Large Solar Plants Research Articles

Scales of accountability: Solar mini-grids and clean energy for all in Uganda

There is great hope pinned on solar mini-grids to fulfil universal rural electrification targets and enable clean energy access, especially in low-income African countries such as Uganda. Yet Ugandan realities are complex, with many unelectrified households in villages the electric grid serves, and varied experiences with the few solar mini-grids implemented in recent years, indicating limited downward accountability. Crucially, large solar plants have arrived, making it timely to resolve the dilemma of just clean energy provision both in and from rural areas. Yet little research on energy transitions in this context exists to explain its political economic complexity. We draw on field visits to three solar mini-grids with contrasting performances, to Uganda's largest 20 MW solar plant, through dozens of villages, and on meetings with the regional utility and the Ministry of Energy and Mineral Development. This is supplemented by knowledge of Uganda's energy policy through document analysis and lived experience. We adapt accountability analysis to deploy a novel ‘scales of accountability’ framework at multiple spatial scales of solar deployment. Our analysis offers insights on the challenges Uganda must address to achieve the potential associated with solar mini-grids and multi-scalar solar energy transitions to achieve universal clean energy access.

Scenario of solar energy and policies in India

Abstract Solar power is energy from the Sun that is converted into thermal or electrical energy. China, the USA, and India have the world’s richest solar energy sources. India receives solar radiation with an average intensity of 200 MW/km2 and 250–300 sunny days a year. The solar radiation in India varies from 4 to 7 kWh/m2/day, with 2300–3200 sunshine hours yearly, depending on the region. Badhla Solar Park, Jodhpur, India, is the world’s largest solar plant, with 2.25 GW of installed capacity. Solar energy is the best alternative electricity source used explicitly in the agricultural sector. In the farming sector, the consumption of solar energy has been increasing. The major issues were the installation costs, low availability of technicians, and poor quality of panels. The focus on skill development equips the workforce to drive innovation, efficiency, and sustained growth in the renewable-energy field. With the support of international collaboration and a skilled workforce, India’s progress in solar energy development is a boon for the industry.

A comparative study of bifacial versus monofacial PV systems at the UK’s largest solar plant

Abstract This paper presents an extensive analysis of the UK’s largest bifacial photovoltaic (PV) power plant, located in North Yorkshire. Commissioned in January 2020, this trailblazing facility, with a total installed capacity of 34.7 MW, is a benchmark for the evaluation of bifacial solar technology within the region. This pioneering study provides a thorough comparative assessment of bifacial and monofacial PV systems through a methodical investigation of their energy production, degradation rates, and spectral responses over a 4-year operational period. Our findings reveal that bifacial PV modules, distributed across four segments of the power plant, demonstrate a remarkable average power gain ranging between 15.12% and 17.31% compared with monofacial modules. Despite experiencing marginally higher annual degradation rates—1.17% for bifacial compared with 0.91% for monofacial systems—bifacial modules show superior resilience and energy yield, particularly during winter months when albedo effects are pronounced due to snow coverage. The study also highlights the strategic importance of spectral response analysis in optimizing PV performance. Bifacial modules have shown greater efficiency in capturing infrared radiation—a property that could be exploited to enhance overall energy yield under specific environmental conditions. The empirical data indicate a consistent performance of bifacial modules with an average normalized energy output clustering around the expected efficiency level. Therefore, the results of this study are pivotal for understanding the practical implications of deploying bifacial PV technology on a large scale. They provide valuable data for stakeholders in the solar energy sector, guiding future installations and innovations in solar panel technology.

IoT Based Solar System Parameter Measurements

Using the Internet of Things Technology for supervising solar power generation can greatly enhance the performance, monitoring and maintenance of the plant. With advancement of technologies the cost of renewable energy equipment is going down globally encouraging large scale solar plant installations. This massive scale of solar system deployment requires sophisticated systems for automation of the plant monitoring remotely using web based interfaces as majority of them are installed in inaccessible locations and thus unable to be monitored from a dedicated location. The Project is based on implementation of new cost effective methodology based on IOT to remotely monitoring a solar plant for performance evaluation. This will facilitate preventive maintenance, fault detection of the plant in addition to real time monitoring.

Predictive evaluation of solar energy variables for a large-scale solar power plant based on triple deep learning forecast models

The advanced development of large-scale solar power plants (LSSPs) has made it necessary to improve accurate forecasting models for the output of solar energy. Solar energy is still hampered by the lack of predictability in its output, which remains a major hurdle in the solar industry. This paper focuses on triple deep learning (DL) techniques such as Artificial Neural Network (ANN), Recurrent Neural Network (RNN) and Convolutional Neural Network- Long-Short Term Memory CNN-LSTM to address this problem. These techniques are utilized in solar energy variables (SEVs) such as power generation (MWh), soiling loss (%), and performance ratio (PR %) to determine the optimal forecast model. The novelty of this research is that it is the first time that important solar system parameters such as PR and soiling loss have been studied to predict a feasible forecast model using a different DL scheme. The SEVs real-time dataset is procured from the largest solar plant in Pakistan, titled “Quaid-e-Azam Solar Park” (QASP). The main significance of the study is that ANN, RNN, and CNN-LSTM-based models were developed in the DL process through feature generation, data scaling, training, and testing steps to predict the optimal model. The prediction values were compared with the solar plant's actual values over the last 7 years, and then a comparison was made to predict the future forecast trend over the next 20 years. The aim and goal is to develop three models to investigate the accurate results of time-series forecasting on the SEVs dataset, as well as to evaluate the performance measure errors to determine the appropriate model. Based on the forecasting/prediction graphic and error results, it was demonstrated that the CNN-LSTM hybrid model is a more capable forecasting model for the output of power generation and PR values and a more accurate predictor of the future trend over the ANN and RNN models. However, the ANN model is slightly better performed in predicting of soling loss value than CNN-SLTM and RNN. Thus, the CNN-LSTM hybrid model is an optimal model for SEVs, which can guarantee a variety of LSSPs of similar nature in the following time-series forecasting investigations which shows key findings and its importance for the solar industrial forecast issue.

Spatial and Temporal Solar Potential Variation Analysis in Uganda Using Measured Data

The paper presents an analysis of spatial and temporal solar potential variations in Uganda. The solar radiation potential distribution was investigated based on measured data from 56 ground meteorological stations across Uganda from January 2015 to February 2022. The data were recorded after every 5-minute interval. The monthly average daily Global Horizontal Irradiance (GHI) was analysed using the spatial inverse distance weighting (IDW) interpolation technique in ArcGIS 10.7.1. The GHI distribution was found to have maxima at equinox and minimum between June and July. The average global horizontal irradiation is found to be 1680 KWh per year, with a daily variability below 10%. This is above the threshold for solar energy applications and with such low variability, large scale solar PV plants can be installed with minimum backup requirements. Northern Uganda receives the highest average daily global horizontal irradiation of 5.38 Whm–2 day–1, while Western Uganda receives 4.16 Whm–2 day–1, the lowest. The average AM/PM ratio depicted a value above 2 for all regions in Uganda and therefore, optimal solar energy exploitation for fixed systems favours eastern orientation. The central, eastern and northern Uganda which is 69.3% of the country has relief favourable for large scale solar PV power plants and CSP facilities.
 Keywords: GHI, IDW, Global solar radiation, Solar insolation, PV power plants, Uganda

Optimal wind-solar site selection using a GIS-AHP based approach: A case of Tunisia

Constructing large wind power plants (WPPs) and solar photovoltaic plants (SPVPs) is a significant long-term investment. Due to the various conflicting factors involved in the selection process, determining the most appropriate locations prior to deploying such facilities is of paramount importance. In this paper, we propose a preliminary assessment of the most promising sites in Tunisia to host large-scale WPPs and SPVPs using geographical information systems (GIS) and multi-criteria decision-making (MCDM). A study of this kind, focusing on both resources, has not been conducted in Tunisia. An in-depth literature review has been conducted in order to determine suitability criteria as well as constraint factors. The analytical hierarchy process (AHP) is used to assign weights to the considered criteria; then, the final suitability maps are generated using the weighted overlay tool under ArcGis 10.8 software. The study findings indicate that there are large areas that are suitable for the deployment of large-scale WPPs and SPVPs, covering 3335 km2 (2.15 % of the total area) and 3815 km2 (2.57 %), respectively. The most suitable wind sites are scattered northwest to southwest, southeast, and to a lesser extent north. In contrast, ideal solar sites are mainly distributed in the central and southern regions of the country. Furthermore, it has been demonstrated that these designated locations are capable of providing an estimated annual energy of 40.896 TWh and 781.83 TWh for wind and solar, respectively. As a result of the adopted model in this study, policymakers could be more proactive in developing solar and wind farms. This would increase the possibility of Tunisia achieving its 2030 target.

Excess power rerouting in the grid system during high penetration solar photovoltaic

• One of the concerns on this implementation is imbalance supply and demand which resulting power congestion that might cause instability of power system operation. • This paper presents the algorithm to solve power congestion in the power line during high penetration solar photovoltaic (PV) to the grid. • In this study the optimization approach is done using multiple mitosis genetic algorithm. • Power flow simulation is done using Power system simulation for engineers (PSSE) software. • This study is useful to the planning division of power system engineer to consider the option to avoid power congestion in the grid before the integration of large-scale solar farm. Large scale solar PV plant has been actively implemented in many countries. One of the concerns on this implementation is imbalance supply and demand which resulting power congestion that might cause instability of power system operation. This paper presents the algorithm to solve power congestion in the power line during high penetration solar photovoltaic (PV) to the grid. In this study the optimization approach is done using Multiple mitosis genetic algorithm (MMGA) to choose the best line to receive the excess power from the congested line and the system used to test the algorithm for 3 different scenarios is IEEE 30 bus test systems. Power flow simulation is done using Power system simulation for engineers (PSSE) software. Simulation results show that the excess power exist in the power line during high penetration solar PV are solved by rerouting the excess power to the available best adjacent line found using MMGA. This study is useful to the planning division of power system engineer to consider the option to avoid power congestion in the grid before the integration of large-scale solar farm.

Characteristics of the foundation rocks using geophysical techniques: A case study for the Egyptian solar plant site, Aswan, Egypt

The main target of the present study is to investigate the foundation layers and the subsurface structures in an Egyptian solar plant site using geophysical techniques including the seismic refraction and Multichannel Analysis of Surface Waves (MASW). The studied solar park is situated at about 40 km to the north of Aswan city on the Aswan-Cairo highway road and is classified as the largest solar plant in Africa and worldwide. Due to its location in the vicinity of the most prone earthquake area in Egypt (Aswan seismic zone); it is imperative to mitigate the earthquake hazard in this region. The geophysical results show that the subsurface foundation in this site is primarily composed of two layers. The upper one is loose and incompetent soil sediments that extend down to about 10 m depth with P-wave velocity ranging from 400 to 1000 m/s and shear-wave velocity ranging from 260 to 550 m/s. The deeper section is considered the main foundation layer with velocities ranging between 650 and 1900 m/s and from 350 to 950 m/s for P-wave and shear-wave, respectively. The average shear-wave velocities calculated for the topmost 30 m (Vs30) vary almost between 319 and 834 m/s; thereby the studied site is primarily ranked into classes C&D (180-360 m/s & 360-760 m/s, respectively) according to the National Earthquake Hazards Reduction Program (NEHRP) soil classification. Additionally, the southwestern and southeastern zones of the site area are characterized by maximum velocity values, relative high values of rock densities, rigidity or shear modulus “μ”, Standard Penetration Test (N-Value), ultimate bearing capacity and allowable bearing capacity, while the low values are observed through the northern and middle sectors across the area. This study an integral part of many works being carried out delineating the subsurface foundation structures around the solar plant and allows the most appropriate sites for constructing the renewable energy plants to be sited away from the highly hazards prone areas.

Adaptive Unit Protection for Lines Connecting Large Solar Plants Using Incremental Current Ratio

Control schemes in a solar plant complying with different grid codes modulate the output voltage and current significantly during the fault. In this article, the issue with conventional current differential approaches for the line connecting the large solar plant is analyzed and a new protection technique using both end incremental current phasors is proposed. The proposed method uses two criteria to identify the internal faults in such connectivity. The first criterion is based on the ratio of both end incremental phase current phasors, and the second one uses the magnitude ratio of positive sequence incremental currents. Both the criteria are adaptive to line terminal currents and complement each other enriching the method applicable for any system condition. The performance of the proposed method is tested for different internal and external fault cases and found to be accurate. The compatibility of the proposed method is also validated using a real-time simulator. Comparative assessment with conventional current differential techniques reveals the superiority of the proposed approach.

Techno-economic assessment of application of particle-based concentrated solar thermal systems in Australian industry

Australia has significant areas with high quality solar resources, but the requirement for large scale solar thermal plants to be financially competitive in the electricity market appears to have hindered uptake. Industrial use of heat provides an alternative route to market where the technology is not impacted by poor efficiencies in converting heat to electricity and an appropriate scale can be applied to the demands of a specific site. A re-examination of prior industrial energy use studies in Australia was used in combination with solar data and published data on industrial sites to identify three specific industrial sites for case studies. These sites were selected to cover applications in three industries with varying scale and temperature requirements. The primary solar technology selected utilizes a particle receiver on a tower with associated storage and heat exchanger for hot water/steam production or heating a gas reactor. The wide range of temperatures possible with this technology appears to be desirable for development of a general-purpose industrial heat system. Comparison with parabolic trough systems that are commercially available was conducted for cases where the required temperatures were appropriate. In all assessments, the optimized solar plant designs approach cost competitiveness with the estimated cost of natural gas purchase for the relevant locations and industrial scales. In smaller and lower temperature applications, parabolic trough systems are likely to be appropriate conventional choices, but the particle system exhibited a high degree of flexibility across multiple sites and applications, which is encouraging to future commercial application.

Model Predictive Control of the Mojave solar trough plants

The size of the current commercial solar trough plants poses new challenges in the applications of advanced control strategies. Ensuring safe operation while maintaining the temperature around an adequate set-point can lead to substantial gains in power production. Furthermore, the controller has to take into account the steam generator constraints to avoid trips leading to production losses.Model Predictive Control algorithms have proved to perform well when controlling solar trough plants. In particular, many MPC strategies were developed and tested at the old experimental solar trough plant of ACUREX at the Plataforma Solar de Almería with excellent results.In this paper, a Model Predictive Control algorithm is presented to control the average temperature of the large scale solar trough plants Mojave Alpha and Mojave Beta. This controller takes into account steam generator constraints in order to ensure safe operation. Several tests under different conditions have been carried out at the actual plants. Results show that the controller performs well on clear and cloudy days in spite of the great size of these plants.

High-frequency validation of predictions for energy production from large solar PV plants

The solar energy source is characterized by variability, intermittency, and unpredictability. The annual average direct normal irradiance and global horizontal irradiance only gives a rough estimation of the amount of energy that can be harvested by a solar photovoltaic plant. It is however also relevant to quantify the variability of the energy production, which is not only the result of alternating daylight and night time but also to accept variability from one day to another due to weather and seasonality. A design that permits a more stable controllable output is preferable because it reduces the need for external energy storage by batteries. Here we quantify the coefficient of variability of existing photovoltaic plants, and compare it with the coefficient of variability of the resource, to validate solar PV plant models.

Assessment of organic Rankine cycle configurations for solar polygeneration orientated to electricity production and desalination

This work addresses the polygeneration concept integrating concentrating solar power (CSP) with an organic Rankine cycle (ORC) to produce electricity and drinking water by hybrid desalination process combining reverse osmosis (RO) and low-temperature multi-effect distillation (LTMED). Experiments carried out on a bench scale RO pilot led to determine optimal operating parameters as well as options to mitigate the main limiting factors of this technology by hybridizing with LTMED. These data helped to simulate a large scale solar polygeneration plant integrating parabolic trough collectors as CSP technology and a hybrid RO-LTMED system as desalination technology. Various ORC design proposals were simulated and the optimal configuration was pointed out on the basis of thermodynamic criteria (energy efficiency and exergy destruction) and an economic analysis by using two working fluids: an alkane commonly admitted as good candidate and an ester proposed here as green alternative. Results obtained in this work contribute positively to extending the solar polygeneration for desalination and production of energy leading to future sustainable plants.

NpTrack: A n-Position Single Axis Solar Tracker Model for Optimized Energy Collection

The single axis solar tracker based on flat panels is used in large solar plants and in distribution-level photovoltaic systems. In order to achieve this, the solar tracking systems generally need to work by tracking the sun’s position with dozens, maybe hundreds of movements along the day with a maximal known tracking error within the specifications. A novel model is proposed along this work based on the control of the angle deviation within a (polar) single axis configuration. This way an optimization of the harnessing of solar energy can be achieved with as few panel displacements as possible in order to decrease the wear in the mechanical parts of the equipment and the energy consumed by it. This tracking approach was implemented with as few as seven positions along the day and got an estimated theoretical value of 99.27% of the total collected energy in a continuous tracking system. Regarding an annual average basis, it would be about 96.5% of a dual axis system according to the proposed model. The novelty of the model is related to a tradeoff between the gain with the simplicity of a single axis n-position tracking and the solar energy loss associated.

Technological Advancement of Solar Thermal System Desalination Process – A Review

Increase in demand for drinking water due to growth in world population and industrialization has lead route for innovating new technologies for purifying sea water. Desalination by conventional energy source increases the emission of greenhouse gases and leads to global warming. As a solution for pollution and water scarcity, solar desalination techniques are incorporated worldwide for converting brackish water into portable water using solar power. Solar power helps water purification via solar thermal systems and also using solar photovoltaic panels which provide electric supply. This review article consolidate the solar thermal energy based small, medium and large scale solar desalination plants for extracting pure water. The environmental benefits and the futuristic challenges of utilizing solar thermal system for purification of water is also highlighted.

Comprehensive Evaluation of Photovoltaic Solar Plants vs. Natural Ecosystems in Green Conflict Situations

This study aims to develop a comprehensive method for evaluating the environmental cost/benefits of photovoltaic (PV) solar plant installation versus conserving natural ecosystems. First, the positive and negative impacts of installing PV solar plants in regions with natural ecosystems are reviewed. For focus and quantification, climate change mitigation and economic benefit were considered as benefits, and the loss of carbon sinks and biodiversity as well as disaster risk were considered as negatives. These items were also integrated as external costs using a life-cycle assessment method, and a ratio of positive versus negative impacts (P/N ratio) was developed, as part of our evaluation. The method was applied to a case study in Hyogo Prefecture, Japan, where 361 large PV solar plants have been installed in areas that previously supported natural ecosystems. Prior to the PV installation, 25.5% of the plants were cleared from the natural ecosystem. Consequently, the annualized benefits (costs) for these Hyogo plants were estimated to be 101.16 (73.88) million USD, which yielded a P/N ratio of 1.37, indicating that their benefits outweighed their costs. An economic benefit was found to be one of the parameters that significantly influenced the P/N ratio.

Design and Control of Medium-Voltage Multilevel Converter for Direct Grid Integration of Photovoltaic System

This paper deals with the design and control of a medium voltage cascaded H-bridge (CHB) multilevel converter for the direct grid integration of a large photovoltaic (PV) system. It presents the design considerations for selecting an optimum number of levels in the multilevel converter, which are to be both efficient and economical. This system is designed for medium voltage, 11 kV, and hence it can be directly interfaced with the grid without a step-up transformer. It contributes large cost savings in the installation, operation and maintenance of the large solar plant. With the increased number of levels, the converter output voltage waveform is a good approximation to the sine waveform. Therefore, the total harmonic distortions (THDs) of the output AC converter voltage and the grid current are reduced, which significantly improves the power quality of the output voltage waveform reducing the size and hence the cost of the filter. The effect of an increased number of levels on THDs is also studied. The control employed is a decoupled control with the synchronous reference frame—phase-locked loop (SRF-PLL), and a 19-level cascaded converter is operating at the low switching frequency. The separate improved perturb and observation (P&O) maximum power point tracking (MPPT) algorithm is used for tracking the maximum power from each array of the multistring solar photovoltaic (SPV) system. Both steady-state and dynamic performances of the system are simulated in MATLAB/ Simulink environment and validated in accordance with the IEEE-519 standard. A substantial reduction in THDs of the output AC converter voltage and the grid current, with increased number of levels, is observed in this system.

District Heating De-Carbonisation in Belgrade. Multi-Year transition plan

A large share of the city of Belgrade is heated by a District Heating network. Established in 1965, the network delivers 3.6 TWh to more than 20 million square meters of households industries and businesses, by means of a 1460km-long network. The system has been continuously upgraded and adapted to new technologies and already operates at relatively low temperature, with modernized substations. However, the delivered heat is still produced mainly by means of carbon intensive technologies. Conscious of the need to de-carbonise the city, a multi-year transition plan was established, where large investments have been secured, comprising greater interconnection levels, installation of large solar thermal plants and waste incineration plants, and the conversion of a power plant into CHP, among others. In this paper, the criteria for the selection of the technologies, the identification of enabling investments, interaction with stakeholders, securing of financing, and status of the plan are presented. After the execution of the de-carbonisation roadmap, it is expected that the DH system will reduce its carbon intensity by 50%.

Comparative Study of 16 Clear-Sky Radiative Transfer Models to Estimate Direct Normal Irradiance (DNI) in Botucatu, Brazil

AbstractThe interest of the direct normal irradiation (DNI) estimation is important in the evaluation of the solar potential and, consequently, for data correction and expansion of the historical series. In this study, a review of the performance of 16 models of radiative transfer was performed. These models are used to estimate DNI on a clear day in Botucatu/SP region located in Brazil. The revised models are categorized into two classes: simple models (11 models: ASH, MAJ, ALLEN, GH, P1, HLJ, FU, KU, H1, IP, and INC) and complex models (five models: BIRD, IQ, MRM5, P2, and YANG). The evaluation methodology used here is consistent with the literature. The input parameters were estimated and a statistical analysis using relative-mean-bias-error (rMBE), root-mean-square-error (rRMSE), and mean absolute percentage error (MAPE) indicators were performed to validate those models. The results indicate that the complex models (that require more atmospheric inputs) generally performed better than simpler models. Despite the consistent limitations in the use of estimated parameters, the performance of the models can be considered satisfactory. The best performances are highlighted for models MRM5 and YANG. Simple models ASH and IP performed similar to complex models. These results were confirmed using frequency distribution and the cumulative frequency analysis. These results are important for engineers of solar systems to use the best model and select the most suitable locations for installing a small or large solar plant.