Improving Accuracy in Solar Power Plant Power Generation Prediction: A Hybrid Model Proposal

Accurately predicting the power produced during solar power generation can greatly reduce the impact of the randomness and volatility of power generation on the stability of the power grid system, which is beneficial for its balanced operation and optimized dispatch and reduces operating costs. Solar PV power generation depends on the weather conditions, such as temperature, relative humidity, rainfall (precipitation), global solar radiation, wind speed, etc., and it is prone to large fluctuations under different weather conditions. Its power generation is characterized by randomness, volatility, and intermittency. Recently, the demand for further investigation into the uncertainty of short-term solar PV power generation prediction and its effective use in many applications in renewable energy sources has increased. In order to improve the predictive accuracy of the output power of solar PV power generation and develop a precise predictive model, the authors used predictive algorithms for the output power of a solar PV power generation system. Moreover, since short-term solar PV power forecasting is an important aspect of optimizing the operation and control of renewable energy systems and electricity markets, this review focuses on the predictive models of solar PV power generation, which can be verified in the daily planning and operation of a smart grid system. In addition, the predictive methods identified in the reviewed literature are classified according to the input data source, and the case studies and examples proposed are analyzed in detail. The contributions, advantages, and disadvantages of the predictive probabilistic methods are compared. Finally, future studies on short-term solar PV power forecasting are proposed.

Renewable power generation is known as a low emission energy source. However, it is extremely important to analyze the greenhouse gas (GHG) emissions of renewable energy power stations along the entire life-cycle to broaden the concept of sustainability to an environmental and economic point of view. The main objective of this study was assessing and comparing the GHG emissions within the life-cycle of solar and gas power generation in Iran. A further objective was to evaluate the external costs associated with carbon emissions. The life-cycle inventory was first analyzed. The output emissions inventoried in the study were carbon dioxide (CO2). Then the CO2 emission and social cost of carbon during every process in solar and gas technologies were calculated by energy and environment software. Gas power plants are found to have a life-cycle CO2 emission of 658 g-CO2/kWh, which is comparatively higher than solar power life cycles (5.9 g-CO2/kWh). Life-cycle CO2 emissions from solar and gas power generation systems, imposes 70.8 and 2883.6 million US dollars/year to compensate its social effects. Results of the present study showed that the solar power generation is the environmentally-friendly form of producing electricity when compared with gas power technology in terms of life-cycle CO2 emissions. This makes solar power as promising solution to the Iran's cleaner power transition.

Purpose. The aim of the article is the theoretical and practical substantiation of the prospects for interaction between the state and society in order to overcome the energy crisis associated with the consequences of the russian-Ukrainian war through the development of wind and solar power generation and, as a consequence, cryptocurrency heat generation. Methodology of research. The methodological basis of this economic scientific research is the dialectical method of scientific cognition. In the process of economic scientific research, general scientific and special scientific methods were applied, among which the main ones are: abstract and logical methods – for formulating general conclusions of economic scientific research; systemic approach – in determining the causes and factors of the influence of the interaction of the state and society in the development of wind and solar power generation and, as a consequence, the development of cryptocurrency heat generation, on the energy security of households. Findings. The role of green energy was studied, in particular, the trends in the installation of small solar and wind power plants by households and firms to ensure the economic, demographic and energy security of the country in the conditions of a full-scale russian-Ukrainian war. Based on the analysis, it was determined that state support for households' investment in the installation of their own solar and wind power plants through a reduction in the tax burden on the import of their components, as well as financial incentives for their purchase, is a key factor in the development of green energy. It is estimated that investments by economic entities in the development of solar and wind power plants in 2024 and subsequent years will allow citizens not only to reduce electricity costs, avoid blackouts and ensure stable operation of critical electrical appliances, but will also contribute to energy independence in the long term. In addition, such investments can become a source of profit throughout the entire period of operation of energy equipment. The possibilities of using excess electricity for cryptocurrency mining are analysed, which creates significant additional economic benefits for households. It is summarized that the combination of cryptocurrency mining and electricity generation by home solar and wind power plants creates a significant synergistic effect that has a mutual economic and security impact on households. Based on the research conducted, it is substantiated that both during the war and in the post-war period, it is economically feasible for households to invest simultaneously in two areas – electricity production from renewable sources and cryptocurrency mining. This will maximize the benefits from the use of generated electricity, increase financial stability, and promote energy autonomy. Originality. The substantiation of the feasibility of introducing state investment support for households by economic entities in the purchase of solar power plants and their payback with the possibility of ensuring a synergistic positive economic effect at the micro- and macro-economic level has gained further development. Practical value. The obtained results of the study can serve as the basis for households and firms to make decisions on the installation of wind and solar power plants for electricity generation in order to meet personal needs and, as a result, additional heat generation, and the mining of crypto coins using cryptocurrency farms is advisable for the state and its citizens due to the achievement of a significant positive synergistic economic effect. Key words: investments, wind power plants, solar power plants, green energy, cryptocurrency, mining.

Solar photovoltaic power generation as a building electrical professional in the energy use of important technical means, through the realisation of photovoltaic conversion, can be a large amount of light energy transmission to the building application, once the electrical energy surplus is too much, but also can be transmitted to the power grid use. Based on this, the article takes the solar photovoltaic power generation system as the basis, comprehensively analyses the operation principle and basic characteristics of solar photovoltaic power generation, summarizes the main influencing factors of grid-connected solar photovoltaic power generation, as well as the impact of grid-connected solar photovoltaic power generation on the grid, and researches on applying automation technology to solar photovoltaic power generation, such as photovoltaic buildings, DC inverters, reactive power compensation, etc., so as to comprehensively improve the grid-connected solar photovoltaic power generation efficiency and provide a constant source of energy for buildings. Solar thermal power generation technology is another kind of solar power generation technology besides photovoltaic power generation. It is a renewable energy generation method that integrates solar thermal conversion power generation, large-scale heat storage and the characteristics of power grid synchronmachine. According to the influence of different intermittent heat load fluctuation characteristics on the design of solar heat collection and heat storage system, the design method of heat collection and heat storage of intermittent solar heating system is established. The operation characteristics of solar energy system in three typical intermittent heating modes are compared and analyzed. It provides the design method and operation optimization strategy for the efficient utilization of solar heating system.

Agri-voltaic system is the combination between solar photovoltaic power generation and plant cultivation. A 480 Wp ground-mounted solar panel system was designed and constructed. After that, a plant plot sizing 1 x 7 m under this solar panel was design as well as 175 vegetations of bok choy were then grown. The potential of agri-voltaic system consisting of efficiency of solar power generation, the bok choy yield and the land equivalent ratio of system were monitored and evaluated. The system could generate power at around 1.05 kW/day (31.00 kW/month). In addition, 8.00 kg/plot of bok choy yield was obtained. The total value of both systems could make up to $6.34 a month ($3.73 and $2.61 from solar power generation and plant production, respectively). The land equivalent ratio (LER) of system was 1.80 which was indicated that the agri-voltaic system could increase the land value up to 80%.

Design, commissioning and operation of a mini hybrid parabolic trough solar thermal power plant for direct steam generation

The paper made an extensive analysis of power generation in the territory of the Republic of Crimea. A special issue is the use of renewable energy sources (RES), in particular wind (WPP) and solar power plants (SPP). The current power generation capacities of the republic are determined and the power deficit is shown, which is currently covered by the electricity of the energy system of the Krasnodar Territory. One of the most important features of the development of the modern world is the increased attention of the world community to the problems of rationality and efficiency in the use of energy resources, the introduction of energy saving technologies and the search for renewable energy sources. In 2021, the countries of the Middle East and Europe increased the capacity of wind and solar power plants several times over. In India, installed renewable energy capacity has exceeded 100 GW. In June-July 2021, solar power generation in the European Union reached a record level and amounted to 39 TWh, an increase of 28%. For most European countries, renewable energy accounts for more than 15% of electricity generation in general. This is due to the fact that in the main markets, renewable, in particular solar electricity, is significantly cheaper than the energy of gas and diesel power plants.For Russia, the southern districts and coastal zones are effective geographical areas for the use of WPPs and SPPs. Thus, the Republic of Crimea is a geographically favorable place for the development of alternative energy.The technical and economic characteristics of SPP and WPP are determined, the current own wind and solar generation is considered in detail. The ways of development and permissible capacities of renewable energy sources in the Crimea are determined. According to the requirements for the systems of regulation, control and protection of renewable energy sources (RES) during their operation as part of the Unified Energy System of Russia, the use of alternative sources of electricity together with the main grid is permissible with their total capacity equal to 20% of the maximum load of the region. Therefore, the development and distribution of renewable energy in the Crimea has a huge potential. The applied systems for integrating RES into the overall energy system are considered, their shortcomings are identified.For the further development of RES in the Crimea, it is proposed to use a model of intelligent integration of SPPs and WPPs into the energy system of the peninsula using solid-state transformers. The use of power transformers for the transmission of electricity from RES to the network significantly reduces the flexibility of the system and eliminates the control of energy parameters. To increase the control capabilities of the output power to the network, as well as to reduce energy costs during voltage transformation, it is proposed to use solid-state transformers (SST) at the inverting stage. The use of SST changes the general principle of power transfer from RES to the network to the following: the DC voltage accumulated in the batteries of WPP and SPP is fed through a high-frequency inverter to a pulse transformer, where it rises to the voltage of the power line. Then it is rectified and inverted to the required mains frequency. Modern power semiconductor components may well provide such a model for integrating RES into the grid. The proposed model is distinguished by the presence of effective control of energy parameters, as well as high efficiency.

Solar energy is significant potential for power and heat production. The Alternative Energy Development Plan 2018–2037 (AEDP2018) developing by Thailand’s Ministry of Energy demonstrates that solar energy is a key role in renewable energy utilization, especially for power generation. In general, solar photovoltaic (PV) technology is the most common type of solar power generation technology. This paper presented a potential of using grid-connected solar PV power generation system for the rooftop of a commercial building. The design and simulation of the solar rooftop PV power generation system and the economic analysis were accomplished. The installation of 1.85 MWp grid-connected solar PV power generation system on the rooftop area required 3,440 pieces of 540 Wp solar panels. By using PVsyst version 7.2, the solar panel configuration was connected in 20 pieces/string in series and 172 strings in parallel, with 80 kWac string inverters of 18 units. The simulated results of produced energy, specific production, and performance ratio were 2,678 MWh/year, 1,442 kWh/kWp/year, and 80% respectively. As a result, the energy cost saving was 269,317 USD with payback period (PB), net present value (NPV), and internal rate of return (IRR) of 6.37 years, 1,062,430 USD, and 15%, respectively. In conclusion, the installation of 1.85 MWp solar rooftop PV power generation system is technically feasible for the investment.

Solar energy is an abundant, clean, and renewable energy source, crucial for addressing the current global energy crisis. Efficiently harvesting solar power to generate electricity for smart grids is vital. However, the variability of solar radiation presents significant challenges in accurately forecasting solar photovoltaic (PV) power generation. Elements such as cloud cover, atmospheric conditions, and seasonal changes greatly influence the amount of solar energy available for electricity conversion. Accurate estimation of solar power output is therefore critical to evaluate the potential of smart grids. This study explores the use of various machine learning models to predict solar PV power generation in Lubbock, Texas. Performance is measured using Mean Squared Error (MSE) and R² metrics. The findings reveal that the Random Forest Regression (RFR) and Long Short-Term Memory (LSTM) models outperformed the others, achieving MSE values of 2.06% and 2.23%, and R² values of 0.977 and 0.975, respectively. These results indicate that RFR and LSTM are highly effective in capturing the complex patterns and relationships in solar power generation data. The developed machine learning models can assist solar PV investors in optimizing their processes and enhancing their planning for solar energy production

Yang, J. and Ma, X.-Y., 2019. Ship power generation system model based on distributed solar photovoltaic power generation. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 520–524. Coconut Creek (Florida), ISSN 0749-0208.In the marine environment, marine pollution caused by ship transportation is becoming more serious. The introduction of distributed solar photovoltaic (PV) power generation system in ship power system is an important method to effectively solve marine pollution. Taking the large-scale ocean-going vessels as research objects, this paper studies the application of distributed solar PV power generation in ship power generation system and establishes corresponding models. The results show that solar light intensity and temperature have a non-negligible influence on distributed solar PV power generation system, distributed solar PV arrays have the maximum values, and the maximum power point can be obtained by changing the dynamic load characteristics of the ship. Besides, based on the ship grid-connected system technology, it carries out the studies on the grid-connected and off-grid dual-mode system of ship power generation system and distributed solar PV power generation system, and performs analysis and modelling of the distributed solar PV power generation system. The research in this paper provides operational experience and conditions for the application of distributed solar PV power generation on large ships.

Comprehensive study of wind supercharged solar chimney power plant combined with seawater desalination

The increasing demand for sustainable energy solutions has highlighted the need to optimize solar power generation systems. While solar power has been extensively studied, the influence of local wind flow on solar irradiance and power generation remains underexplored. This study addresses this gap by developing a differential model that incorporates both solar irradiance and wind flow effects to enhance the prediction of solar power generation across various regions in Uganda. Key qualitative findings suggest that regions with higher wind flow significantly enhance solar power efficiency, revealing potential opportunities for optimizing solar facility locations. Numerical findings show that the northern region yielded the highest solar power generation (), followed closely by the eastern (), western (), and central () regions. Error analysis using the RMSE indicator confirms the validity of the model with values of 0.9701, 0.8215, and 6.4186 for the northern, central, and western regions, respectively. This work proposes an integrated approach to solar power generation, considering both solar irradiance and wind flow effects, with the potential to identify optimal deployment sites for solar facilities. Consequently, the study suggests deploying solar facilities in regions with higher solar power distribution and transmitting energy to areas with sparse distribution. Further studies are needed to conduct a comprehensive assessment of solar potential in varying environmental conditions.

Solar power generation is highly uncertain and intermittent due to its strong dependence on climate and meteorological factors. In this study, we have proposed a bagging ensemble of artificial neural network (BagANN) model with weighted averaging optimized using grey wolf optimization (GWO) and investigate the impact of climatic and meteorological factors on the output power prediction of the solar power plant. Initially, we have preprocessed the data by applying feature engineering, normalization techniques, and appropriate features are selected for power prediction. The hyperparameters of the BagANN model are tuned and optimized using the GWO technique to improve the models predictive accuracy. Experiments are conducted to evaluate the generalization performance of the developed model using five-fold and 10-fold cross-validation techniques. The performance results are assessed using RMSE, coefficient of determination ( R 2 ), adjusted ( R 2 ), and the MAPE. Results show that the BagANN with weighted averaging has a higher level of precision with R 2 of 98.5% predictive accuracy, has less prediction errors with 0.1263 MSE and 0.0267 MAPE than the other developed models. From the result, it is evident that the BagANN model has significant improvements compared to other models available in the literature in terms of robustness of the prediction and predictive accuracy.

Regarding the Direct Current (DC) power generation for the offshore gas wellhead platform, the hybrid power generator Thermoelectric generator (TEG) and Solar Panel is used in the COMPANY design to supply power for DC loads such as a PLC and Telecom system of the offshore gas wellhead platform in past 10 years. To effectively achieve Capital Expenditures (CAPEX), and Operating Expenditures (OPEX) and green environment, now 100% solar panel power generator with battery backup is considered. The challenge of a single power generation which is a solar power system is reliability. There are a few key factors that effect to the reliability of 100% solar power system design. The shadow on solar panel, solar radiation and battery backup duration during the low insolation and nighttime would be key factors in engineering design. Approximately 20 gas wellhead platforms in the gulf of Thailand are designed with 100% solar power generation with battery backup during the past 3 years, they have been operating without power generation issue. When designing solar panel locations, the software Sun-Path software is used to confirm there is no significant shadow on solar panel in all seasons. For the sun solar radiation, we use weather statistic solar insolation data provided by NASA. And battery backup time, we use weather statistic data as a factor for battery backup time. During the low insolation days and nighttime, the DC load shall be power supplied by backup battery. Battery duration shall be referred to solar insolation and Equivalent Number of NO-SUN Or BLACK Days data provided by NASA. As per a study prior deciding to select 100% solar power system gas wellhead platform, 100% solar power system CAPEX can totally save about 30% when compared to Hybrid Thermal Electric Generation (TEG) &Solar power generation. In addition, there is no concern about fuel gas properties such as high CO2 on wellhead platform. There is no fuel gas consumption in solar panel power generation which support a green environment.

Chapter 10 - Meteorological assessment of coupled wind–solar power generation regimes in Spain