PV Station Research Articles

The efficient strategy of operating the active cooling systems incorporated with photovoltaic panels for the three climatic regions: A case study

ABSTRACT Photovoltaic stations in Algeria are considered an effective solution to overcome the problem of its lack of electrical power and achieve the goals of sustainable development. The weather in Algeria is continental, it has three main climate zones from north to south, and the climate in Algeria is desert, which causes an increase in the temperature of photovoltaic modules and thus a decrease in their production of electrical power. Then the active cooling systems that use water as a cooling medium represent a good option to reduce the PV module temperature and thus increase electrical power generation rates. Due to the change in weather in Algeria from north to south and during the four seasons, in some periods, the operation of cooling systems is ineffective and leads to a decrease in the net output electrical power of photovoltaic stations. Therefore, this manuscript aims to develop an advanced strategy for operating active cooling systems incorporated with PV stations to achieve the highest net electrical power output from PV stations in Algeria. To achieve this goal, the theoretical study was conducted on three different regions in Algeria that express its continental climate, namely, Algiers (36°46′ N, 3°03′ E), northern Algeria, and Djelfa (34°40′ N 3°15′ E) in central Algeria and Ghardaïa (32°29′ N 3°40′ E) in southern Algeria, to get the optimal cooling strategies that achieve the highest net electrical power produced by PV stations. The simulation results presented that the average improvement in the electrical power generated from the PV panels incorporated with active cooling systems reached 15.1%, 17.8%, and 19.7% under the climate conditions of Algiers, Djelfa, and Ghardaïa, respectively. The optimal operating strategies of active cooling systems integrated with PV stations in Algeria increase the average net output electrical power of the PV stations by a rate reached 7.65%, 7.13%, and 4.91% for Algiers, Djelfa, and Ghardaïa, respectively.

Multimodel Ensemble Forecast of Global Horizontal Irradiance at PV Stations Based on Dynamic Variable Weight

Multimodel Ensemble Forecast of Global Horizontal Irradiance at PV Stations Based on Dynamic Variable Weight

Distributed Photovoltaic Output Prediction Using Machine Learning and Numerical Model Combined Method

Abstract In recent years, distributed photostatic (PV) has developed rapidly. Accurate prediction of distributed PV output can improve the reliable, efficient and economical grid-connected operation of distributed PV, and enhance the reliability of power supply. In this study, we first collected the datasets of distributed PV output and centralized PV station output in Dongan County, Yongzhou City, Hunan Province. Then, we analyzed the relationship between distributed PV station output and centralized PV output under different weather conditions, and constructed the centralized PV output prediction curve by combining machine learning and numerical prediction model, and finally obtained the distributed PV output prediction of the whole county. The results show that the correlation coefficient changes between the output of distributed PV stations and that of centralized PV stations under different weather scenarios (sunny, cloudy, etc.), but they all show a good consistency (the correlation coefficient of more than 0.6 accounts for more than 95% of the PV stations), indicating that the output change of centralized PV stations in one county can be used to characterize the output change of distributed stations. The distributed PV output prediction model built by LSTM and numerical model combined method has achieved a prediction accuracy of 90.4% for a single station and 94.31% for the whole county within 24 hours, both of which are 4%˜5% higher than the requirements of national standards. The model can be further extended to forecast the distributed PV output of the whole province.

A Sustainable Solution for Urban Transport Using Photovoltaic Electric Vehicle Charging Stations: A Case Study of the City of Hail in Saudi Arabia

As the global shift toward sustainable transportation gains momentum, the integration of electric vehicles (EVs) becomes imperative, necessitating a robust and environmentally friendly charging infrastructure. Leveraging the abundant solar potential in the region, this study examines the technical, economic, and environmental feasibility of deploying photovoltaic electric vehicle charging stations (PV-EVCSs) in Hail City, Saudi Arabia, as a case study. This study examines factors such as the energy demand, grid integration, and user accessibility, aiming to address the challenges and opportunities presented by the urban fabric. The proposed solar charging station network seeks to catalyze a paradigm shift toward a cleaner and more sustainable transportation ecosystem, embodying a forward-thinking approach to meeting the evolving needs of urban mobility in the 21st century. The analysis encompasses many scenarios, encompassing a range of car battery sizes, charger powers, and car slots per station. Zone 4 is identified as the most crucial area, where seven charging stations are needed to fulfill the expected demand in the absence of any private charging alternatives. The economic evaluation of the 1047.35 kWp PV system reveals an estimated conventional payback time of 11.69 years, accompanied by a return on assets of 10.17%. The system generates accumulated cash flows amounting to SR 7,169,294.62 over 30 years, while the estimated operational and maintenance expenses are predicted to be SR 50,000 per year. The overall investment cost for the solar PV and EV charging stations is SR 4,487,982. This cost is offset by the yearly electricity savings from solar and grid sources, which can reach up to SR 396,465.26 by year 30. This work presents a detailed plan for the future of sustainable transport. It combines technical, environmental, and economic aspects to promote a cleaner and more sustainable urban mobility system.

An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques

Integration renewable energy sources into current power generation systems necessitates accurate forecasting to optimize and preserve supply–demand restrictions in the electrical grids. Due to the highly random nature of environmental conditions, accurate prediction of PV power has limitations, particularly on long and short periods. Thus, this research provides a new hybrid model for forecasting short PV power based on the fusing of multi-frequency information of different decomposition techniques that will allow a forecaster to provide reliable forecasts. We evaluate and provide insights into the performance of five multi-scale decomposition algorithms combined with a deep convolution neural network (CNN). Additionally, we compare the suggested combination approach's performance to that of existing forecast models. An exhaustive assessment is carried out using three grid-connected PV power plants in Algeria with a total installed capacity of 73.1 MW. The developed fusing strategy displayed an outstanding forecasting performance. The comparative analysis of the proposed combination method with the stand-alone forecast model and other hybridization techniques proves its superiority in terms of forecasting precision, with an RMSE varying in the range of [0.454–1.54] for the three studied PV stations.

ACTIVE POWER FILTER IMPACT ON POWER QUALITY IMPROVEMENT FOR INDUSTRUAL PLANT SUPPLIED BY PHOTOVOLTAIQUE STATION

This work deals on industrial electrical power quality improvement using an active power filter (APF) based on fuzzy logic controller. The studied system is a PV conversion chain used to supply linear and non-linear industrial loads of 200 kw plant. The PV station is modeled then simulated under Matlab Simulink, with standard conditions consideration in the first time then under real irradiation and sun power variation during the day hours, to obtain the true parameters design of the PV station to be able to give the needed power during the climatic conditions changing. APF parameters design and control loop structure are well studied to have an optimal control. MPPT technique is used in PV station control with the P&O algorithm. Also PV panel fault diagnosis has been done by using alarm for fault indicator and protection over under power. Simulation results are analyzed and discussed comparison with real signals, produced by the FLUK 6001B reference source with the use of the PRS 600 and the Teledyne 3,5 GHz-40Gs/s oscilloscope as measurement instrument, to improve the effectiveness of APF on electrical power quality, THD, amelioration and harmonic minimization in the industrial installation.

Modeling Multi-Temporal Correlation of PV Stations Output via Improved Nonparametric Disaggregation Method in Power System Reliability Evaluation

Modeling Multi-Temporal Correlation of PV Stations Output via Improved Nonparametric Disaggregation Method in Power System Reliability Evaluation

Technical achievable potential of photovoltaic conversion of solar radiation for the conditions of Ukraine

This study investigates solar energy photovoltaic conversion processes while exploring new approaches to identify potential areas for the installation of photovoltaic stations. This research aims to enhance existing methodologies of technical-achievable potential calculation, considering the specificity of territories, the possibility of installing rooftop photovoltaic stations, and the current development of photovoltaic technologies. The developed methodology considers the type of stations, urban building specifics during the calculation of suitable areas for photovoltaic station installation, the potential for installing small and medium rooftop stations, and the modern technical characteristics of photovoltaic modules. The refinement of the PV panels and PV station area ratio calculations revealed that its value depends on the type and power of the station, varying from 0 to 1. This approach simplifies the determination of power capacity of a station that can be installed in a designated area. Consideration of the technical characteristics of the latest photoelectric conversion technologies demonstrates a significant potential increase compared to the existing calculation methodologies. Calculations conducted using the developed methodology revealed that the technically achievable potential of solar energy conversion for Ukraine is 369 TWh/year (254 GWp DC). This figure exceeds the estimations of existing calculation methodologies at least twice. The obtained results showed a significantly greater potential for solar energy in Ukraine, which expands the possibilities of using photovoltaic technologies to supply energy to consumers. This is especially important during the war because of the insufficient electricity production by existing power plants, many of which have been destroyed.

Distributed photovoltaic short‐term power forecasting using hybrid competitive particle swarm optimization support vector machines based on spatial correlation analysis

AbstractIn order to further improve the accuracy of distributed photovoltaic (DPV) power prediction, this paper proposes a support vector machine (SVM) model based on hybrid competitive particle swarm optimization (HCPSO) with consideration of spatial correlation (SC), for realizing short‐term PV power prediction tasks. Firstly, the spatial correlation analysis is conducted on the distributed PV stations. The k‐means clustering method based on morphological similarity distance improvement and mutual information function is used to select the best reference station and the best delay, which generates strongly correlated PV sequences. Then, a hybrid algorithm of particle swarm optimization (PSO) and sine cosine algorithm (SCA) in a competitive framework (HCPSO) is proposed, aiming to fuse the fast convergence capability of PSO algorithm with the global search capability of SCA algorithm, while enabling the algorithm to effectively handle high‐dimensional optimization problems based on a competitive mechanism. Finally, the HCPSO algorithm is combined with SVM algorithm, which expands the applicable scenarios of the SVM model and effectively improves the accuracy of PV short‐term prediction.

Identifying the functional form and operation rules of energy storage pump for a hydro-wind-photovoltaic hybrid power system

Coupling energy storage pumps with conventional hydropower plants is one of the most valuable methods to increase the consumption rate of renewable energy. There are few small-scale hybrid power systems configurating energy storage pumps in the world (e.g., Ikaria Island, Greece). However, whether the operating principle and configuration method are feasible and transferable for a large-scale renewable energy base is unclear. This study proposes specific operating principles and configuration method for a large-scale hybrid power system, demonstrating the feasibility by investigating typical scenarios of an engineering case in Qinghai Province, China. Assume the conventional hydropower plants, wind farms, and PV stations in the case are constructed and in operation completely. The configuration relationship between energy storage pump and hydropower is investigated by setting the unit of energy storage pump from 1 to 50, the per-kW investment cost from CNY5000/kW to CNY30000/kW under the constraint of individual capacity of 100 MW. Furthermore, the economic indicators of internal rate of return and dynamic payback period are introduced to evaluate the performance of the whole hybrid power system. The configuration consequence of 18–21 pumps shows a good relation with renewable energy. This study provides theoretical and technical support for planning relevant hybrid power station projects.

The Impact of Adding Solar Panels on The Wind Turbine Performance During Transient Disturbances

Recently electrical engineers look forward to replace the conventional power grid with a smart grid. This replacement requires massive changes, one of them is the integration of distributed generations and renewable energy sources in the distribution networks of the grid. These changes may affect the transient stability of the grid. In this paper, IEEE 9-bus system is used to perform transient stability analysis for a three-phase fault contingency. A 20 MW wind turbine was installed to study its performance and impact on the transient stability of the system. Then, a 3.6 MW PV station was added to study its impact on the wind turbine performance during the contingency. ETAP® 2016 software is used for simulation. The results show that the critical clearing time (CCT) of the system increases when the wind turbine is added and decreases when the PV station is installed. The impact of PV station on the wind turbine performance is not significant and it mainly affects the reactive power of the wind turbine generator after the fault is cleared.

Wide frequency band oscillation mechanism and suppression measures for grid-interfaced PV inverters based on impedance analysis

With the rapid development of PV and wind power, the energy structure of the power grid is changing dramatically. The dominant power supply role played by conventional power sources such as hydropower and thermal power is gradually replaced by PV and wind power. All the power electronics-based equipment makes the power system stable form more complex, and one of the most significant challenges is wide frequency band oscillation (WFBO). This paper proposes an impedance analysis method for PV inverters in high proportion to new energy-integrated power systems. First, we investigate WFBO mechanism caused by the PV inverter based on its impedance model, and then a detailed impedance model of parallel PV inverters is developed to study WFBOs in PV stations. Finally, the WFBO suppression measure based on active damping control is proposed. Simulation results prove the correctness and feasibility of the active damping control strategy.

Application of generating units based on renewable energy sources for damping oscillations in the power system

In today’s world, generating units based on renewable energy sources occupy one of the main places when it comes to the development of power systems. Modern generating units based on renewable energy sources have a power converter in their composition. On the one hand, the use of a power converter gives some advantages: no direct connection to the grid, operation in all quadrants of the PQ diagram. However, on the other hand, widespread use of renewable generation units based on power converter reduces the overall inertia of the EPS, excessive use of power electronic converters in the electric grid will cause many harmonic disturbances and create new problems for safe and stable operation of EPS. In order to ensure the reliable operation of EPS with renewable energy units based on the power converter, the power converters control system should be upgraded to meet the requirements of conventional generation as part of EPS. This paper presents the result of applying a power oscillation damping controller implemented in a power converter to improve the stability of a high-dimensional EPS. The paper presents an analysis of the effect of regulators of different topology for oscillation damping. The results of the application of the power oscillation damping regulator in the following research scenarios are presented. For a more accurate assessment of the impact of the regulator, the transient damping coefficient was calculated. In this paper, the result of using the oscillation damping controller implemented in the power converter for the PV station to improve the stability of the EPS as a whole was demonstrated. The proposed solution is based on the “deloading” strategy of the PV power station and the SI block with two-loop control. The effect of oscillation damping controller on power fluctuations was evaluated according to the AVR oscillator tuning methodology.

A Study on the Operation of a Balancing Group Consisting of PVs and On-site Storage Batteries

The renewable energy resources, such as photovoltaic generation and wind turbine, are rapidly being integrated. In order to compensate for the variable output and imbalance between actual and scheduled outputs, introduction of a battery storage would be one of the promising solutions. In this paper, we focus on the scheduled operation of a balancing group (BG) consisting of the widely distributed photovoltaic generation with storage battery. BG forming would bring reduction of total imbalance due to cancellation of forecast errors among PV stations, and could enable cooperative usage of battery storages for imbalance compensation. This paper proposes a new battery storages operation scheduling for the BG considering the imbalance risk, which are assumed based on the confidence interval forecast for PV output. Effectiveness of the proposed scheduling method is ascertained through year-basis computational simulation of the BG. Advantages of BG forming is also discussed.

Frequency control by the PV station in electric power systems with hydrogen energy storage

The rapid growth of renewable energy capacity, in particular photovoltaic systems, is creating challenges associated with changing the rate of transient processes in the power system. This is due to the approach PV systems are connected to the grid using power converters and the absence of a rotating mass in the PV power plant. One of the most pressing challenge is the participation of PV stations in the process of frequency control in power systems, including in emergency modes. Simultaneously with PV power plants, it is efficient to use energy storage systems, including hydrogen ones. This is due to the fact that it is possible to obtain hydrogen for such energy storage systems using excess energy from PV power plants. The article proposes to solve the problem of frequency regulation in the power system by using an algorithm that allows to control the frequency in the power system using a synthetic inertia block of PV station, including at different levels of insolation and temperature of PV panels. The robustness of the proposed algorithm allows it to be used at different levels of power generated by the PV station, as well as in emergency modes.

Feasibility and Potential Assessment of Solar Resources: A Case Study in North Shewa Zone, Amhara, Ethiopia

The feasibility and potential assessment (PA) of solar PV energy is one of the key factors in identifying the most promising areas for the installation of solar PV stations. It determines the useful energy generated in the given area. This paper assesses the solar energy distribution and PA in the North Shewa administration zone. Based on the data collected and analysis made, it is found that more than 80% of the North Shewa areas are suitable for the solar energy generation for off-grid and on-grid systems. Hence, the solar potential of the North Shewa zone completely fulfills the standards of sunshine, solar radiation, and temperature. That is, most of the areas have solar radiation of 5.2 kWh/m2, and daily sunshine is greater than 7 h. The maximum energy production is found in December in Shewa Robit, Mehal Meda, Eneware, Debre Berhan, Alem Ketema, and Sela Dengay with 175.35 kWh, 188.18 kWh, 180.78 kWh, 189.54 kWh, 175.78 kWh, and 189.63 kWh, respectively. This is a good opportunity for investors to invest in solar PV electricity generation. It will solve the issue of electricity supply to the community, which currently relies on wood and fossil fuels. It also highlights the positive opportunities for the future implementation of solar energy.

Research on Fast Frequency Response Control of PV Power Stations

In this paper, the frequency support capacity of power system integrated by A large number of PV generation is considered. Based on the conventional inverter PQ control strategy, virtual droop control and inertia control are introduced, and a fast frequency response control strategy of PV inverter similar to the synchronous generator is proposed. Meanwhile, in simulation software of power system, a three-machine nine-node simulation model including the PV power station is established, and the simulation verification is carried out. The simulation results show that when the system is disturbed, PV station can actively provide frequency regulation and enhance frequency stability of the power system.

An Advanced Artificial Neural Network Energy Management in Standalone PV Systems

With the ever-increasing prevalent power crisis and pollution of the environment, solar power, has attracted greater attention as a new and clean energy source. It provides an alternative solution for isolated sites with an unavailable grid connection. However, it is not without any drawbacks, mainly its intermittent nature, related primarily owing to its reliance on meteorological variables such as the temperature outside and the amount of sunlight. In effect, the PV systems that produced electrical energy could well display an electricity excess or deficit at the loads level, likely to result in system service discontinuity. In this respect, the present paper is designed to provide an intelligent management strategy to PV station owners with a dump load. It can involve serving two customers simultaneously according to the following scenarios: the PV production installation of the customer1 is greater than their required load; however, the customer2's neighboring station does not have enough power to cover its electrical load. This case brings electrical energy from the initial station to make up for the shortfall, and vice versa. Lithium-ion batteries step in the case when the essential electrical power cannot be delivered either by the local station or the neighboring one or to keep the accumulated power excess. If one of the stations (1 or 2) detects a power surplus and the batteries are completely charged, the generated power excess must be redirected to a secondary load, commonly known as the dump load. Relying on the artificial neural network controller, the suggested exchange control is used for two independent PV-battery stations with dump load. The MATLAB/Simulink attained simulation turns out to demonstrate the advanced controller’s noticeable performance and effectiveness in managing the standalone PV system’s operability in terms of continuous electrical energy delivery flow to the resistive load while reducing power waste and increasing the lithium-ion battery lifespan.

Reactive Power Compensation for Preventing Voltage Instabilities in Distribution Lines Enriched with PV Power Plants

The efficient voltage regulation method by capacitive reactive power usage is represented in the article. The stochastic electricity generation of multiple PV stations placed in local distribution lines induces voltage instabilities. These voltage fluctuations may overcome the allowable limits and cause technical problems and economic losses. The method of applying reactive power generated by a capacitor bank at the load is proposed. Primarily, a strict analytical solution of nonlinear equations describing voltage deviations in the distribution line connected with photovoltaic systems was obtained. The control system can fast select optimal capacitors based on the analytical solution and then connect them smoothly to a load. The developed experimental setup verified and approved the correctness and accuracy of theoretical analysis. Experimental measurements confirmed the proposed method’s ability to improve voltage stability in distribution grids. The proposed method is supposed to be used together with the transformer tap-changers in electrical substations. The capacitive power is applied in a time of inappropriate voltage deviations only and is disconnected as the tapchanger corrected the transformation ratio.

A life cycle assessment of Hydropower-Silicon-Photovoltaic industrial chain in China

In this paper, we conducted a life cycle assessment (LCA) for the Hydropower-Silicon-Photovoltaic (HSPV) industrial chain in China. The Energy Conservation and Emission Reduction Index in the 13th Five Year Plan of China (ECER-135) is calculated based on the software eBalancev4.7 (eB) and eFootprint (eF). The total environmental impact index of ECER-135 of the HSPV industrial chain is 2.61E-06. The uncertainty result of the comprehensive index is 15.21% and the uncertainty of the inventory data is no more than 30%. The Energy Payback Time (EPBT) of the HSPV industrial chain is calculated as 1.68 years, accounting for only 5.60% of the operating cycle of the PV station. There are 7 impact category indexes of ECER-135, which are Chemical Oxygen Demand (COD), Primary Energy Demand (PED), CO2, SO2, Ammonia Nitrogen Content (NH3–N), NOx and Industrial Water Use (IWU). Considering the contribution of characteristic indexes to ECER-135, the contribution of PED index accounts for 22.93% of ECER-135, which is the major factor to environmental impact, and it is followed by COD, which accounts for 18.40%. Considering the contribution of each stage to ECER-135, PV module manufacturing, BOS manufacturing and SoG-Si manufacturing stages have significantly contributed to ECER-135, in which the PV module manufacturing stage has the greatest contribution to ECER-135, accounting for 97.63%, which is the main stage of impact on the environment. The sensitivity analysis reveals that the highest sensitivity is copper wire consumption, which is 47.83%. It is followed by aluminum consumption during the BOS manufacturing and the PV module manufacturing, which are 41.70% and 29.75% respectively. Finally, compared the total environmental impact of the HSPV industrial chain and the Thermalpower-Silicon-Photovoltaic (TSPV) industrial chain, the results reveal that the HSPV industrial chain has the energy-saving and emission reduction benefits of 2.89E-06, whose comprehensive indexes account for 47.39% of that of the TSPV industrial chain, proving that the HSPV industrial chain has significant energy saving and emission reduction benefits in all indexes. The EPBT of the HSPV industrial chain is only 38.17% of that of the TSPV industrial chain.