Operation Of Solar Power Plants Research Articles

DEVELOPMENT TRENDS OF SOLAR POWER ENGINEERING BASED ON THE MATERIALS OF THE SCIENTIFIC AND PRACTICAL CONFERENCE «RENEWABLE ENERGY AND ENERGY EFFICIENCY IN THE 21

The main results of the reports at the "Solar Energy" section were considered and summarized, in particular, one of the areas of solar energy engineering - solar power generation. Specialists from Ukraine and the Republic of Uzbekistan took part in the work of the section in this field. A total of 32 reports were presented, focusing on topics such as the implementation of distributed generation facilities based on photovoltaic systems, improving the energy efficiency of solar power plants, etc. The reports demonstrated the primary trends to highlight the issues of building and operation of energy-efficient solar power plants in today's realities.

Experimental analysis on improving heat storage efficiency of high-temperature packed bed system using spherical capsules filled with MgCl2–KCl–NaCl/Al2O3 nanoparticles composite phase change material

While thermal energy storage (TES) systems are becoming crucial to the stable operation of solar power plants, molten salt packed bed thermal energy storage (PBTES) systems attracted widespread attention due to their wide operating temperature range and low cost. However, achieving high-efficiency thermal storage systems is still a datum challenge to meet the higher energy demand, as well as sustainable development and utilization of renewable energy systems. This study developed spherical capsules employing nanocomposite salts (MgCl2–KCl–NaCl/Al2O3 nanoparticles) as composite phase change materials to experimentally study the heat storage process of a high-temperature PBTES prototype experimental system. Also, the heat storage performance of the PBTES system under different operating conditions is further investigated. The results showed that the nanocomposite salt gradually melted along the flow direction of the heat transfer fluid by exhibiting three-stage characteristics including solid phase sensible heat, phase change latent heat, and liquid phase sensible heat. Also, the temperature difference inside and outside the capsules showed the characteristics of peak-trough-peak. The PBTES system reached a heat storage density of 1290.51 MJ m−3 at a thermal efficiency of 86.95 %. The average heat storage rate increased by 49.55 % and the heat storage time was shortened by 29.67 % when the blower speed was increased from 800 r·min−1 to 1200 r·min−1. The experimental results implied that the PBTES system encapsulating nanocomposite salts has excellent thermal performance. This study demonstrated solving the problems of insufficient thermal energy supply in time or space and improving energy utilization could result in a high-efficiency thermal storage system.

Reconstructing 10-km-resolution direct normal irradiance dataset through a hybrid algorithm

Evaluating, mapping, and monitoring high-quality Direct Normal Irradiance (DNI) is crucial for the design, financing, and operation of solar power plants, especially those utilizing concentrating technologies. In China, limited number of first-class meteorological stations provide DNI observations. To bridge this gap, this study has reconstructed a comprehensive 41-year (1982–2022) daily DNI dataset for China (CHDNI). This dataset integrated CMA ground-based observations with ERA5 and MERRA-2 reanalysis data, employing a spatial resolution of 10 km. The data was processed using the REST2 radiation transfer model combined with Stacking ensemble machine learning. Validation with ground-based measurements indicated that the Stacking model exhibited high and consistent performance. This was evidenced by its sample-based cross-validation results, showing a correlation coefficient (R) of 0.92, a root-mean-square error (RMSE) of 32.04 W/m2, a mean absolute error (MAE) of 23.68 W/m2, and a global performance indicator of 3.86. Among the four analyzed DNI products (CERES, ERA5, SWGDN, and CHDNI), CHDNI demonstrated the closet alignment with ground observations, evidenced by the least deviation (MAE = 21.67 W/m2 and RMSE = 31.00 W/m2) and the highest R value (0.92). Aerosol optical depth and cloud cover emerged as the primary factors influencing the quality and accuracy of DNI products under clear-sky and total-sky conditions. The spatial distribution of DNI across China is complex, showcasing DNI values ranging from 25.82 W/m2 to 194.22 W/m2, with an average value of 98.08 W/m2 over 41-year. This dataset is a valuable resource for analyzing regional climate change, photovoltaic applications, and solar energy resources assessment.

ASPECTS OF THE FURTHER DEVELOPMENT OF PHOTOENERGY ACCORDING TO THE MATERIALS OF THE SCIENTIFIC AND PRACTICAL CONFERENCE «RENEWABLE ENERGY AND ENERGY EFFICIENCY IN THE 21st CENTURY» 2023

The main results of reports at the "Solar Energy" section were considered and summarized, in particular, one of the areas of solar energy – photoenergy. Specialists from Ukraine, Poland, the Czech Republic and the Republic of Uzbekistan took part in the work of the section in this area. A total of 22 reports were presented, which related to the issues of increasing the energy efficiency and reliability of the operation of solar power plants, the peculiarities of the operation of solar autonomous power plants and installations, new technologies for the production of photo modules, etc. For the most part, the reports focused on the creation and operation of energy-efficient and reliable solar power plants.

An interpretable horizontal federated deep learning approach to improve short-term solar irradiance forecasting

Solar irradiance forecasting is critical in the planning and operation of solar power plants for production scheduling, energy trading, and maintenance planning. Accurate solar irradiance forecasting is crucial for efficient and stable power systems. Various deep learning (DL) methods have been researched in solar irradiance forecasting because of their powerful capabilities of nonlinear mapping. However, traditional DL models face challenges with small sample sizes, irradiance fluctuations, and data privacy concerns. On this foundation, it is also critical to ensure the interpretability of artificial intelligence (AI) models, as interpretable and trustworthy predictive models can help operators make effective decisions. Focusing on the above-mentioned issues, a privacy-preserving, interpretable, and DL-based model is proposed to improve the forecast accuracy of solar irradiance while ensuring the data available but not visible to each participant and prediction comprehensibility. This model is constructed by horizontal federated framework (HFF), self-attention (SA) mechanism, convolutional neural network (CNN), and long short-term memory (LSTM) network, named HFF-based SA-CNN-LSTM. A series of comprehensive experiments spanning various climate regions are designed to assess model performance under different federated conditions. The experiments show that this method significantly improves forecasting accuracy, especially in scenarios with incomplete data and highly fluctuating irradiance when federated with other datasets, and the model exhibits interpretability, adjusting attention for precise predictions at different time points. Moreover, the effects of different federated scales on the predictive performance of the target model are fully discussed for future practical applications. These findings hold significant promise for enhancing the accuracy of irradiance forecasting, contributing to energy efficiency, grid stability, and data privacy.

ЕКСПЕРИМЕНТАЛЬНИЙ АНАЛІЗ РОБОТИ СОНЯЧНИХ ПАНЕЛЕЙ ІЗ РІЗНИМИ ХАРАКТЕРИСТИКАМИ

Abstract. The article reviews the current state and prospects for the development of solar energy devices and systems. The analysis of the main directions for improving the operation of solar power plants was carried out: improving the design of solar panels; power optimizer using trackers; a decrease in the temperature of the SP; surface cleaning of SP; options for connecting SPs to each other; SP modulation. A comparison of these directions was performed, and the perspective of the method of reconfiguration of solar panels was shown. The results of an experimental study of solar panels are presented. Suggestions for further research into solar energy systems are given. It was concluded that it is necessary to analyze the work of the joint venture under the same external factors. Keywords: solar energy; solar power plants, solar panel, power optimizer, volt-ampere characteristic, efficiency improvement

Disturbance rejection model predictive control for solar collector fields based on fast Fourier transform

Stability of fluid temperature in the collector field guarantees for the safe operation of a trough solar power plant. As a control algorithm that handles process characteristics, the model predictive control (MPC) algorithm provides good effectiveness in temperature control of the collector field. In order to compensate for model errors and unmeasurable disturbances, this paper proposes a novel model predictive control algorithm based on the Fast Fourier Transform (FFT) to control the temperature of the collector field. During the control process, the dominant frequencies of model deviations and disturbances are acquired by the FFT. Then, the effects brought by these factors can be estimated and compensated in advance by the expansion of the prediction model and the calculation of the estimator. Simulation results show that the proposed FFT-based MPC algorithm has good disturbance rejection ability, especially for periodic disturbances.

Перспективы Крайнего Северо-Востока России на производство "зеленого" водорода с использованием климатических источников возобновляемой энергии

For the first time, Russia's Far North-East prospects for hydrogen production by the method of water electrolysis, using climatic energy sources and ultra-fresh mountain-river water, are comprehensively assessed. Taking into account the identified regional features, it is calculated that, with the current technical level of development, the amount of hydrogen produced in the region will be controlled just by the amount of used ultra-fresh mountain-river water. Thus, using no more than 10 percent of the general runoff (18 billion m3 water), it is possible to annually obtain 2x109 tons of "green" hydrogen through the operation of wind and solar power plants. To accommodate the latter, it is ecologically feasible to use the areas in mountain tundras and forest-tundras on flattened and flat watersheds.

Organisation of the Structure and Functioning of Self-Sufficient Distributed Power Generation

During the operation of solar and wind power plants, it is necessary to solve issues related to the guaranteed capacity of these plants, as well as the frequency stabilisation in the power system where they operate, and maintain an operating mode of self-sufficiency conditions. One of the solutions to these problems is the use of energy storage systems. This article proposes a mathematical model for the study of frequency and power regulation processes in power systems with distributed generation, which includes renewable energy resources and energy storage systems. The novelty of the model lies in the possibility of determining energy cost indicators based on instantaneous energy power data. The model allows us to estimate the conditions under which distributed generation becomes self-sufficient. The results of the model calculations of two variants of power system operation, which includes wind generators with a capacity of 1500 MW, demonstrate the ability of the proposed model to accurately reproduce the dynamics of the frequency stabilisation process. The calculation results of the energy-economic indicators of a real power system combined with a powerful subsystem of wind generation and a battery-type energy storage system prove the competitiveness of self-sufficient renewable energy power plants.

Solar Electricity Energy: Utilization of Renewable Energy Sources to Realize a Sustainable Campus at UIN Raden Fatah Palembang

Universities play an essential role in achieving Indonesia's 2060 carbon-neutral target. Emissions in the campus are mainly sourced from its electrical energy, transportation, and water use, along with other wastes. Electrical energy from solar is renewable energy, free from pollutants and noise pollution. This paper examines the sustainable energy performance of solar energy at the Universitas Islam Negeri Raden Fatah Palembang (UINRFP) and its development efforts. From August 2022 to March 2023, a solar power plant (SPP) operation with a capacity of 7.74 kWp has generated 6,281.5 kWh of electricity (28.55 kWh/day). Using a radiation factor of 0.8 and an equivalent sun hour of 4.61 (3-5 hours/day), the rooftop capacity of all buildings on Jakabaring Campus is 2,000 kWp, the potential of SPP electricity of UINRFP will exceed 39.3% compared to the 2022 electricity demand. If the capacity is, half the electricity generated from renewable energy meets 70% of the demand. Gradually UINRFP continues to develop its energy sources towards sustainable energy. The development of other research-scale renewable energy with hybrid solar energy and wind power for the aesthetic lighting function on the rectorate building has the potential to generate 290 kWh/year. In addition, micro-hydro energy sources from campus canals (water volume ±9,400 m3) and biomass are potential renewable energy sources at UINRFP for a sustainable campus in the future and contributing to reducing the impact of climate change.

Performance analysis of MW-scale grid connected rooftop and ground-mounted solar power plants installed in Assam, India

Solar energy-based electricity generation has become an essential component of sustainable development and meeting the growing demand for energy. A study is conducted to compare the performance of rooftop and ground-mounted solar power plants installed in Assam, India. The study found that ground-mounted plants generated an average of 3.41 kWh per kWp of energy per day, while rooftop plants generated 2.89 kWh per kWp. The study also observed that rooftop solar power plants had non-operating days due to inverter faults, grid failures, and poor weather conditions, which were 1.1 and 0.95 days, respectively. The capacity factors were 14.2 % and 11.4 %, while the performance ratios were 77.8 % and 70.1 % for ground-mounted and rooftop plants, respectively. The average system efficiency of ground-mounted plants and rooftop plants is 12.59 ± 0.26 % and 11.88 ± 0.11 %, respectively. The study used the Weibull distribution function to describe the daily normalized energy generation frequency curve, which revealed a peak probability of 0.38 at a daily normalized energy generation of 2.9 kWh per kWp for rooftop plant and 0.34 at a daily normalized energy generation of 3.4 kWh per kWp for ground-mounted plant. The installation of a solar power plant has resulted in an average reduction of Rs. 43.7 lakhs per year in the University's electricity bill. This study demonstrates the successful operation of rooftop solar power plants, which not only reduces the electricity expenses of organizations but also has a positive impact on sustainability.

Maximizing Annual Energy Yield in a Grid-Connected PV Solar Power Plant: Analysis of Seasonal Tilt Angle and Solar Tracking Strategies

Harnessing the abundant solar resources holds great potential for sustainable energy generation. This research paper delves into a comprehensive analysis of seasonal tilt and solar tracking strategy scenarios for a 15 MW grid-connected PV solar power plant situated in Kandahar province, Afghanistan. The study investigates the impact of fixed tilt, seasonal tilt, SAHST (single-axis horizontal solar tracking), and SAVST (single-axis vertical solar tracking) on energy yield, considering technical, economic, and environmental aspects. In the first scenario, a fixed tilt angle of 31 degrees was employed. The second scenario explored the use of seasonal tilt angles, with a summer tilt angle of 15 degrees and a winter tilt angle of 30 degrees. The third scenario analyzed SAHST. Finally, the fourth scenario focused on implementing SAVST. SAVST proved to be an exceptional solution, showcasing a remarkable increase in annual energy yield, and generating an additional 6680 MWh/year, 6336 MWh/year, and 5084 MWh/year compared to fixed, seasonal, and SAHST scenarios, respectively. As a result, surplus energy yielded an income of USD 554,440.00 per year compared to fixed tilt. However, the investment cost for the solar tracking system amounted to USD 1,451,932, accompanied by an annual operation and maintenance cost of 0.007 USD/W/year. The analysis revealed a promising payback period of 3 years, confirming the economic feasibility of this investment. The findings underscore the effectiveness of different strategies for optimizing solar power generation in the Kandahar region. Notably, the installation of SAVST emerged as an influential solution, significantly increasing power production. These research outcomes bear practical implications for solar tracking strategies for addressing the load challenges faced by Kandahar province and offer valuable insights for the operators and operation of solar power plants in similar regions.

Global Horizontal Irradiance in West Africa: Evaluation of the WRF-Solar Model in Convection-Permitting Mode with Ground Measurements

Abstract The number of solar power plants has increased in West Africa in recent years. Reliable reanalysis data and short-term forecasting of solar irradiance from numerical weather prediction models could provide an economic advantage for the planning and operation of solar power plants, especially in data-poor regions such as West Africa. This study presents a detailed assessment of different shortwave (SW) radiation schemes from the Weather Research and Forecasting (WRF) Model option Solar (WRF-Solar), with appropriate configurations for different atmospheric conditions in Ghana and the southern part of Burkina Faso. We applied two 1-way nested domains (D1 = 15 km and D2 = 3 km) to investigate four different SW schemes, namely, the Community Atmosphere Model, Dudhia, RRTMG, Goddard, and RRTMG without aerosol and with aerosol inputs (RRTMG_AERO). The simulation results were validated using hourly measurements from different automatic weather stations established in the study region in recent years. The results show that the RRTMG_AERO_D01 generally outperforms the other SW radiation schemes to simulate global horizontal irradiance under all-sky condition [RMSE = 235 W m−2 (19%); MAE = 172 W m−2 (14%)] and also under cloudy skies. Moreover, RRTMG_AERO_D01 shows the best performance on a seasonal scale. Both the RRTMG_AERO and Dudhia experiments indicate a good performance under clear skies. However, the sensitivity study of different SW radiation schemes in the WRF-Solar model suggests that RRTMG_AERO gives better results. Therefore, it is recommended that it be used for solar irradiance forecasts over Ghana and the southern part of Burkina Faso.

Methods and software for anomalies searching in the telemetry data of a solar power plant based on the normalized power analysis

Objectives. In connection with the increase in the number of solar power plants, the automation of monitoring their performance becomes an urgent task. The search for anomalies in the operation of solar power plants is one of the main components of monitoring. The purpose of the study is to develop new methods and software algorithms for finding anomalies in the operation of solar panels based on the results of a digital twin created and trained according to the telemetry data of a solar power plant.Methods. The developed technique is based on statistical studies of deviations of power values at the point of maximum efficient operation of the solar panel calculated by the digital twin. In addition, a normalized value of the power in the maximum efficient operation of the solar panel was introduced for more accurate clustering and anomaly search.Results. Using the developed method of static search for half a year of observations, 18 anomalies were detected in the operation of the solar panels of the power plant. All cases are analyzed for the causes of anomalies in the operation of solar panels.Conclusion. It has been established that when using normalized power values in the analysis of deviations at the point of maximum power PN, it is possible to detect abnormal operation of individual panels. The level of deviation of the normalized values at the point of maximum power was calculated, indicating the presence of an anomaly in the operation of solar panel.

Geographic information system‐based prediction of solar power plant production using deep neural networks

AbstractThe study aims to predict solar energy generation to ensure the successful operation of solar power plants. This objective is crucial in light of the increasing energy demand, global warming concerns, and greenhouse gas emissions. To achieve this, the study employs multiple linear regression and feature selection techniques to calculate energy generation. Additionally, long short‐term memory (LSTM) is used to predict energy generation levels based on climate conditions. Furthermore, the spatial distribution of energy generation is analyzed using inverse distance weighting. The results of the study reveal that temperature, solar radiation, relative humidity, wind speed, wind direction, and vapor pressure deficit are the most significant parameters for predicting energy generation. The LSTM method proves to be highly accurate in predicting fluctuating energy generation patterns. Notably, the southern regions of the study area exhibit a greater potential for energy generation compared to the northern regions. Approximately 30% of the region generates over 1400 kWh, with the southern areas, characterized by hot and dry climates, producing around 1500 kWh, while the northern regions, with cold and humid climates, generate approximately 1100 kWh.

Experimental analysis of a novel confined bed system for thermal energy storage

Thermal energy storage (TES) is an essential subsystem for the uniform operation of concentrated solar power (CSP) plants. A sensible heat storage system based on a novel confined bed of small particle size granular material was experimentally evaluated. The bed of regular silica sand was mechanically confined between a bottom and a top perforated plate gas distributor, to prevent the motion of particles even for gas velocities above the minimum fluidization velocity of the solids, operating the bed under a fixed or packed bed regime. The discharge process of the confined bed was experimentally analyzed, preheating the granular material at 300–320 °C and supplying various volumetric flow rates of cold air through the bottom distributor. During the discharge process, the temperature of the bed was segregated, obtaining a high temperature zone at the top region and a low temperature zone at the bottom region of the bed. These regions are separated by a thermocline that evolves in the upwards direction as the discharge process progresses. The temperature distribution in the bed and the total pressure drop of the TES system were monitored during the tests. For all cases, the temperature of the bed at different heights evolves as in a fixed bed, confirming the proper confinement of the granular material. The thermocline velocity depends on the volumetric flow rate of cold air, obtaining a discharge time for the temperature located at the exit of the system of around 50, 40, and 30 min for air volumetric flow rates of 700, 900, and 1100 Nlpm, respectively, using 55 kg of regular silica sand as granular material. The experimental results of the evolution and distribution of temperature in the bed were compared with an analytical model of the process for a fixed/packed bed regime of operation, resulting in a good agreement between the experimental measurements and the numerical predictions.

НАКОПИЧУВАЧІ ЕЛЕКТРИЧНОЇ ЕНЕРГІЇ

The article provides an analytical review of reverse-acting electric energy storage devices that can be used to solve systemic problems of the United Energy System of Ukraine. The need for the use of electric energy storage is due to the existing shortage of maneuverable capacities of the United Energy System and the construction of solar and wind power plants, which, due to the stochastic mode of operation, are a significant destabilizing factor. Due to the lack of market pricing mechanisms, the possibility of adjusting the rates of the "green" tariff, and the decrease in the cost of solar and wind power plant technologies, a rapid increase in their number and capacity has been observed in recent years. At the beginning of 2021, the installed capacity of solar power plants was 6.87 GW, and wind power plants – was 1.31 GW, and by 2030, their growth is planned to be 10.5 GW and 5.0 GW, respectively. Without adequate regulatory capacity, this can lead to catastrophic consequences, as happened in South Australia. The conducted review and analysis showed that the dominant technology of electric energy storage in the world is hydro-storage power plants, the implementation costs of which are about 260 USD/kWh. Compressed air energy storage is the cheapest technology but needs to be located near the energy systems of natural caves. Accumulator systems of energy storage are developing at a fast pace, the costs of their implementation are 311-520 USD/kWh with a tendency to decrease by 2030 by about 25%. They are the most promising for work in energy systems. These storage devices can be used to regulate frequency and power, reduce electricity flows, reduce voltage fluctuations in electrical networks, consolidate daily schedules of electrical loads, prevent overloads of electrical networks and transformers, increase the reliability of electricity supply, increase the stability of the operation of solar and wind power plants, as well as for commercial purposes in various segments of the electricity market of Ukraine. Keywords: energy system, electricity storage, power, capacity.

Multidefect Detection Tool for Large-Scale PV Plants: Segmentation and Classification

Unmanned aerial vehicles (UAVs) with high-resolution optical and infrared ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IR</i> ) imaging have been introduced in recent years to perform inexpensive and fast inspections in operation and maintenance activities of solar power plants, reducing the labor needed, while lowering the on-site inspection time. Even though UAVs can acquire images extremely quickly, the analysis of those images is still a time-consuming procedure that should be performed by a trained professional. Therefore, a computer vision approach may be used to accelerate image analysis. In this work, a dataset of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IR</i> images was created from a 10-MW solar power plant and a comparative analysis between mask R- convolutional neural network (CNN) and U-Net was performed for two experiments. Concerning the defective module segmentation, the mask R-CNN algorithm achieved a mean average precision at intersection over union (IoU) = 0.50 of 0.96, using augmentation data. Regarding the segmentation and classification of failure type, the algorithm reached a value of 0.88 considering the same evaluation metric and data augmentation. When compared to the U-Net in terms of IoU, the mask R-CNN outperformed it with 0.87 and 0.83 for the first and second experiments, respectively.

РАЗРАБОТКА И ИССЛЕДОВАНИЕ СПОСОБОВ ПОВЫШЕНИЯ ЭЛЕКТРОЭНЕРГЕТИЧЕСКОЙ ЭФФЕКТИВНОСТИ СОЛНЕЧНЫХ ЭЛЕКТРОСТАНЦИЙ В УСЛОВИЯХ СЕВЕРА

The article is devoted to the issues of development and research results of ways to improve the electric power efficiency of solar power plants in the conditions of the North. Field studies of this work were carried out during 2020-2022 in the central part of Yakutia. In the course of the research, key photoelectric, electrical and technical and economic regularities, statistical methods for processing experimental data, including the method of calculating the student’s t-criterion, were applied. Algorithms have been developed for conducting field studies to idеntify the nature of the influence of climatic factors of the North on the functioning of solar power plants. The indicators of the influence of climatic factors of the North on the operation of solar power plants are obtained. А model for assessing the energy potential of solar power plants has been developed, taking into account the nature of the influence of climatic factors of the North, the reliability of calculations of which increases by 5.61% and approaches the actual indicators of electricity generation from existing solar power plants. As a result of the research, ways have been developed to reduce the negative impact of the climatic factors of the North on the functioning of solar power plants, allowing to increase their production by 15 ... 25%. Positive indicators of the effect of the introduction of the developed methods on the parameters of operational reliability, technical, economic and environmental indicators have been obtained. The results of the research can be applied when updating the guidelines for improving the electric power efficiency of mini- and microgrid facilities operating with the use of solar power plants in the conditions of the North.

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

Parabolic Trough Collectors (PTCs) are the most mature, reliable and widespread among Concentrated Solar Power (CSP) technologies for electricity generation. The conventional power plants relying on PTCs use synthetic oil as Heat Transfer Fluid (HTF) which has limited life span, has limited operation temperature, is expensive and harmful to the environment. In the present research work, a new perspective has been developed to directly generate steam in the collectors, eliminating the need for HTF in the solar field and avoiding auxiliary heat exchangers. A mini hybrid Direct Steam Generation PTC power plant having a boiler as a backup that can be operated with biogas or natural gas is installed at Ecole Nationale d'Ingénieurs de Tunis (ENIT) within the framework of REELCOOP project (Renewable ELectricity COOPeration). The description, commissioning and operation of the solar plant are presented in this paper. The plant is designed and tested under real-life operating conditions in the south Mediterranean region. The feasibility of the DSG process in horizontal parabolic trough collectors has been confirmed and an important know how has been acquired regarding the operation of DSG solar plant. The main instructions for the operation of the solar plant have been presented including start-up and shutdown procedures of the plant, as well as the safety measures to be considered.The development of this plant is aimed to address the challenge of coupling intermittent solar radiation and the presence of a two-phase fluid in the absorber tubes. An important know how has been acquired regarding the operation of DSG solar plants in solar only mode and in hybrid mode which allowed to balance strengths and weaknesses of solar and biogas/natural gas technologies. By combining both systems, we have tackled the problem of the controllability of the energy supply while exploiting as much as possible renewable sources.