Photovoltaic Electricity Generation Research Articles

Farm electricity system simulator (FESS): A platform for simulating electricity utilisation on dairy farms

The objective of this paper was to define, validate and demonstrate a model capable of accurately simulating dairy farm electricity consumption across varying herd and parlour sizes, to facilitate research investigating renewable energy systems (RES) and demand side management (DSM). The Farm Electricity System Simulator (FESS) was developed using grey-box modelling techniques utilizing empirical data for parameter tuning. Empirical data were gathered from nine spring calving, pasture based dairy farms located in the Republic of Ireland. A k-means clustering analysis was conducted, separating the farms into three, near homogenous groups, from which representative farms were selected. FESS was trained using 12 months of data from three representative farms using the repeat hold out method for data partitioning with 75 % of data used for training and 25 % used for validation. An optimisation algorithm was used to minimize the error during model training. Through cross-validation, FESS achieved a root mean squared error (RMSE) of 7.65 kWh, mean absolute percentage error (MAPE) of 7.10 %, mean percentage error (MPE) of −0.86 % and a relative prediction error (RPE) of 7.56 % for total daily electricity consumption. Across the three farms, the simulated outputs of FESS achieved an average R2 value of 0.72, demonstrating good agreement with observed data. FESS’s utility was demonstrated by analysing the effects of different electricity pricing structures and on-site solar photovoltaic electricity generation on total farm energy costs. We concluded that FESS simulated on-farm electricity consumption with sufficient accuracy for the intended application. FESS accurately simulated dairy farm electricity consumption across three dairy farms of different herd and parlour sizes while evaluating the effects of demand side management and renewable generation on farm electricity consumption and costs.

Optimal design of a local renewable electricity supply system for power-intensive production processes with demand response

This work studies synergies arising from combining industrial demand response and local renewable electricity supply. To this end, we optimize the design of a local electricity generation and storage system with an integrated demand response scheduling of a continuous power-intensive production process in a multi-stage problem. We optimize both total annualized cost and global warming impact and consider local photovoltaic and wind electricity generation, an electric battery, and electricity trading on day-ahead and intraday market. We find that installing a battery can reduce emissions and enable large trading volumes on the electricity markets, but significantly increases cost. Economically and ecologically-optimal operation of the process and battery are driven primarily by the electricity price and grid emission factor, respectively, rather than locally generated electricity. A parameter study reveals that cost savings from the local system and flexibilizing the process behave almost additively.

Research on optimal dispatching strategy of solar thermal-photovoltaic-wind combined power generation system

New energy photovoltaic generation of electricity and wind power have developed rapidly, and the installed capacity has been increasing, but their volatility and randomness have also caused a certain impact on the power grid. Considering that solar thermal power generation and photovoltaic power generation have natural complementary advantages, and solar thermal power generation and power output of wind power can complement each other in time., this paper proposes an optimal scheduling strategy for solar thermal-photovoltaic-wind alliance power generation system, which uses thermal storage device of the heat power station of solar energy to cope with the problem of wind and light abandonment of new energy power generation and promote the consumption level of renewable energy. The economic and stability deviations of the system before and in the launch the solar thermal power station are compared in depth and the simulation is verified in the IEEE30 node system. The results show that after the introduction of solar thermal power (CSP) station in the combined power generation system, the economy of the scientific is remarkable improvement, the wind turbine is also reduced, which realizes the full absorption of new energy.

Assessment of Economic Synergies of Agrivoltaics in the Distributed Generation Segment in Chile

Agrivoltaics (AV) combines photovoltaic (PV) electricity generation with agriculture on the same land. In Chile, despite high potential, AV is not yet commercialized due to high investment cost. To close the remaining cost gap to conventional PV, we shed light on a set of AV specific synergies in the market segment of Small Distributed Generation Facilities. Through a techno-economic model, this paper monetizes AV synergies to derive the economic performance of a sun tracked AV system over blueberries for the PV stakeholder. The study reveals that tracked AV systems can be operated with an Internal Rate of Return (IRR) of 5.2% at the threshold of profitability. This is enabled due to the exploitation of synergies within the market segment that improve IRR for the PV stakeholder by 2.5%. Still, sun-tracked AV requires compulsory technology grants between 5 – 10 USD/MWh to be economically implemented. The results indicate the necessity for regulative adaption. Legislation must open agricultural land for AV project development to enable the commercialization.

An urban-scale spatiotemporal optimization of rooftop photovoltaic charging of electric vehicles

Solar photovoltaic (PV) farming is increasingly being used to power electric vehicles (EVs). Although many studies have developed dynamic EV charging prediction and scheduling models, few of them have coupled rooftop PV electricity generation with the spatiotemporal EV charging demands at an urban scale. Thus, this study develops a research framework containing three interconnected modules to investigate the feasibility of EV charging powered by rooftop PVs. The framework is constructed by the statistics of time serial EV charging demands at each station, the planning of rooftop PV installations associated with all charging stations, and the development of a dynamic dispatching algorithm to transmit surplus electricity from one station to another. The algorithm can maximize the overall balance between supply and demand, maximize the total PV electricity generation while minimising the total PV area, minimize the number of PV charging stations used as the suppliers for dynamic dispatch, and minimize the total electricity transmission distance between stations given the same power supply. The experiment utilizes a complete EV charging dataset containing 5574 charging piles with more than 9.7 million records in June and July in Guangzhou, China. The results show that rooftop PVs can supply more than 90% of the charging demand. The results encourage and inspire us to generalize and promote such a solution in other cities. Future work can refine the algorithm by adapting different PV sizes into various charging stations to further improve the electricity generation capability and the dynamic dispatching efficiency.

Accurate nowcasting of cloud cover at solar photovoltaic plants using geostationary satellite images

Accurate nowcasting for cloud fraction is still intractable challenge for stable solar photovoltaic electricity generation. By combining continuous radiance images measured by geostationary satellite and an advanced recurrent neural network, we develop a nowcasting algorithm for predicting cloud fraction at the leading time of 0–4 h at photovoltaic plants. Based on this algorithm, a cyclically updated prediction system is also established and tested at five photovoltaic plants and several stations with cloud fraction observations in China. The results demonstrate that the cloud fraction nowcasting is efficient, high quality and adaptable. Particularly, it shows an excellent forecast performance within the first 2-hour leading time, with an average correlation coefficient close to 0.8 between the predicted clear sky ratio and actual power generation at photovoltaic plants. Our findings highlight the benefits and potential of this technique to improve the competitiveness of solar photovoltaic energy in electricity market.

Reverse osmosis desalination for greenhouse irrigation: Experimental characterization and economic evaluation based on energy hubs

Water scarcity is a threat to crucial economic sectors, notably agriculture, which is a major concern in arid regions like Spain's Almería province, home to a substantial greenhouse industry. One of the possible solution for this fact is the use of alternative water sources, as desalination. This work offers a comprehensive characterization and economic evaluation of reverse osmosis desalinated water for greenhouse irrigation, exploring various scenarios, including photovoltaic electricity generation. To accomplish this, an economic model based on the energy hub methodology is proposed. This model provides a versatile framework that accounts for factors like variable electricity generation and water demand, allowing for accurate cost assessments. The results show that levelized cost of water between 2.51 and 3.69 €/m3 can be reached depending on the configuration of the system. Moreover, the cash flow analysis demonstrates that the investment in reverse osmosis systems for greenhouse irrigation can be recovered in less than three years in all the studied scenarios. These findings suggest that using reverse osmosis systems for greenhouse irrigation is a viable option particularly appealing to farmers and small associations in specific districts, promoting distributed desalination adoption in agriculture environments.

Enhancing rooftop solar energy potential evaluation in high-density cities: A Deep Learning and GIS based approach

The assessment of rooftop solar potential is vital for optimal photovoltaic (PV) system placement and renewable energy policy in dense urban areas. Complex shading from buildings and diverse rooftop obstacles have posed significant challenges to this evaluation. We propose a method that leverages Deep Learning and Geographic Information Systems (GIS) to precisely gauge solar energy potential at the city scale, accounting for shading and obstacle effects. We integrated building data with height attributes to measure inter-building shading and employed the DeepLab-v3 Convolutional Neural Network to identify rooftop obstructions from high-resolution satellite imagery. Using this hybrid framework, we calculated the available rooftop area in Shanghai, excluding the Chongming Island, and produced a detailed map of PV potential. Results show that the estimated annual potential for rooftop solar radiation in Shanghai stands at 257,204 GWh, with a predicted annual PV electricity generation of 49,753 GWh. In the study area, obstacles occupy approximately 14.9 % of the rooftop area. Neglecting the impact of rooftop obstructions and shading effects would result in a 25.6 % overestimation of the rooftop PV capacity. This work advances the precision of renewable energy development and informs sustainable urban planning strategies.

Prospective life cycle environmental impact assessment of renewable energy-based methanol production system: A case study in China

Integrating renewable electricity and green hydrogen with CO2 utilization to produce chemicals has drawn much attention due to its low carbon emission characteristics. The goal of this paper is to investigate the environmental sustainability of producing a steady hourly output of methanol by utilizing electricity and hydrogen produced via renewable energy resources, and CO2 captured from a coal-fired power plant located in Inner Mongolia, China. Six renewable energy-based electricity and hydrogen systems are considered based on photovoltaic, wind turbines and combinations thereof, including battery and grid technologies. The environmental impact indicators of these system are compared comprehensively through life cycle assessment approach, including not only global warming potential but also fossil fuel depletion, water & soil & air pollution indices and human health index. The results indicate that the most environmentally friendly system is Case B2 which uses photovoltaic to produce hydrogen and electricity, with battery for energy storage and excess electricity sold back to grid. It shows apparently the best sustainability performance in global warming potential, which is 0.105 kg CO2-eq per kg methanol. In general, the proposed six systems outperform conventional methanol production systems in terms of global warming potential and abiotic depletion potential, with reductions ranging from 74% to 92% and 51.1%–73.8% respectively, but they have high levels in other environmental sustainability indicators such as human toxicity, eutrophication potential, and ozone layer depletion potential due to the photovoltaic electricity generation unit. The findings highlight that it is essential to consider a comprehensive range of environmental sustainability indicators when developing renewable energy-based methanol systems on a large scale.

Unravelling the effects of dynamic urban thermal environment on utility-scale floating photovoltaic electricity generation

The utility-scale photovoltaic systems have been widely integrated for sustainable urban development. However, the varying photovoltaic conversion efficiency (PVCE) affected by dynamic urban thermal environment causes uncontrollable uncertainty in electricity generation, which challenges installed-capacity planning and load-balancing operations. To tackle this problem, this study develops a PVCE estimation model containing four hierarchical modules. First, photovoltaic surface temperatures (PVSTs) are retrieved from satellite imagery, and meteorological features are collected to represent the dynamic thermal environment. Second, the contribution of each feature to the PVST estimation is evaluated, referring to the Mean Decrease in Impurity, Permutation Importance, and SHapley Addictive exPlanations. Third, machine learning models using Support Vector Machine, Random Forest, and XGBoost are developed to establish robust regressions between PVSTs and the selected features, enabling an accurate estimation of PVST spatio-temporal heterogeneity. Finally, the spatio-temporally corresponding PVCEs are calculated, resulting in a refined estimation of annual electricity generation. The investigation of four floating PV systems in Singapore found that their PVCEs vary insignificantly throughout the year, which is probably because of its stable climate and the cooling effect of water. The proposed model is simple and effective, demonstrating its impact on PV potential estimation when the urban thermal effect becomes significant.

Evaluation of the energy-economic-environment potential of urban-scale photovoltaic bus parking lots: The case of Tianjin, China

Integrating urban bus parking lots with photovoltaics is an important solution to promote carbon neutrality and net zero emissions in transportation systems. Except for the research on the integration of photovoltaics with car parking lots and bus roofs, not much attention has been paid to photovoltaic bus parking lots so far. We develop a new methodology for evaluating the potential of urban-scale photovoltaic bus parking lots. We use Google Earth, Baidu Panorama Map, Grasshopper, UAV, and PVSYST to evaluate the electrical generation potential of the bus parking lots integrated with photovoltaics in the central urban area of Tianjin. Considering the actual driving conditions of buses, the operating income and expenditure, and lifecycle energy demand, we evaluate the charging potential, economic feasibility, and environmental benefits of photovoltaic bus parking lots. The results show that the electrical generation of photovoltaic bus parking lot in the first year is 53971.96 MWh, which can meet the normal operation of 50% electric buses. When the self-use ratio of photovoltaic bus parking lot electrical generation is 40%, 80% and 100%, the system will reach the balance of payments in the 6.21st, 4.79th and 4.31st year respectively. The energy payback time of the photovoltaic bus parking system is 4.00 years. Our research demonstrates that photovoltaic bus parking lots have significant potential as one of the strategies for low-carbon and green transportation development in China. We also discuss policy measures that can promote their large-scale application. Finally, the method proposed in this study can help evaluate and understand the feasibility of charging electric buses by integrating photovoltaics in bus parking lots covering large-scale urban areas, thereby supporting decision-making and better planning of PV-integrated bus parking lot.

Standalone Photovoltaic Power Stabilizer Using Double Series Connected Converter in Sudden Cloud Condition

Renewable energy is clean energy that cannot harm the environment in its way, especially on standalone photovoltaic electricity generation. The only problem with renewable energy electricity generation is the intermittency and its instability in power quality and power efficiency. Power system stability in renewable energy is essential during the real environmental case problem such as the sudden cloud. The sudden cloud, known for its ability to decrease solar irradiance input, depends on how thick and big the cloud is. Several attempts had been tried to increase renewable energy power system stability, including modifying its maximum power point tracker with a new algorithm such as perturb and observe. This paper discussed an improved way of maintaining renewable energy power system stability using perturb and observe Algorithm in a double series-connected Converter as the current and power stabilizer. The results show that the current overshoot has decreased by 65,336%, and the current sudden cloud undershoot decreased by 10,529%. Power overshoot also decreased by 43,685%, and the power of sudden cloud undershoot has decreased by 7,133%.

Energy generation by crystalline silicon photovoltaic network per meter square in Iraq

<span lang="EN-US">Iraqi people have been without energy for nearly two decades, even though their geographic position provides a high intensity of radiation appropriate for the construction of solar plants capable of producing significant quantities of electricity. Also, the annual sunny hours in Iraq are between 3,600 to 4,300 hours which makes it perfect to use the photovoltaics arrays to generate electricity with very high efficiency compared to many countries, especially in Europe. This paper shows the amount of electric energy generated by the meter square of crystalline silicon in the photovoltaic (PV) array that already installed in 18 states in Iraq for each month of the year. The results of the meter-square of PV array in three tracking positions are presented in this paper. This paper shows that the average electricity generated in North cities (Dohuk, Al-Sulaymaniyah, and Erbil) are less than the southern cities in the winter season (three positions) by about 40-50%. Iraq has a stable PV electrical generation during all the year in all regions except the North cities while the highest cities in electricity generation are (Najaf and Al-Anbar).</span>

AN INTEROPERABLE DIGITAL TWIN TO SIMULATE SPATIO-TEMPORAL PHOTOVOLTAIC POWER OUTPUT AND GRID CONGESTION AT NEIGHBOURHOOD AND CITY LEVELS IN LUXEMBOURG

Abstract. This paper focuses on the importance of Geographical Digital Twins to increase renewable energy production in urban areas and cities for decarbonization and reduction of climate change impacts. The study demonstrates the role of interoperable geographical digital twins based on Free and Open-Source software and geospatial software technologies in the simulation, monitoring, and management of renewable-based energy systems. We simulated the potential for building-integrated and building-attached solar photovoltaic (PV) electricity generation for the use case in cities to allow at a later stage for scale up to a nationwide level. The platform provides a tool for estimating PV power generation at high resolution across entire neighbourhoods and districts. Tools for the identification of cost-efficient PV placement or integration in buildings on roof-tops and facades were implemented to allow for interactive selection of optimal PV placement. The developed platform serves multiple beneficiaries, including municipalities, urban planners, developers, citizens, investors, and energy communities. Overall, the study highlights the advantage of an interoperable geographical urban digital twin, which provides the flexibility necessary to simulate and test scenarios for rapid, integrated urban planning for decarbonization under climate change. The platform is based on open-source, open standards and APIs, using open 3D city models, and allowing seamless integration of simulation and assessment methods and tools to provide a 3D real-world environment to assess and develop energy transition approaches.

A new non-isolated high-gain DC-DC converter for the PV application

Small, distributed types of generation like solar photovoltaic (PV) played a significant part in shifting to a clean energy future due to economic factors and governmental laws. DC-DC converters are essential in the generation of solar PV electricity because they regulate the output voltage relying on the input voltage. The conventional boost converter (CBC) has minimal output voltage gain, and voltage stress at a switch is typically equivalent to the output voltage. The voltage produced by distribution generation (DG) sources is minimal, necessitating the use of high-gain boost converters. This proposed study is concerned with the development of an improved architecture of non-isolated high-gain DC-DC converters for PV applications, which provides quadratic output voltage gain and reduced voltage stress across a switch. The proposed configuration of the converter is comprised of a conventional quadratic boost converter with a voltage lift cell, which provides a high gain. The topological benefit is the use of a single switch with a lower number of inductors which reduces the circuit bulkiness. The developed topology was contrasted in terms of voltage gain, number of passive components used, and other parameters with other recently presented topologies. The simulation was performed using MATLAB/SIMULINK, and the output voltage gain was verified by prototype experimental results employing the simulation data.

Ventilation and heat dissipation analysis of photovoltaic roof

In recent years, the development and utilization of new energy have attracted more and more attention. As a green and clean energy, the utilization and development of solar energy have attracted much attention. Moreover, solar photovoltaic (PV) technology has been vigorously promoted, with building-integrated photovoltaic (BIPV) technology widely used in the building sector. However, in BIPV, although PV modules can be used as building envelope materials and provide electricity for buildings, due to various conditions during installation and design, PV modules are prone to overheating problems and affect photovoltaic performance. Hence, in the present study, a novel type of PV roof structure with lightweight crystalline silicon PV modules installed on the building surface is proposed, and an air space is provided between the novel lightweight crystalline silicon PV modules and the building surface, the novel lightweight crystalline silicon PV module has the characteristics of thinness and flexibility. After that, an experimental test platform with air space is established, and the data of typical meteorological days are selected to analyze the electrothermal performance of the novel lightweight PV roof, to obtain the optimal structure with the best PV performance. The results show that, under the same conditions, when the spacing is 0 mm and 80 mm, the temperature of the backplane and the substrate of the PV module gradually decreases with the increase of the air space. In contrast, the PV power and electricity generation gradually increase with the growth of the spacing. At the same time, when the distance exceeds 40 mm, the changing trend of the backplane of the PV module temperature, the temperature of the roof substrate, and the electricity generation is not apparent. In the present study, the optimal spacing of the novel lightweight PV roof is 40 mm.

Dense station-based potential assessment for solar photovoltaic generation in China

To achieve carbon neutrality before 2060, China is vigorously promoting the development of solar photovoltaic (PV) systems to replace traditional power supplies dominated by fossil fuels. A detailed potential assessment for solar PV generation will contribute to constructing and integrating a new power system with a high proportion of solar energy. In this study, we combined high-density and high-accuracy station-based solar radiation data from more than 2400 stations and a solar PV electricity generation model to map the technical potential for solar PV generation in China, while simultaneously considering land constraints through geographic information system technology. We found that the total installable capacity is at least 44,614.6 GW for China as a whole, resulting in an annual electricity generation potential of 72.7 PWh. However, the spatial distribution of solar PV potential does not match the electricity demand in China. Northwest China accounts for more than 95% of the total PV technical potential of China, but the power load centers are mainly located in eastern, southern, and central China, accounting for more than 70% of the total electricity consumption of the country. The challenges of solar PV development in China include grid integration and transmission from resource centers to load centers. The establishment and planning of new power systems based mainly on clean energy should facilitate the integration of fluctuating solar resources in China. This study will contribute to the planning and construction of solar PV systems in China.

Model construction and electro-thermal-hydrogen co-generation performance for multi-section compound parabolic concentrator

Non-imaging solar concentrator has many applications in solar thermal conversion and photovoltaic power generation because of its performance characteristics such as no tracking, stable light concentration, compact structure and easy integration. For this purpose, this paper conducts a study on the non-imaging concentrator based on the optimized design of the concentrating surface structure for photovoltaic electric generation, thermal energy recovery and direct-drive hydrogen production. Firstly, a theoretical construction of a mathematical model of the solar Concentrating Photovoltaic and Photo-thermal (CPV/T) system with electricity-thermal-hydrogen co-generation and a numerical solution path for the Current and Voltage (I-V) characteristic curve is presented. Moreover, an integrated CPV/T system experimental setup is constructed outdoors and its power generation, heat collection and hydrogen production processes are measured. Finally, it is found that the average electrical efficiencies of the CPV/T system are 13.03 % and 13.29 % for theory and experiment, respectively. The theoretical and experimental average thermal efficiencies are 27.47 % and 27.24 %, respectively. The theoretical and experimental average hydrogen production rates based on Maximum Power Point Tracking (MPPT) control are 19.47 ml/min and 16.11 ml/min, respectively. The research results also show that the integrally constructed CPV/T system not only achieves effective conversion of solar energy into electrical and thermal energy, but also can directly convert electrical energy into clean, stable and easily stored hydrogen energy, which has potential application prospects.

Modelling of Large-Scale Photovoltaic Power Generation System Based on PSCAD and Analysis of Its Stability

In this paper, based on the study of PV power generation principles and mathematical models of PV cells, PSCAD simulation modelling is performed for a large-scale PV plant with required output over 100 MW, and its operational characteristics are analysed. An improved Newton iteration, conductance increment method and semi-aggregate equivalent control algorithm are used to achieve maximum power point tracking (MPPT) for large-sized photovoltaic electricity plant. Finally, the simulation analysis of the large-scale photovoltaic electricity generation system under normal operation and light disturbance is conducted to validate the validity and stability of the model.

The European Solar Communication—Will It Pave the Road to Achieve 1 TW of Photovoltaic System Capacity in the European Union by 2030?

The urgency of a clean energy transition in the European Union is now not only driven by concerns about climate change, but also by using local renewable energy resources to reduce the dependency on foreign energy imports. Solar photovoltaic electricity generation is acknowledged as one of the pillars of this transition and various policy measures were implemented over the last two years to not only accelerate the deployment of solar photovoltaic electricity generation systems, but also to rebuild a competitive solar value chain in Europe to hedge against solar photovoltaic component supply chain disruptions. However, the current political ambitions still do not pay sufficient attention to the importance of solar photovoltaics as a major contributor to the necessary future renewable energy supply. According to the market trend between 2017 and 2022, the currently average EU installed capacity of 474.55 Wp/capita will not reach the necessary 2246 Wp/capita or 1 TWp target by 2030. At the moment, only seven member states have an installed capacity per capita higher than the average EU value.