Rooftop Solar System Research Articles

Evaluation of household electricity consumption in multi-apartment buildings for optimization of rooftop PV systems

Empowering citizen energy communities (CECs) to produce, self-consume and share renewable energy can enhance household energy efficiency, support the adoption of renewable energy sources, reduce energy consumption and supply tariffs, and increase independence from fossil fuels. This study analyzes actual electricity consumption data from 31 dwellings in typical five-story multi-apartment buildings in Riga, Latvia, considering the potential for rooftop solar energy systems within CECs. The novelty of this study lies in the detailed analysis of household electricity consumption data and characteristics (e.g., household size, population, etc.) to predict household load which is essential for the optimal design of a multi-apartment building scale PV system. We evaluate the suitability of typical multi story buildings for rooftop photovoltaic (PV) systems, aiming to determine the potential PV performance relative to final electricity consumption. The study utilizes PolySun computer simulation software. Our findings indicate that a rooftop PV system on a typical 5 story multi-apartment building (60 apartments) can cover up to 77% of annual electricity consumption. This analysis is based on hourly real electricity consumption data. The research outcomes can inform optimization of on-site energy storage to mitigate the impact of PV systems on the grid. The proposed solution is applicable in many Eastern European countries and in some Western European countries that were influenced by the Soviet Union in the latter half of the 20th century.These regions have a similar stock of panel-constructed multi-apartment residential buildings and share comparable climatic conditions.

Renewable energy in sustainable cities: Challenges and opportunities by the case study of Nusantara Capital City (IKN)

Indonesia's future IKN capital might be sustainable, low-carbon, and climate-resilient. The Low Emissions Analysis Platform (LEAP) simulates energy efficiency in various demand sectors, renewable energy, and sustainable transportation solutions. Sustainable cars, such as renewable-energy-powered electric and green hydrogen-powered vehicles, can reduce energy consumption by 43% in 2045 and 33% in 2060, respectively, compared to BAU. GHG emissions per capita will drop 70% in 2045 and 63% in 2060. In the net-zero emission (NZE) scenario, IKN can reach 100% green energy by 2045 with a 4.4 GW solar power plant, a 0.92 GWh BESS, and a full load hour capability of 4 hours. We will use 1.1 GW of hydropower and 143 MW of wind power by 2045. In 2060, hydropower will be 2.8 GW, wind power will be 184 MW, and solar power will be 8 GW with 1.6 GWh of BESS. Lack of legislation, technical expertise, high prices, inadequate grid infrastructure, and insufficient renewable electricity restrict BESS use in Indonesia. Solar energy installation requirements, subsidies, and off-grid project incentives can all help ease BESS use. Forecasts predict 0.53 GW of rooftop solar PV capacity by 2045 and 3.35 GW by 2060. Net metering and solar tariffs boost rooftop solar system profitability. One ton of green hydrogen production requires 55.7 MWh from a solar power plant. Solar power plant capacity will rise to 0.49 GW by 2045, producing 19,359 tons of green hydrogen, and almost quintuple to 89,594 tons by 2060. Hydrogen generation, storage, transit, and distribution require specific infrastructure due to high capital costs and a lack of networks, yet interest in them is growing.

Integrated rooftop solar PV-based residential advanced energy management system: An economic involvement of energy systems for prosumers

The growing adoption of rooftop solar photovoltaic (PV) systems, coupled with the ability to sell surplus energy back to the national grid, presents a promising opportunity for residential energy management. This research introduces an innovative Advanced Energy Management System (AEMS) that integrates rooftop solar PV with energy-efficient appliances, offering a transformative approach to optimizing household energy consumption. By leveraging advanced demand-side management (DSM) techniques, the AEMS enables users to strategically shift energy usage away from peak hours, thereby reducing reliance on grid energy and minimizing costs. Empirical evaluations reveal that the AEMS significantly outperforms conventional energy management systems, achieving cost reductions of 28.59–35.48 %. The user-friendly interface and robust optimization strategies of the proposed model ensure operational efficiency, making it a valuable tool for maximizing energy savings and enhancing grid stability. Focusing on the specific context of Bangladesh, this study provides a comprehensive techno-economic analysis, demonstrating the practical applicability and long-term sustainability of suggested AEMS. The findings underscore the potential of the proposed model to revolutionize residential energy management, positioning it as a key enabler of both economic and environmental benefits for prosumers in emerging markets.

The role of value, belief and norm in shaping intentions to use residential rooftop solar for environment sustainability

The ongoing climate crisis presents a formidable global challenge, driving the urgent need for both technological advancements and a deeper understanding of the psychological factors that influence sustainable energy practices. Among the various technologies available, solar photovoltaic (PV) systems are pivotal in reducing greenhouse gas emissions. However, the adoption of residential rooftop solar systems, particularly from a psychological perspective, remains underexplored. Hence, this study aims to investigate the influence of personal values, beliefs, and norms on the intention to adopt residential rooftop solar systems. By integrating the Value-Belief-Norm (VBN) framework with Norm Activation Theory (NAT) and the norm internalization process, the research seeks to provide a more nuanced understanding of the environmental and sustainability context. This study employs a non-probability purposive sampling method, collecting 303 valid responses from individuals who do not currently use residential rooftop solar systems, live in landed houses, and are involved in primary household decision-making. Data were analyzed using SmartPLS software. The findings confirm all hypothesized relationships, except for the impact of egoistic values on both the new ecological paradigm and awareness of consequences, as well as the influence of descriptive norms on personal norms. This paper introduces a novel approach by adapting the VBN model to predict the intention to use residential rooftop solar systems through several key modifications: integrating ecological values and openness to change, establishing connections between different values and beliefs (such as altruistic, biospheric, egoistic, openness to change, and ecological values) and awareness of consequences, and incorporating the influence of response efficacy, injunctive social norms, and descriptive norms in positively shaping personal norms.

A Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

Solar energy plays a critical part in lowering CO2 emissions and other greenhouse gases when integrated into the grid. Higher solar energy penetration is hindered by its intermittency leading to reliability issues. To forecast solar energy production, this study suggests a three-step forecasting method that selects weather variables with a moderate to strong positive correlation to solar radiation using Pearson correlation coefficient analysis. Low-level data fusion is used to combine weather inputs from a reliable local weather station and an on-site weather station, significantly improving the forecasting model’s accuracy regardless of the machine learning method used. Weather data was obtained from the Kisanhub Weather Station located in Cranfield University, UK and the meteorological station in Bedford, UK. In addition, PV power supply data was obtained from four solar plants. Using the Regression Learner app in MATLAB, the proposed architecture is tested on a utility scale solar plant (1 MW), showing a 6% and 13% prediction accuracy improvement when compared to solely using data from the on-site and local weather station respectively. It is further validated using data from three residential rooftop solar systems (8 kW, 10.5 kW and 15 kW), achieving root-mean square values of 0.0984, 0.0885, and 0.1425 respectively. The data was pre-processed using both rescaling and list-wise deletion methods. Training and testing data from the 1 MW solar plant was divided into 75% and 25% respectively, while 100% of the residential rooftop solar plants was used for validation.

Economic Optimization and Performance Enhancement of Rooftop Solar Power Systems Using Concentrated Solar Technology and Advanced Materials

Abstract: This research investigates the economic optimization and performance enhancement of rooftop solar power systems through the integration of concentrated solar technology and advanced materials. The aim is to assess the viability and effectiveness of these innovations in both residential and commercial settings. By focusing on improving energy efficiency and reducing costs, the study provides a comprehensive economic perspective on the adoption of these advanced solar technologies. Key aspects of the research include the evaluation of lifecycle costs, energy yield, and payback periods, offering insights into the long-term financial benefits and feasibility of implementing such systems. The integration of concentrated solar technology enhances the intensity of solar energy captured, thereby significantly boosting the efficiency of rooftop solar panels. Advanced materials, such as perovskites, multi-junction cells, and nanomaterials, are examined for their potential to improve energy absorption, durability, and overall performance of solar panels. The research employs simulation software to model the performance of these optimized systems under various environmental conditions, providing a detailed analysis of their energy output and efficiency.

Design and Implementation of Self-Cleaning Coated Rooftop Photovoltaic System Supporting Energy Conservation in Small-Medium Enterprises

The implementation of rooftop solar power system for SMEs is one step to provide an examplified pilot project so that the clean energy transition in the economic sector can also be realized. However, difficult operations and maintenance for rooftop solar power plant require a self-cleaning coating design to passively clean the surface of the solar cell module and hence, the performance of rooftop solar power system is maintained. In this research, the design of a rooftop solar power system utilizes global climate data, i.e., air temperature data and duration of sunlight. Long-term trends in solar radiation levels were analyzed using the Mann-Kendall test and Sen's slope analysis to assess the long-term solar energy potential. The self-cleaning layer utilized a mixture of ZnO/TiO2 (1:1) dispersed in water/ethanol (7:3). The results of implementing the solar energy system for food-based SMEs in Indramayu showed a positive response. Solar energy supply from rooftop solar power system with the application of ZnO/TiO2 self-cleaning coating can save energy usage by up to 30% of the monthly electricity costs charged for MSME operations and domestic needs. The ZnO/TiO2 self-cleaning layer is found to be able to maintain rooftop solar power system performance of up to 85% during 9 months of observation.

Waste solar panel generation in Viet Nam: waste estimation and management orientation

Solar energy has emerged as a prominent solution to address the rising energy needs of expanding populations and combat climate change. While the advancement and proliferation of solar photovoltaics have significantly contributed to the decarbonization of energy systems, the improper disposal of end-of-life solar panels could potentially result in significant environmental impacts. Moreover, lack of or inadequate information on the quantity of the obsolete solar panels and their related environmental impacts, as well as proper incentives, and regulatory policies on waste solar panel management are major hinderances for the safe disposal of waste solar panels their materials. In this case study, surveys at solar panel manufacturers, solar power plants and rooftop solar systems have been conducted. The collected information and data are then used to derive solar panel’s lifespan and estimate the amount of waste solar panel till 2050. It is estimated that the cumulative amount of waste solar panel generated in 2022 is about 148 thousand tonnes and is projected to increase to 1.7 million tonnes by 2050. Based on that, sound management solutions toward circular economy have been proposed to properly manage waste solar panel in Vietnam.

Willingness to pay for solar adoption: Economic, ideological, motivational, and demographic factors

Residential solar energy installations are a critical component of the energy transition. Nonetheless, just a small fraction of all eligible households have installed solar panels. We investigate household willingness to pay (WTP) for a residential rooftop solar system using a stated preference approach and including socio-demographic, ideological, economic, and psychological factors.We implemented an online survey of 580 households in New York State who had not previously adopted a residential solar system. Respondents were presented with hypothetical PV systems with varying upfront costs and monthly savings that allow us to understand discount rates and payoff preferences. This allowed us to explore not only WTP and how it varies across the factors described above, but also how those factors affect discount rates and attitudes towards uncertain future payoffs from the systems. We limit our analysis to New York to control for variation in solar adoption policies from state to state, but these results are broadly generalizable to other US States and, with caveats, to advanced industrialized democracies.We find an average WTP of $7388.5 for installing a residential rooftop solar system. Respondents' WTP is $11.66 in upfront costs for each additional $1 of average monthly savings. We also find substantial heterogeneity in WTP and in trade-offs between upfront costs versus savings. Age, children in households, income, education, motivation, and ideology are all independent factors associated with WTP. We discuss a range of implications for policy and marketing to further increase rates of adoption in the future.

Factors influencing the decision to use rooftop solar power systems in Vietnam

Factors influencing the decision to use rooftop solar power systems in Vietnam

Financial Implications of Rooftop Solar Penetration in Sri Lanka from Utility Point of View

Solar is one of the fast growing and economical renewable power generation sources. The intention of development of solar power generation is to promote clean energy while addressing the basic requirement of uninterrupted and reliable electricity supply.The Sri Lankan government decided to adopt a policy that would use subsidies to encourage the growth of solar PV-based electricity. As a result, the market developed with a large number of customers eager to install solar rooftop systems, and they received strong assistance from solar power service providers. Hence, the utility is required to absorb the solar energy produced and this study focuses on the impact of solar penetration to the utility.System dispatch data for year 2019 and rooftop solar generation data for a period of 6 months of year 2019 were considered for the analysis in this paper. The model compares the financials of two scenarios to estimate the impact to the utility. The base case scenario, which is business as usual with the already installed solar generation in the system and No solar scenario which assumes that there is no solar in the system and therefore the demand is met by other available generation capacities in the system.This paper examines the two scenarios with careful calculations of how the system can still run without solar in the system. Daily demand patterns were also analysed and then expanded to months and summarized for the year. This research focuses the financial impact of solar electricity penetration to the national grid and how everyone can still be benefitted.

Performance analysis of drone sqadron optimisation based MPPT controller for grid implemented PV battery system under partially shaded conditions

In recent years, growing consumer demand for sustainable energy is driving down costs and paving the way for more clean energy in the future. Since these energies are sporadic, and the load pattern does not correlate to their generation pattern, a battery storage system is required. Operating dispersed alternative energy sources, connected to the grid in this situation makes energy control an unavoidable task. The difficulty is brought on by things like intermittent sources, daytime costs, solar panel and battery size restrictions, and limitations in battery charging and discharging rates. Moreover, integrating energy storage devices into the power system network is one of the recommendations made in this work to increase the performance and dependability of these systems. Compared to the existing works reported in the literature, this study offers enhanced control techniques for hybrid Photovoltaic and Battery Energy Storage System under fluctuating atmospheric scenario. Here, an innovative approach called Drone Squadron Optimisation, which tracks the Global Maximum Power Point, is used get maximum power. Further, suggested approach is tested with various partial shading instances and the uniform irradiance condition to validate it. This research also investigates photovoltaic models and the status of the battery storage device for improved energy management in the system. Finally, the proposed algorithm assists in quickly identifying the potential benefits of a grid-connected, battery-powered rooftop solar system.

Moderating effect of subsidy policy on intention to purchase residential rooftop solar panel systems

PurposeThe adoption of residential rooftop solar panel systems (SPS) in India is at a nascent stage. Therefore, this study aimed to examine the factors affecting consumers’ intention to purchase SPS by expanding the theory of planned behavior (TPB) with three environmental psychology factors. The study was targeted at potential users’ intention to purchase SPS, thus it further explored the moderating role of perceived government subsidy policy (PGSP) in determining consumers’ purchase intention of SPS.Design/methodology/approachUsing G*power software, the minimum sample size of 189 was calculated; accordingly, 292 valid responses were gathered from potential users of SPS from three Indian states, namely Rajasthan, Punjab and Haryana, via an online questionnaire survey with the help of purposive sampling method. Structural equation modeling technique of partial least squares was employed to analyze the data.FindingsResults demonstrated that attitude, subjective norms, perceived behavioral control, perceived consumer effectiveness (PCE) and PGSP significantly influence purchase intention of SPS. Green trust and green self-identity did not influence the purchase intention of SPS. Further, PGSP strengthens the effect of attitude, green trust, PCE on purchase intention of SPS while it weakens the effect of subjective norms on purchase intention of SPS.Originality/valueThis study contributes to the existing literature by integrating green trust, green self-identity, PCE and PGSP into the TPB model to better understand factors affecting consumers’ purchase intention towards SPS in India.

PERANCANGAN PEMBANGKIT LISTRIK TENAGA SURYA (PLTS) PADA ATAP GEDUNG WISTI SABHA BANDAR UDARA INTERNASIONAL I GUSTI NGURAH RAI

The installed PLTS capacity in Bali is currently still 3.44% of the target given by the General National Energy Plan (RUEN) of 108 MWp in 2025. The island of Bali has limited land availability so rooftop PLTS is a solution. The design of the rooftop PLTS was carried out on the roof of the Wisti Sabha Building at I Gusti Ngurah Rai International Airport. The research uses PVSyst simulation software while the investment feasibility method uses the Benefit-Cost Ratio (BCR), Net Present Value and discounted payback period (DPP) methods. Based on the simulation results, the rooftop PLTS capacity is 56.6 kWp with energy production of 98,009 kWh/year. The B-CR value obtained is 2.23, the net present value is IDR 707,436,838.55 and the DPP is 7 years, with a rooftop solar system life of 25 years.

Toward residential decarbonization: Analyzing social-psychological drivers of household co-adoption of rooftop solar, electric vehicles, and efficient HVAC systems in Georgia, U.S.

The marketplace of climate solutions has grown considerably. Three technologies, in particular, exhibit strong potential for disruptive change and advancement in the residential sector: electric vehicles (EVs), rooftop photovoltaics (RPVs), and efficient heating, ventilation, and air conditioning (HVAC) systems. Many scholars have studied the adoption of these technologies; we address their co-adoption. Using a survey conducted in Georgia, we examine pro-environmental behavior, risk tolerance, and energy-related knowledge as social-psychological drivers for the co-adoption of RPVs, EVs, and efficient HVACs (including heat pumps). We conclude that some but not all of these drivers are relevant to the adoption and co-adoption of the three transformational climate solutions. Pro-environmental behaviors, for instance, appear to create conditions for “positive spillover,” propelling consumers toward adopting multiple climate solutions, whereas energy knowledge has no clear relationship with co-adoption. At the same time, the = influence of these drivers are unique to different combinations of technologies – one notable example is the significance of risk tolerance when RPV is added to technology bundles. Our paper contributes to the literature by broadening the understanding of the adoption of bundled (or co-adopted) climate solutions.

Hybrid power plant using synchronization controller system to save electricity cost

The application of hybrid energy power plants is one solution to save electricity cost in buildings of government agencies, industries, and universities. The problem with using hybrid power plants that use solar energy sources and paid electricity networks is that sunlight energy cannot produce energy consistently from sunrise to sunset. Maximum energy can only be obtained when the sun is vertically acceptable to the photovoltaic (PV). This results in electrical loads having to be disconnected or switched back to the grid. The application of an electrical power sharing system synchronization controller system (SCS) can automatically regulate the use of electrical energy to low PV energy. The results of research on the application of hybrid PV using the SCS system with a rooftop solar panel system at the Gorontalo State University Building can produce a total electrical power of 600,975 kWh. The need for electrical power from January to September 2022 amounted to 859,151 kWh. The SCS hybrid power plant can reduce the use of paid electrical energy and its costs by 83.60%. The investment, operational, and maintenance cost requirement is IDR 10,747,886,801. The return on investment (ROI) analysis results show that the return on investment can be achieved for up to 34 years.

Advancing Solar Rooftop Power Generation: A Review on the Integration of Concentrated Solar Technology and Advanced Materials with Economic Perspectives

Abstract: This review paper offers a thorough analysis of the integration of concentrated solar technology and advanced materials in solar rooftop power generation, with a primary emphasis on optimizing efficiency and economic viability. As the demand for sustainable energy solutions intensifies, harnessing concentrated solar energy on rooftops presents a promising avenue for meeting these challenges. The paper explores current advancements in concentrated solar technologies, including solar concentrators, parabolic troughs, and solar towers, elucidating their working principles and efficiency gains. Concurrently, the integration of advanced materials, such as high-efficiency photovoltaic materials, thermal storage materials, and coatings, is discussed for their role in enhancing the overall performance and durability of rooftop solar systems. A critical examination of the economic aspects associated with these technologies forms a pivotal aspect of this review, encompassing an evaluation of initial investment costs, operational expenses, and potential returns on investment. Economic models and case studies are presented, offering valuable insights into the financial implications and feasibility of widespread adoption.

Efficiency Comparison of Floating, Ground, and Rooftop Solar Systems: Environmental and Social Impacts of Floating Solar Grids

The global fossil fuel shortage and environmental concerns underscore the imperative for transitioning to renewables. Developing nations like Sri Lanka are prioritizing green technologies, notably solar energy, to bridge the gap between current usage and its substantial potential. This study compares technical efficiency among floating, ground, and rooftop solar in Sri Lanka. Analyse local perceptions of floating solar. Assess the environmental impact and sustainability of floating solar systems in Sri Lanka. This study compares the energy production efficiency of floating solar, ground solar, and rooftop solar systems in Sri Lanka. This study compares the technical efficiency of floating, ground-mounted, and rooftop solar systems. Kilinochchi, chosen for floating solar, a nearby ground solar site facilitates a direct comparison, and Mass Vidiyal in Kilinochchi represents rooftop solar. The study strategically gathers data from inverters to assess performance metrics. The goal is a representative analysis, minimizing solar irradiance variations for accurate comparisons. Conducting a literature review to analyse the environmental impact of floating solar systems, drawing insights from past published research papers, and A socio-economic survey was conducted among the local community to assess the socioeconomic viability of a proposed floating solar plant near Chandrika Lake. The survey considered factors such as job creation, local employment opportunities, skill development, and alignment with national energy policies. Floating solar systems were found to have the highest energy generation capability and efficiency, followed by rooftop solar systems, while ground-mounted solar systems had lower energy output. The advantages of floating solar systems over ground-mounted systems were significant (43.69% advantage) and outperformed rooftop solar systems (30.81% advantage). According to the survey, stakeholder engagement and mitigation measures were identified as crucial, considering concerns related to water quality, safety, fisheries, agriculture, and the aesthetic value of the lake This study highlights technical efficiency, socioeconomic viability, and environmental impact of solar systems in Sri Lanka, emphasizing responsible deployment. While floating solar exhibits energy efficiency, addressing altered water flow and aquatic habitat concerns through mitigation measures is crucial for sustainable implementation.
 
 Keywords: Solar energy, Floating solar, Environmental impact, Social impact, Renewable energy

Comparison of machine learning models for the estimation of solar power generation in Australia

Solar power is a renewable energy source that contributes a lot to improving the environmental sustainability of energy production. In Australia, rooftop solar panel systems are installed for power generation. By seeking the optimal installation strategy, people could develop more efficient technologies and systems. In this work, data related to power generation was gathered between January 1 and December 31, 2022. This article only analyzes qualitative data in the dataset. Firstly, the support vector machine (SVM) model is used to compare the results obtained by removing only one qualitative feature at a time with the results obtained by including all features. It is concluded that the shading condition feature has a significant impact on power generation, and then. By comparing the accuracy of K-nearest neighbor (KNN), Logistic Regression, SVM with Radial Basis Function (RBF) kernel, and Decision Tree, it was found that SVM with RBF kernel is the most suitable classification method for the feature of the shading condition.

Optimizing energy consumption in smart homes: Load scheduling approaches

AbstractRising fuel prices, global warming, and environmental damage are leading to increased demand for rooftop solar energy systems connected to the power grid. The development of smart grids, modern metering systems, and energy management could promote energy conservation in households. In this study, two different meta‐heuristic optimization techniques were employed to schedule the shiftable load in suitable hours for decreasing electricity costs and minimizing peak to average ratio in a smart home while maintaining optimum user comfort. For power generation and storing energy, a grid‐connected residential load with rooftop solar panels, a battery, and an inverter is considered. First, the problem is theoretically described using a load model and an objective function, with the primary goal of reducing power costs by moving the time of usage for certain home appliances. Simulations validate the proposed strategies, which effectively reduce power costs by 4.5% by shifting the time of use, with both optimization algorithms showing similar output. The residential electricity cost before optimization was 507.12 BDT/day, which decreased to 484.33 BDT/day after optimization without compromising load turn‐off.