Rooftop Photovoltaic Systems Research Articles

V-Iq Based Control Scheme for Mitigation of Transient Overvoltage in Distribution Feeders With High PV Penetration

High penetration of rooftop photovoltaic (PV) systems in distribution feeders can give rise to overvoltage during peak generation hours. A well-known solution for this problem is Volt-VAR control method, in which PV inverters mitigate the overvoltage by reactive power absorption. The conventional Volt-VAR scheme calculates the reactive power reference based on a limited bandwidth V-Q droop controller. Although the conventional method is capable of steady-state voltage regulation, it is not effective against voltage overshoots caused by fast solar irradiance variations. In this paper, a new V-Iq based Volt-VAR control scheme is presented to suppress the transient voltage overshoots during cloud passing. In this method, the bandwidth of the Volt-VAR controller is increased to enhance its responsiveness to voltage variations. To prevent instability caused by unwanted interaction between the high bandwidth Volt-VAR controller and the voltage feedforward section of the inner control loop, a low pass filter is added to the feedforward path. Small signal analysis of the proposed method provides a guideline for designing the bandwidths of Volt-VAR controller and feedforward filter. The stability of the proposed method is assessed based on Lyapunov method. Hardware in the Loop (HIL) experimental results are presented to validate the proposed scheme.

A Flexible Rooftop Photovoltaic-Inductive Wireless Power Transfer System for Low-Voltage DC Grid

A rooftop photovoltaic (PV) system is a significant solution of building-integrated centralized generation in the low-voltage (LV) DC grid. The drilling-free rooftop PV-inductive wireless power transfer (PV-IWPT) system for the LVDC grid can reduce the installation and post-maintenance costs, with the elimination of physical cable connections and preventing breaking of thermal bridge and rain penetration between the rooftop and the inside of the building. Moreover, it has inherent isolation properties between the input and the output terminals. However, it is challenging for the PV-IWPT system to simultaneously achieve the maximum power point tracking (MPPT) for the PV panels and the maximum efficiency point tracking (MEPT) for the system even under diverse irradiance conditions. In this paper, we propose an efficient PV-IWPT system, which consists of a series-series IWPT converter, driven by the PV panels and loaded by the LVDC grid directly. Moreover, we apply in the proposed system a particle swarm optimization with an auxiliary Perturb and Observe (P&O) algorithm and a load matching method without wireless feedback communication to realize MPPT and MEPT in the overall PV-IWPT system simultaneously. Finally, we analyze theoretically and verify experimentally the proposed PV-IWPT system in a 500-W experimental platform under different irradiance conditions.

Assessing the Potential of a Rooftop Grid-Connected Photovoltaic System for Gaziantep Islamic Science and Technology University/ Turkey

In this paper, a grid-connected rooftop photovoltaic (PV) system is proposed to fulfill the electricity needs of Gaziantep Islamic Science and Technology University (GIBTU) in Turkey. The proposed system is to be placed on the roof of the Faculty of Engineering and Natural Sciences, which is considered as the most complex and challenging roof on campus. The system production of electricity - taking into account the possible losses caused by light-induced deterioration, soiling, etc. - is determined. The obtained simulation results reveal that installing a 121 kW PV system will be sufficient for meeting the electricity needs of the Faculty of Engineering and Natural Sciences alone, since such system is capable of generating 197.7 MWh annually with an efficiency of 81.51%. However, in order to meet the needs of the whole university, a 933.1 kW PV system - with generation capability of 1524.9 MWh/year - is required. Also, the obtained results unveil that deploying the proposed system - with its relatively low payback period of 2.19 years - will prevent the release of 989.35 tons/year of CO2 emissions into the atmosphere.

Comparison of Simulation Results for 25 kW Power Output Rooftop PV System

The use of electrical energy from renewable energy sources has increased considerably in recent years. Photovoltaic (PV) solar energy, which is one of the renewable energy sources, takes its source from the sun, which is considered an unlimited source. With the widespread use of photovoltaic systems, some legal regulations by governments have been made for their installation. Simulation programs are used for the design, layout, technical and economic analysis of PV systems. In this study, the design was made using the PVsyst, PV*SOL, Solarius programs, and the PVGIS website used in PV systems. The projects are designed to have an output power of 25 kW. According to the simulation results, the PVGIS website provides approximate data, since technical details cannot be entered. In the results of PVGIS and all simulation programs, it has been calculated that the system can produce 42-48 MWh of electrical energy annually. Power Ratio (PR) results of the system were in the range of 78-85%. Annual electrical energy production per installed kW has been calculated to be 1436-1635 kWh/year. It is stated that the annual saved CO2 will be 18.66-22.226 tons /year. When the simulation results are analyzed monthly, the differences between the months are remarkable. The reason for these deviations can be explained by the annual solar radiation (kWh/m2) data and databases used by the programs. It has been observed that the simulation programs consider the monthly average temperatures and sunshine durations of the region. It is thought that there is a need to compare real-time data with simulation results in future studies. It is considered that this study will be helpful for future studies.

Energy performance assessment of a post-retrofit office building using measurement and verification protocol: A case study from KSA

Buildings account for over one third of the global energy consumption and greenhouse gas emissions. While new buildings are being sought to be more efficient, retrofitting of existing building is also critical to improve the energy and environmental sustainability of the building sector. Measurement and Verification (M&V) based energy retrofitting studies are becoming important in presenting the case for energy retrofit solutions. This work presents an energy performance assessment of a retrofitted office building using the International Performance Measurement and Verification Protocol (IPMVP) option B to conduct the M&V. The building, an office block with a built-up area of 7,500 m2, is in the Eastern Province of Saudi Arabia. The work carries out a detailed energy audit of the building to investigate the energy saving opportunities. Of the identified options, five energy efficiency measures (EEMs) are implemented. The energy performance of the building is also helped by the installation of a rooftop Photovoltaic (PV) system. The results indicate that retrofit measures helped reduce the Energy Use Index (EUI) from 458.9 kWh/m2/year to 361.4 kWh/m2/year. The economic analysis finds the compound payback period for the investments to be six years.

A density‐based time‐series data analysis methodology for shadow detection in rooftop photovoltaic systems

AbstractThe majority of photovoltaic (PV) systems in the Netherlands are small scale, installed on rooftops, where the lack of onsite global tilted irradiance (GTI) measurements and the frequent presence of shadow due to objects in the close vicinity oppose challenge in their monitoring process. In this study, a new algorithmic tool is introduced that creates a reference data‐set through the combination of data‐sets of the unshaded PV systems in the surrounding area. It subsequently compares the created reference data‐set with the one of the PV system of interest, detects any energy loss and clusters the distinctive loss due to shadow, created by the surrounding objects. The new algorithm is applied successfully to a number of different cases of shaded PV systems. Finally, suggestions on the unsupervised use of the algorithm by any monitoring platform are discussed, along with its limitations algorithm and suggestions for further research.

Transactive charging management of electric vehicles in office buildings: A distributionally robust chance-constrained approach

In this paper, a new energy management model is proposed to determine the optimal scheduling of an office building which includes electric vehicle (EV) charging piles, batteries, and rooftop photovoltaic systems. To optimally manage the electricity procurement of the building and mitigate the rate of transformer aging, the building energy management system (BEMS) employs the flexibility of batteries and EV charging. In the proposed model, to incentivize EV owners to offer their flexibility, the BEMS organizes a transactive market among plugged-in EVs. To this end, EV owners submit their response curves and the target state-of-charge to the BEMS. Then, the transactive market is cleared to determine the market-clearing price for each EV, the optimal EV charging decisions, and accordingly, the scheduling of office building. Also, to model the correlated uncertainties of solar power generation and demand, the distributionally robust chance-constrained method is employed. Moreover, the “Big-M” technique and the piecewise linear approximation method are utilized to linearize the optimization problem. Finally, the case of a building with 100 charging piles is studied. The numerical results illustrate a decrease in the total operating cost of BEMS and the rate of transformer aging compared to uncontrolled charging and direct control approaches. • Developing a TE model to incentivize EVs’ participation in the energy management program. • Developing a new response curve model for EV owners. • Incorporating the transformer’s loss of life in the proposed TE model. • Developing a distributionally robust chance-constrained building energy management model. • Linearizing non-linear equations to mitigate the computational complexity.

A Review of Peer-to-Peer Energy Trading with Standard Terminology Proposal and a Techno-Economic Characterisation Matrix

Nowadays decarbonisation of the energy system is one of the main concerns for most governments. Renewable energy technologies, such as rooftop photovoltaic systems and home battery storage systems, are changing the energy system to be more decentralised. As a consequence, new ways of energy business models are emerging, e.g., peer-to-peer energy trading. This new concept provides an online marketplace where direct energy exchange can occur between its participants. The purpose of this study is to conduct a content analysis of the existing literature, ongoing research projects, and companies related to peer-to-peer energy trading. From this review, a summary of the most important aspects and journal papers is assessed, discussed, and classified. It was found that the different energy market types were named in various ways and a proposal for standard language for the several peer-to-peer market types and the different actors involved is suggested. Additionally, by grouping the most important attributes from peer-to-peer energy trading projects, an assessment of the entry barrier and scalability potential is performed by using a characterisation matrix.

Design of a Stand-Alone Roof-Top Photovoltaic System for a Residence in Zamfara State, Nigeria

This paper presents in detail the design analysis of a stand-alone photovoltaic power system for a typical residential building in Zamfara State, Nigeria. A photovoltaic power system can be used as a source of electrical power to our homes through the direct conversion of solar irradiance into electricity. The process of harnessing photovoltaic power generating system involves designing, and selection of the different components employed in the system. The success of this process depends on a variety of factors such as geographical location, weather condition, solar irradiance, and load profile. The paper outlines the procedures employed in specifying each component of the stand-alone photovoltaic power system and as a case study, of a medium range energy consumption residence in Zamfara State (Nigeria).

Techno-economic evaluation of a hybrid photovoltaic system with hot/cold water storage for poly-generation in a residential building

There is a growing effort towards the application of solar technologies to meet electrical and thermal demand. However, substantial energy is used in buildings around the world for electricity and thermal comfort. Here we evaluate a novel hybrid solar-powered system for reducing the load on the direct expansion and heat pump unit of a combined heating and air conditioning system while generating electricity. The system combines rooftop photovoltaic (PV) and building-integrated photovoltaic thermal (BIPV/T) systems for electricity generation, while any excess electricity is used to drive a hot and cold water storage system. A residential building in Tehran is used as a case study, and the results are computed via MATLAB, TRNSYS, and Carrier HAP software. The system is shown to outperform both rooftop PV and BIPV/T systems alone, generating at least 50% more electricity while reducing the heating and cooling loads on the machinery by at least 60%. The system also enjoys a payback time of 2.87 years. The impact of thermal comfort setpoints, in addition to inflation and discount rates, are also evaluated via a sensitivity analysis involving several key performance metrics, namely the hot and cold water storage volumes, the size of the desiccant wheel, and the payback time. The cooling load is found to have the greatest influence on the cold water storage volume and the desiccant size, with 80.1% and 41.2% variations for baseline variations of ±20%. With a 57.7% increase, the heating load is found to have the biggest influence on the hot water storage volume. With a 27.1% variation, inflation has the strongest effect on the payback time.

Benefit Optimization and Energy - Economy Environmental Analysis of Solar Rooftop Photovoltaic System at Industrial Segment in Indonesia

This study aims to compare 4 scenarios of solar rooftop photovoltaic system technology that is used in the industrial segment in two different locations in Indonesia. Comparisons were made using energy, economic and environmental analysis methods and continued with optimization using linear programming methods. The results of the study show that scenario 2 solar photovoltaic system can produce more electrical energy and CO2 that can be reduced than in the other scenarios. While scenario 4 solar photovoltaic system is a scenario with better economic value and optimal benefits value than the other scenarios.

Environmental and Economic Impact Assessments of a Photovoltaic Rooftop System in the United Arab Emirates

The shift toward renewable energy resources, and photovoltaic systems specifically, has gained a huge focus in the past two decades. This study aimed to assess several environmental and economic impacts of a photovoltaic system that installed on the rooftop of an industrial facility in Dubai, United Arab Emirates (UAE). The life cycle assessment method was employed to study all the flows and evaluate the environmental impacts, while several economic indicators were calculated to assess the feasibility and profitability of this photovoltaic system. The results showed that the production processes contributed the most to the environmental impacts, where the total primary energy demand was 1152 MWh for the whole photovoltaic system, the total global warming potential was 6.83 × 10–2 kg CO2-eq, the energy payback time was 2.15 years, the carbon dioxide payback time was 1.87 years, the acidification potential was 2.87 × 10–4 kg SO2-eq, eutrophication potential was 2.45 × 10–5 kg PO43-eq, the ozone layer depletion potential was 4.685 × 10–9 kgCFC-11-eq, the photochemical ozone creation potential was 3.81 × 10–5 kg C2H4-eq, and the human toxicity potential was 2.38 × 10–2 kg1,4-DB-eq for the defined function unit of the photovoltaic system, while the economic impact indicators for the whole system resulted in a 3.5 year payback period, the benefit to cost ratio of 11.8, and 0.142 AED/kWh levelized cost of electricity. This was the first study to comprehensively consider all of these impact indicators together. These findings are beneficial inputs for policy- and decision-makers, photovoltaic panel manufacturers, and photovoltaic contractors to enhance the sustainability of their processes and improve the environment.

Rooftop PV or Hybrid Systems and Retrofitted Low-E Coated Windows for Energywise and Self-Sustainable School Buildings in Bangladesh

The electricity crisis is a common issue in Bangladesh; however, recently the electricity scenario has been getting worse due to various reasons including power generation and distribution all over the country. Meanwhile, the large number of people requires a huge amount of energy which is not possible to be met by the national grid due to the limited power generation from different plants. Among all renewable energy sources, the solar photovoltaics (PV) system is the best choice as a generation source, either off-grid or with a grid-tied connection, to reduce the pressure on the national grid. In Bangladesh, there are more than 175,000 schools, and it is possible to generate a huge amount of renewable (solar) power to supply all the schools by using rooftop PV systems. We propose a new approach that combines solar energy harvesting and savings to make the schools self-sufficient and energywise. We performed a Hybrid Optimization Model for Multiple Energy Resources (HOMER) pro simulation and find that it was possible to generate approximately 200 megawatts (MW) of power. We conducted a feasibility study on generating power from rooftop PV systems on school buildings and reduced the power consumption using retrofitted thin-film-coated glass by around 16–20% per day depending on the school size, which can help the national power grid system by either making all the schools off-grid or grid-connected to supply power to the national grid. In addition, we perform a HelioScope simulation to investigate the maximum upscaling of PV sizing for the rooftops of school buildings in Bangladesh to realize how to make each school a mini solar power station in the future. The HelioScope simulation performance showed that it was possible to generate approximately 96,993 kWh per year from one school building.

IRMAC: Interpretable Refined Motifs in Binary Classification for smart grid applications

Modern power systems are experiencing the challenge of high uncertainty with the increasing penetration of renewable energy resources and the electrification of heating systems. In this paradigm shift, understanding electricity users’ demand is of utmost value to the retailers, aggregators, and policymakers. However, behind-the-meter (BTM) equipment and appliances at the household level are unknown to the other stakeholders mainly due to privacy concerns and tight regulations. In this paper, we seek to identify residential consumers based on their BTM equipment, mainly rooftop photovoltaic (PV) systems and electric heating, using imported/purchased energy data from utility meters. To solve this problem with an interpretable, fast, secure, and maintainable solution, we propose an integrated method called Interpretable Refined Motifs And binary Classification (IRMAC). The proposed method comprises a novel shape-based pattern extraction technique, called Refined Motif (RM) discovery, and a single-neuron classifier. The first part extracts a sub-pattern from the long time series considering the frequency of occurrences, average dissimilarity, and time dynamics while emphasising specific times with annotated distances. The second part identifies users’ types with linear complexity while preserving the transparency of the algorithms. With the real data from Australia and Denmark, the proposed method is tested and verified in identifying PV owners and electrical heating system users. The performance of the IRMAC is studied and compared with various state-of-the-art methods. The proposed method reached an accuracy of 96% in identifying rooftop PV users and 94.4% in identifying electric heating users, which is comparable to the best solution based on deep learning, while the speed of the inference model is a thousand times faster. Last but not least, the proposed method is a transparent algorithm, which can tackle the concerns regarding the agnostic decision-making process when policies prohibit some machine learning methods.

Techno-economic analysis of photovoltaic rooftop system on car parking area in Rayong, Thailand

The intensity of solar radiation in Thailand is sufficient to produce electricity, thus the government has unconditionally promoted electricity production from solar energy, known as photovoltaic power system. Although it can reduce energy costs, it should also be environmentally friendly. This research aims to design and evaluate the photovoltaic rooftop system by concerning economic feasibility, cost of energy, and the compensation for carbon dioxide emissions. The research methodology also calculates the installation area and the solar power generation potential. Carbon dioxide emissions compensation and cost-effectiveness tools are used to evaluate the overall system. The results revealed that the photovoltaic rooftop system had the production capacity of 31.49 kilowatt-hours with an installation area of 184 m2. Solar panels orient to north direction with 11 degrees tilt from horizontal plane. The PV rooftop system generated the highest electricity around 137.103 kilowatt-hours per year and electricity production per installed system size is 4.354 kilowatt-hours per kilowatt-power. Within the period of 25 years and interest rate of 6.3145 percent, this project would be worthwhileness for the investment because the payback period is 6.83 years, the net present value is 1,523,571.70 baht, internal rate of return is 17.85 percent, benefit–cost​ ratio is 1.77, cost of energy is 2.31 baht per kilowatt-hour, in addition to the project can reduce carbon dioxide emissions by up to 643.77 tons of carbon dioxide equivalent. The promotion of electricity production from solar energy will increase the sustainability of energy and environment. In addition, the project sensitivity study indicated that initial cost, interest rate, and electricity price will be the important factors in making a decision to initiate a project.

A Novel Time-of-Use Pricing Based Energy Management System for Smart Home Appliances: Cost-Effective Method

Smart grids (SG) allow users to plan and control device usage patterns optimally, thereby minimizing power costs, peak-to-average ratios (PAR), and peak load demands. The present study develops a typical framework of a home energy management system (HEMS) for SG scenarios using newly limited and multi-limited planning approaches for domestic users. Time-of-use pricing (TOUP) is used to develop, handle, and manage the optimization problem properly. As a capable method for optimizing the proposed problem, this paper uses a robust meta-heuristic algorithm named wind-driven optimization algorithm (WDOA) and compares it to the other optimization algorithms in order to demonstrate its efficiency. In addition, it integrates a rooftop photovoltaic (PV) system with the system in order to show that all devices are cost-effective if managed properly. Eight diverse case studies are analyzed using a variety of time planning algorithms. The simulation results advocate for the quality and high performance of the proposed model by minimizing the total cost and managing energy consumption economically.

High resolution photovoltaic power generation potential assessments of rooftop in China

Rooftop photovoltaic system plays an important role in solar energy power generation especially in urban. In this paper, we present an assessment method for the PV power generation potential of rooftop in China. Using machine learning model processes the big data that consists of the gross domestic product, building footprint, road length and population, at a high geographic resolution of 10 km by 10 km. The result shows that the rooftop generation potential in China is 3.27×109 MWh annually, which is close to half of the total electricity generation of China mainland in 2020, and will contribute to 2.41×109 tons of CO2 emission reduction per year. The regional results are counted by provinces and cities, showing Shandong province is the one with highest potential of 0.275×109 MWh. On the whole, the western region covers a large area with sufficient solar radiation, while the eastern region has greater photovoltaic power generation potential because of its available roof resources. The development potential of first tier, new first tier and second tier cities is generally greater than that of third and fourth tier cities.

Comparative investigation of energy-saving potential and technical economy of rooftop radiative cooling and photovoltaic systems

Building-integrated radiative cooling (RC) and photovoltaic (PV) systems are promising renewable technologies harvesting energy from outer space and the sun, respectively, and can contribute to carbon neutrality. However, due to the limited building envelope area, it is significant to compare the energy-saving potential and technical economy of these two technologies, which helps to determine the system form under different working conditions. This study establishes the thermal models for rooftop RC and PV systems to simulate their temperature, heat transfer flux, and energy-saving performance. Then the energy-saving and economic indicators for comparative investigation are proposed, in which the cooling load reduction is converted into electricity saving to be compared with PV’s electricity generation. The comparison results show that RC roof has a lower energy-saving potential than PV roof during the cooling season in Beijing, China (the energy saving ratio of RC to PV is 0.536). However, the economic cost of equivalent electricity saving during the life cycle is $0.011 and $0.034 per kilowatt-hour for RC and PV systems, respectively, indicating that RC roof is more economical. In addition, applicability analysis indicates that the total cooling capacity of RC roof throughout the cooling season is larger in western and southern China, while the energy-saving potential of PV roof is higher in western and northern China. Moreover, the effects of meteorological parameters, indoor conditions, building roof characteristics, and surface optical properties on RC and PV roofs’ performance are thoroughly analyzed. The parametric analysis shows that RC roof is suitable for buildings with high heat dissipation demand and lightweight envelope structures. It is calculated that the energy yield of the RC roof is comparable to that of the PV roof in a telecommunication base station. This study will pave the way for maximizing the energy-saving potential of limited building roofs and contribute to the efficient utilization of renewable energy.

Quantitative impact assessment of temperature on the economics of a rooftop solar photovoltaic system.

This paper analyzes the economics of a grid-interactive rooftop solar photovoltaic (PV) system and the impact of the temperature on it. The analysis related to energy metrics, lifecycle costing, and environmental economics was performed considering the PV system's life as 30years. The system economics is also compared at different conditions like theoretical, temperature-corrected, and real electricity generation data. The parameters like energy payback time (EPBT), energy return on energy invested (EROI), and lifecycle conversion efficiency are determined as 5.95years, 5.04, and 0.078, respectively, based on actual generation. The unit electricity cost of the rooftop PV system was estimated as INR 5.37 at the 5% interest rate. The electricity cost varies with the interest rate variation and operation system life. The results show a reduction in overall economic performance on the increase in module temperature. The effect of temperature on the economics of the system is presented in terms of the per degree rise of module temperature. One degree increase of module temperature 8.5days in EPBT of the PV system increases, and INR 0.021 increases in the unit cost of electricity considering a reference temperature 25°C. A PV system has environmental benefits by reducing greenhouse gas emissions, which are also affected by the rise of module temperature. The system lost INR 355.93 in carbon credits at an increase of one-degree module temperature.

The technical and economic potential of urban rooftop photovoltaic systems for power generation in Guangzhou, China

With the adoption of carbon peak and carbon neutrality targets, countries and cities must spend more on renewable energy to replace polluting and emitting traditional fossil energy sources. Distributed rooftop photovoltaic (PV) cells, in comparison to hydropower and wind generation, use only space and radiation resources and are the least restricted by geography and climate, making them a significant choice for communities looking to create green electricity. Using Guangzhou, a city in southern China, as an example, we offer four installation scenarios based on rooftop area data and research on relevant characteristics and analyze the technical and economic potential of PV power generation on the rooftops of urban buildings. The following conclusions are reached: the rooftop area in Guangzhou suitable for PV installation is 391.7 km2, with a maximum potential power generation capacity of 44.06–72.12 billion kWh per year, which could lower Guangzhou’s greenhouse gas emissions from the power industry by 70.12–100%. The optimal economics are reached with a 20° installation tilted angle and monocrystalline silicon PV panel material, with a 6-year payback period.