероятностей для мощности соответствующих электростанций может оказать существенную помощь системному оператору при прогнозировании мощности, генерируемой станциями на «зеленой» энергии. Цель: построение моделей законов распределения, наилучшим образом описывающих результаты наблюдений скорости ветра и солнечной инсоляции, а также моделей законов распределения для вырабатываемой мощности ветроэнергетической и солнечной станций. Методы: методы оценки параметров законов распределения, методы проверки статистических гипотез. Результаты. Показано, что в отличие от наиболее часто используемого в этих целях закона Вейбулла, наилучшими моделями законов распределения вероятностей для рядов измерения скорости ветра и солнечной инсоляции на рассматриваемой территории являются законы семейства бета-распределений 3-го рода, а также смеси этих законов. То же самое касается описания распределения вероятностей мощности ветроэнергетической и солнечной станций. Построены модели законов распределения (по месяцам) для скорости ветра, солнечной инсоляции и мощности соответствующих станций. Показано, что на основании закона распределения скорости ветра и математических соотношений, связывающих мощность со скоростью ветра, можно строить хорошие модели для распределений вероятностей мощности ветроэнергетических станций. Построенные модели могут использоваться в качестве вспомогательного инструмента для системных операторов энергосистем для прогнозирования выдаваемой мощности.

Optimal Capacity of Solar PV and Battery Storage for Australian Grid-Connected Households

This article determines the optimal capacity of solar photovoltaic (PV) and battery energy storage (BES) for grid-connected households to minimize the net present cost of electricity. The real-time rule-based home energy management systems using actual annual data of solar insolation, ambient temperature, household electricity consumption, and electricity rates are used in the optimization process. The above-mentioned technique is applied to two system configurations—household with a solar PV and a BES. The uncertainty analysis is implemented using ten years of real data to confirm the optimal results. An accurate cash flow analysis is also presented to illustrate the customer payment in each year during the project lifetime. The sensitivity analysis is conducted by varying the cost and capacity of system components, grid constraint, average daily electricity demand, and retail price of electricity. A typical grid-connected household in South Australia is considered as the case study. A practical guideline is presented for the residential consumers in South Australia to select the optimal PV/BES based on their daily average electricity demand and the available rooftop space for PV installation. Finally, the proposed optimization method is applied to households of other Australian States and a comparison of results is presented.