Solar PV Penetration Research Articles

Ray-Tracing modeling for urban photovoltaic energy planning and management

The traditional Radiative Transfer Modelling solutions for Solar Energy monitoring and forecasting often provide outputs for a single point location or an area location. However, for high resolution representation of areas these solutions suffer due to low simulation speeds. This approach makes it difficult for decision-makers to accurately estimate the solar potential of the administrative area and plan installations accordingly. In this direction, the study introduces three-dimensional Ray-Tracing based radiative modeling which is a high-speed area-based solution for solar energy monitoring. The three-dimensional ray-tracing was simulated by using advanced graphic creation platforms and cloud computing in conjunction with satellite data of the clouds, aerosols, building shadows effects and three-dimensional representations of the city using Cesium 3D tiles and Unreal Engine ®. The entire system was developed in a hybrid model to be exploited by urban planners for solar PV installations and by electricity distribution system operators for energy management and efficient incorporation of the produced energy into the regular and smart grids. This study implements and analyses this Ray-Tracing model for solar photovoltaic energy potential estimation at a rooftop level for the city of Athens, Greece. The total rooftop exploitable area in Athens was found to be close to 34 km2, which is able to massively host distributed PVs followed by almost 4.3 TWh of annually produced energy, whilst Penteli (a Municipality in Athens) possessed a potential of 96.8 GWh with an exploitable area of just 0.8 km2. This amount of energy, in a hypothetical full coverage scenario, is able to provide for 48.7% of Athens’s total energy requirement. Similar year-long simulations were conducted using the EU’s largest rooftop solar installation at Stavros Niarchos Foundation Cultural Center and randomly selected rooftops having solar installations in different municipalities in Athens. With these estimated solar potential values, the gross savings in natural gas consumption and hence the CO2 equivalent emissions can be computed. With the current estimated solar potential of Athens, the analyzed savings accounted of nearly 2.43 billion euros and 18 MT CO2 equivalent emissions. These computed annual savings are capable of covering installation costs for nearly 100,000 new solar installations. The end-product of this study is the development of a solar cadastre web tool which will support the decision-makers in the energy transition policies and the solar PV penetration into the urban environment and eventually drive the effort into renewable energy transition across the globe.

Analysis of the Effect of Solar PV Penetration for Empowering the Grid

Analysis of the Effect of Solar PV Penetration for Empowering the Grid

The Impact of Solar Distributed Generation on Distribution Networks: Case Study of Chipata Distribution Network

The installation of solar PV systems in distribution networks is slowly increasing. The study focused on identifying the challenges and benefits of installing Distributed Solar Generation in the Chipata 33kV and 11kV distribution Networks. Chipata Town is in the Eastern Part of Zambia, and it has a peak demand of about 23.3MW. The 2023 version Power Factory Dig Silent Software was used to model the Chipata 33kV and 11kV distribution network and different Solar penetration levels were used to understand the impact of Distributed Solar. Chipata Distribution Network has four major stations operating at 33kV and 11kV voltages and four main distribution lines. The main objective of the study was to determine the impact of distributed solar PV in the Chipata Distribution Network. One of the specific objectives was to determine the hosting capacity of the Chipata Distribution Network. The hosting capacity gives the maximum amount of PV power integrated in a power system network without violating the set operation limits. The study analysed the impact of solar Distributed Generation on network losses, fault levels, voltage stability and line loading. The study revealed that an increase in penetration level resulted in a general increase in the Bus Bar voltages on both 11kV and 33kV voltage levels. Different Penetration levels of solar ranging from 6.66MW to 132MW were studied. Simulations revealed that the hosting capacity for Chipata Distribution Network is 96MW (412% of Solar PV Penetration Level). The voltages in the distribution network at hosting capacity were ranged from 0.93p.u to 1.02p.u. Short Circuit analysis simulations showed negligible impact on the fault level after integration of solar in the distribution network. Some circuits showed both increased and reduced power losses with increased solar penetration. The obtained results indicated that increased installation of distributed Solar PV systems in the Distribution Network impacts voltage stability, line losses and line loading.

Assessment of photovoltaic generation penetration effect on the maximum loadability of the system

This paper proposed a method to investigate the effect of increasing PV penetration on the voltage stability of an IEEE 14-bus test system considering maximum PV penetration and system loadability limit. The critical bus of the test system has been decided based on nose curve analysis. The solar PV system is deployed with the most critical bus of the system. The effect of increasing PV penetration on the improvement in the loading capacity of various power system components like transmission lines, transmission line transformers, and generators is investigated over the adopted test system. Based on solar PV penetration up to 100 MW, the maximum loadability limit of the IEEE 14-bus test system increases, as shown by the results. Bus 14 is found to be the most severe bus of the test system using the continuation power flow (CPF) method. However, in some cases, overloading situations develop after a certain limit of PV penetration in the power system. In this condition, the overloading of the power system equipment is improved by the use of a Static Synchronous Compensator (STATCOM) at bus number 14, a double circuit line in the critical line (9–14), and Static Synchronous Series Compensator (SSSC) in the most severe line (9–14) in the system. The maximum loadability of the system gets maximum enhanced from 4.0349 p.u. to 4.5602 p.u. under simultaneous use of solar PV generation, SSSC, and STATCOM at the most critical bus and in most severe line of the system. As evidence, the enhancement in maximum loadability of the system found using the proposed method has been also compared with the existing research. The maximum system loadability has been also enhanced under normal and (N-1) contingency conditions by the use of PV penetration in the system. PSAT/MATLAB software is used for simulation and maximum loadability has been investigated by continuation power flow (CPF) method.

Framework for policy prescription to sustainably steer stochastic penetration of electric vehicles and solar PV in distribution network of a developing country

Cash-strapped distribution companies of developing countries face stochastic penetrations of solar photovoltaic units (PVs) and electric vehicles (EVs) while planning to manage their uncertain growth trajectories. Since Pakistan’s power distribution sector is not technically and financially sound, this research presents a framework for policy prescription to avoid dangerously burdening distribution companies or deteriorating the grid conditions. The EV load model considers EVs' arrival and departure times based on a survey of daily commuters. The Burr distribution function is used for selecting sizes of the PVs for grid integration because it best fits sampled data of installed PVs in the country. After stochastically selecting network nodes for integrating EVs and PVs to mimic their locational growth, technical and financial parameters are evaluated with and without the net metering effect. At peak PV hour and higher PV penetration of 50%, voltage limit conformance improves from 88% to 94% if net metering is not allowed. Results show that annual net revenue increases with rising EV penetration and always remains positive in the absence of PV. However, irrespective of EV penetration level, even 25% PV penetration and consequent loss of cash inflows lead to negative net revenues. The study concludes that excessive PV penetration with net metering causes voltage instability and negative net revenues, whereas EV integration can reduce both effects. A network-wide extension of our research methodology, to representative feeders selected by clustering, is proposed as a framework for policy prescription to steer the growth of EVs and PVs integration sustainably.

Capacity Credit of Solar PV Projects – Oman’s Main Interconnected System Case Study

Due to high growth in electricity demand, it is important to add more dispatchablegeneration capacity in power systems to maintain demand-supply balance in real time. In many power systems, fossil fuel-based units such as gas or coal power plants are used to maintain high-reliability standards during peak demand hours. Although intermittent renewable energy generation facilities such as solar PV systems are used as a fuel saver, they can offset part of the load during peak hours. Capacity credit measures the contribution of a power plant to reliably meet demand. Estimating capacity credit of solar PV systems is important to ensure the adequacy and security of electricity supply. In this article, the capacity credit of solar PV power plants in the Main Interconnected System (MIS) of Oman is modelled. Oman’s MIS considered in this study has 6,372 MW gas-based generation capacity, a negligible solar PV capacity, and 5,712 MW peak load. The results revealed that the capacity credit of solar PV plants is high at low solar PV penetration levels. However, it decreases drastically as solar PV capacity increases. For example, the first 500MW plant has a capacity credit of about 120 MW. When the cumulative installed solar PV capacity is 2000MW, the next 500MW plant has a capacity credit of only 26MW.

Ring connected microgrid clusters for improved resiliency in distribution systems with high solar PV penetration

Ring connected microgrid clusters for improved resiliency in distribution systems with high solar PV penetration

Overcoming the Fluctuating Curve from PV Power Generation by Modelling the Integration of Hydrogen Energy Storage Into Electricity Microgrid

Java Madura Bali (Jamali) system is the Indonesian largest grid, which contributes approximately 61%, with the Coal Thermal dominates by 59% and followed by the New Renewable Energy (NRE) of 9%. Solar Photovoltaic Power Plants (SPP) contribute only 1% from the NRE itself. Low voltage customers (TR) are approximately 61% with the residential contribute approximately 42%. The rates of the national SAIDI is 12.72 hours/subscriber/year and the national SAIFI is 9.25 times per subscriber/year. There is some challenge in regulating voltage in area with high penetration of solar PV, case of voltage fluctuation in response to the fluctuating of solar irradiance, as well as other factors such as load transient. This voltage fluctuation is proportional to the amount of current generated by the PV system and also proportional to the solar irradiance.Hydrogen energy storage (HES) is an alternative to NRE-based energy storage technology. Integrating solar PV with hydrogen energy storage and optimisation device may mitigate PV-driven voltage fluctuation, preventing excessive reserve power flow on the grid. The hydrogen energy storage system can cover variation of the loads at the nearby solar PV system in the microgrid and the ability to manage those loads, as mentioned in the energy management system. Integrating the HES within Solar PV system can improve the curve shape, improve system reliability and voltage stability, especially in the Residential Microgrid. Also may build the opportunities to earn new revenues from wholesale electricity markets, enhancing the reliability rate and competitive monetary value.

Probabilistic Assessment of Conservation Voltage Reduction Using Static Load Model Parameter in the Presence of Uncertainties

Higher penetration of solar PV and wind generation in distribution networks may change the conservation voltage reduction (CVR) capabilities. The uncertainties associated with the renewable generations and system loads are neglected in the deterministic CVR assessment. In this paper, a probabilistic framework for CVR assessment has been presented to assess the impact of uncertainties associated with renewable generations and system loads. A theoretical framework has been presented by establishing a mathematical relationship between the probability distribution of renewable generations (solar PV and wind) and the probability distribution of static exponential load model parameters. The simulation results have confirmed that the penetration of non-Gaussian solar PV and wind generation leads to non-Gaussian static exponential load model parameter distribution, which is validated by the normality tests (quantile-quantile plot, skewness, and kurtosis). Subsequently, the magnitude and probability distribution of the CVR capabilities of the network changes with the penetration of renewable generations, where the higher renewable penetration scenarios lead to higher CVR values and non-Gaussian (asymmetric) distribution.

Centralized battery systems to manage voltage under high penetration of solar-PV and electric vehicles

With the increased concern on carbon emissions from fossil-fuel-based power generation sources and the transportation sector, the world and Australia are shifting towards renewable energy solutions. The increase in penetration of distributed energy resources (DERs), such as rooftop solar photovoltaic (PV) systems and electric vehicles (EVs), would make a profound impact on the power system. This paper analyzes the effects of the bidirectional power flow of solar-PV and EV charging load on distribution network voltage using time-series profiles. The DIgSILENT PowerFactory is used for the study. According to the study, the solar-PV can violate the upper voltage limit during the mid-day, and the EVs can violate the lower voltage limit in the evening. Therefore, solar-PV systems and EVs cannot be utilized to complement each other at the household level, and hence a central solution is required to tackle this issue. This study has proposed a solution based on a central battery energy storage system (BESS) to tackle this problem. According to the analysis, the central BESS can assist in flattening the voltage profile during the day and can maintain the voltage within the statutory limits defined in AS60038.

A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks

The use of fossil-fueled power stations to generate electricity has had a damaging effect over the years, necessitating the need for alternative energy sources. Microgrids consisting of renewable energy source concepts have gained a lot of consideration in recent years as an alternative because they use advances in information and communication technology (ICT) to increase the quality and efficiency of services and distributed energy resources (DERs), which are environmentally friendly. Nevertheless, microgrids are constrained by the outbreaks of faults, which have an impact on their performance and necessitate dynamic energy management and optimization strategies. The application of artificial intelligence (AI) is gaining momentum as a vital key at this point. This study focuses on a comprehensive review of applications of artificial intelligence strategies on hybrid renewable microgrids for optimization, power quality enhancement, and analyses of fault outbreaks in microgrids. The use of techniques such as machine learning (ML), genetic algorithms (GA), artificial neural networks (ANN), fuzzy logic (FL), particle swarm optimization (PSO), heuristic optimization, artificial bee colony (ABC), and others is reviewed for various microgrid strategies such as regression and classification in this study. Applications of AI in microgrids are reviewed together with their benefits, drawbacks, and prospects for the future. The coordination and maximum penetration of renewable energy, solar PV, and wind in a hybrid microgrid under fault outbreaks are furthermore reviewed.

Assessment of the optimum location and hosting capacity of distributed solar PV in the southern interconnected grid (SIG) of Cameroon

ABSTRACT Cameroon’s electricity mix is dominated by hydropower sources despite the huge potentials of other sources like solar. The over-dependence on hydropower has led to frequent load shedding especially in the dry season as a result of low water levels. Interestingly, the government plans to diversify her power mix and provide sustainable energy to Cameroonians. It is in this framework that this study evaluates the integration of solar PV into the Southern Interconnected Grid of Cameroon using dynamic analysis. The ETAP tool was used in developing the model. A power loss assessment was done through successive injection of solar PV into the candidate busbars while monitoring the active power losses in the grid. Then, a transient stability analysis was conducted so as to assess the grid’s response to induced instability after the penetration of large-scale solar PV. The study showed that the use of static performance indices to evaluate the solar PV hosting capacity do not safeguard the grid’s technical robustness. The results indicated an optimum solar PV penetration level of 30% (211.8 MW) at the Ngousso 93 kV busbar. The findings will be useful to system operators and regulators in developing low-carbon pathways in the electricity network in Cameroon.

Protection Analysis of a Traveling-Wave, Machine-Learning Protection Scheme for Distributions Systems With Variable Penetration of Solar PV

Protection Analysis of a Traveling-Wave, Machine-Learning Protection Scheme for Distributions Systems With Variable Penetration of Solar PV

Effects of Household Battery Systems on LV Residential Feeder Voltage Management

With the advancements of the battery energy storage systems (BESSs), reduction of their manufacturing costs and government subsidies, the BESS uptake is likely to increase rapidly in power distribution networks. This paper investigates the effects of residential BESSs on low-voltage (LV) networks using the actual household load profiles equipped with BESS and solar-photovoltaic (PV) systems. The electricity consumption data collected via smart meters (2200 households with PV/BESS, 1950 households with PV only and 1000 households without a PV or a BESS) at different solar-PV penetration levels and network types are used to simulate real network operating scenarios. A real LV distribution network in Australia is analysed in DIgSILENT PowerFactory under different scenarios, such as, customers with and without a solar-PV/BESS, with a solar-PV but without a BESS, and without a solar-PV, by using both the power flow and quasi-dynamic simulation studies under balanced and the unbalanced network loading conditions. According to the study, customers experience large voltage excursions from solar-PV power exports, which could be resolved by the household BESS, provided that the BESS charging is coordinated with the solar-PV production. Moreover, quasi-dynamic simulation shows that the BESS could reduce the violation of the over-voltage limit during the solar peak hours (midday) by lowering the worst-case feeder voltage by 3%. Finally, extreme-event (high solar PV generation scenario) simulation shows that the implementation of the BESS controller to facilitate charging BESS during afternoon solar-PV export may reduce the negative grid impact and will assist to avoid network upgrades.

Energy Storage Applications to Address the Challenges of Solar PV and Wind Penetration in Indonesia: A Preliminary Study

Indonesia intends to increase the renewable energy ratio to at least 23% from the energy mix generated by 2025. This target is also in line with the Paris Agreement that Indonesia ratified in October 2016. However, renewable energy capacity has not been significant, as 11.38% of the total on-grid power capacity (MEMR, 2021). More than 90% of renewable comes from hydropower and geothermal, and only a limited capacity comes from wind and solar energy. On the other hand, wind and solar energy potential are enormous for energy generation in Indonesia. One of the barriers that hinder the use of both is their intermittent nature so that they are not economically profitable and can disrupt the existing power grid. Energy storage systems (ESS) can reduce this intermittent problem as frequency regulators and voltage support to the grid. This paper reviews the potential and challenges of energy storage and renewable power generation, especially wind and solar power. This paper also outlines lessons learned from energy storage systems that have been implemented and are still under development. The discussion focuses on the types of energy storage suitable for applications in Indonesia.

Sunflower optimization based fractional order fuzzy PID controller for frequency regulation of solar-wind integrated power system with hydrogen aqua equalizer-fuel cell unit

ABSTRACT The rapid advancement of electric consumer demand enforces challenging situations to manage high penetration of Solar PV and Wind Power into the hydrothermal system resulting in load frequency control (LFC) problem. This article introduces an advanced strategy to manage the LFC issue in an integrated power system (PS) with the impact of hydrogen aqua equalizer (HAE)-based Fuel cells (FC). A transformative fractional-order fuzzy-based PID (FOFPID) controller regulated by the Sunflower optimizing (SFO) technique has been proposed for frequency regulation of the proposed integrated PS. The preeminence of the FOFPID controller has been validated over PID, Fuzzy-PID (FPID), and fractional order PID (FOPID) controller. The effectiveness of the SFO technique has been established over teaching learning-based optimization (TLBO) and Genetic Algorithm (GA). The supremacy of the SFO approach authenticated by some recent frequency regulation research outcomes. The influence of HAE-FC for frequency regulation in an integrated PS has been studied with the proposed SFO-tuned FOFPID controller. From the observation, it is perceived that the values of reduction in ITAE with suggested SFO-tuned FOFPID controller as compared to GA & TLBO are 84.61% & 56.04% and further 35.16% is reduced with the occurrence of HAE-FC element. It is also perceived that the improvement in settling time for ∆f1, ∆f2, ∆Ptie12 with SFO approach related to GA are 78.07%, 76%, and 83.87% and compared to TLBO are 9.97%, 38.25%, and 68.23%. Furthermore, 26.45%, 18.64%, and 31.21% are reduced with the presence of HAE-FC unit. Lastly, the sturdiness of the anticipated strategy was authenticated by a sensitivity test and a real-time validation test using OPAL-RT.

Sky Image-Based Localized, Short-Term Solar Irradiance Forecasting for Multiple PV Sites via Cloud Motion Tracking

Power generation through solar photovoltaics has shown significant growth in recent years. However, high penetration of solar PV creates power system operational issues as a result of solar PV variability and uncertainty. Short-term PV variability mainly occurs due to the intermittency of cloud cover. Therefore, to mitigate the effects of PV variability, a sky-image-based, localized, global horizontal irradiance forecasting model was introduced considering the individual cloud motion, cloud thicknesses, and the elevations of clouds above the ground level. The proposed forecasting model works independently of any historical irradiance measurements. Two inexpensive sky camera systems were developed and placed in two different locations to obtain sky images for cloud tracking and cloud-based heights. Then, irradiance values for onsite and for a PV site located with a distance of 2 km from the main camera were forecasted for 1 minute, 5 minutes, and 15 minutes ahead of real-time. Results show that the three-level cloud categorization and the individual cloud movement tracking method introduced in this paper increase the forecasting accuracy. For partially cloudy and sunny days, the forecasting model for 15 min forecasting time interval achieved a positive skill factor concerning the persistent model. The accuracy of determining the correct irradiance state for a 1 min forecasting time interval using the proposed model is 81%. The average measures of RMSE, MAE, and SF obtained using the proposed method for 15 min forecasting time horizon are 101 Wm-2, 64 Wm-2, and 0.26, respectively. These forecasting accuracy levels are much higher than the other benchmarks considered in this paper.

Assessment of the Availability and Penetration of Solar PV, Wind and Biogas in Ghana

Access to energy is pivotal to the socio-economic growth of many developing countries, including Ghana. Energy generation from fossil fuels is not sustainable and leads to global warming, which is detrimental to the environment. This study seeks to establish how renewable energies are embedded and utilised in the Ghanaian energy system and the factors that can expedite the speedy penetration of renewable technologies into the country, particularly solar PV, wind, and biogas. The study adopted a mixed research approach which includes quantitative and qualitative studies. The findings revealed that solar energy is the most available resource in the country compared to other renewables. It was also indicative that integrating solar PV, wind and biogas in the national electricity grid will improve the percentage of energy generation mix, which will help sustain constant power supply, reduce the cost of energy charges, and consequently improve the country’s economy. The results also showed the possible factors that affect future penetration of these technologies, including unavailability of consumer financing opportunities, inadequate training facilities, lack of adequate regulations/policies, lack of information on the cost and benefits of renewable energies. The six findings of the paper established the availability of renewables in Ghana and the prospect of their related technology. While solar PV is on the ascendency, biogas is progressing gradually and wind is moving at a snail’s pace. This study significantly established the benefits of incorporating solar PV, wind and biogas in the Ghanaian energy mix to improve the electricity supply and further outlined the impeding factors that need to be improved upon through policy.

Preliminarily Screening Geographical Hotspots for New Rooftop PV Installation: A Case Study in Thailand

As rooftop PV deployment accelerates around the world, forecasts of rooftop PV penetration by geographical region and customer group are essential to guide policy and decision-making by utilities. However, most state-of-the-art forecasting tools require detailed data that are often unavailable for developing countries. A simplified analytical tool with limited data is proposed to preliminarily identify the rooftop PV “hotspots”—that is, geographical areas where many new investments into rooftop PV investments are likely to occur. The tool combines the assessment of financial and technical indicator in form of the optimal PV-to-load ratio indicating the maximum penetration of solar PV, and the capital-to-expenditure ratio indicating the ease of such investment. Using Thailand as a case study, the results from this tool show that under the self-consumption and net-billing scheme, the Northern and Northeastern regions are marked as the potential hotspots where the utility’s impact will be realized early or strongly or both. The average LCOE and self-consumption level for all customer classes and regions are in the range of 0.084–0.112 USD/kWh and 41.33–73.13% of PV production, respectively.

Optimizing operational costs and PV production at utility scale: An optical fiber network analogy for solar park clustering

Increasing the share of renewable energy sources in power systems is key to a successful energy transition. Optimal renewable site selection requires a holistic approach, involving land, resources, environmental and economical data and constraints. In this paper we consider the problem of solar PV penetration into the power network as a spatiotemporal analysis combined with decision support targeted for policy makers and investors. Our goal is to seek new models that maximize energy penetration and stability into the network, while minimizing the operational costs. We show how the selection of solar PV sites can be accomplished to satisfy such objectives by investigating the optimal clustering of multiple solar PV parks around a shared electrical substation. This is a combinatorial problem in terms of all the potential clusters given the set of PV site candidates. Our main contribution lies in identifying and proposing a modeling analogy of our problem with the so-called SONET problem, tackled in fiber network designs. We show how this new spatiotemporal PV park placement model minimizes operational costs, while increasing energy stability of the solutions produced. We also introduce a GIS preprocessing step to reduce the computational cost of the proposed approach. We compare our proposed SONET-based model to an existing GIS-optimization model on a real case study and data from the French Guiana’s power system. This new approach aggregates multiple PV parks into clusters distributed across the territory. In the case of French Guiana, the same global nominal power (≈45MW) can, for instance, be distributed among 11 PV parks and 3 clusters, against 3 large-scale PV parks. Results show substantial gain in costs per kWh produced, up to 10MW of extra installed power and 16GWh of extra power generation when considering PV parks ⩽5MW. The new cluster configuration also ensures improved energy stability of the solutions, resulting in mitigation of the risks for both the network manager and the decision maker.