Benchmarking the Performance of Solar Installers and Rooftop Photovoltaic Installations in California

Adoption of solar photovoltaic (PV) power generation systems has been accelerating around the world, contributing to the debate about the future of policy and regulation in a high distributed energy resources future. As one of the leaders in solar investment in Southeast Asia, Thailand has recently shifted its policy framework for the support of small scale, distributed solar PV systems from subsidizing power export through feed-in tariff toward a policy that is focused on self-consumption. This paper investigates stakeholder perspectives of the detailed design options for self-consumption schemes for supporting rooftop solar PV installations. The research methodology employed questionnaires and focus group discussion in order to capture stake-holder perspectives for each element of rooftop solar PV self-consumption schemes. In all, the data derived from questionnaires and focus group discussion involved a total of 72 stakeholders. The results indicate that most stakeholder groups expressed a strong desire for compensation for excess generation of PV electricity from rooftop PV systems. While the majority of electric utilities prefer a system of net billing with real-time buyback, designed to minimize revenue losses, consumers and policymakers preferred a net-metering-based compensation scheme for supporting use of rooftop PV electricity in Thailand.

Assessment of large commercial rooftop photovoltaic system installations: Evidence from California

More than two hundred sixty grid-tied photovoltaic (PV) systems sized 30 kW to 1.1 MW installed in California during 2002 through 2004 received partial funding through the Self-Generation Incentive Program (SGIP). The SGIP is administered statewide by PG&E, SCE, SoCalGas, and the San Diego Regional Energy Office. The incentive is structured as a one-time capacity based payment made at the time of system completion. The first PV system incentive was paid in Summer 2002. Through the end of 2004, a total of 269 PV systems had received financial support through the program. The cumulative generation capacity of these systems exceeded 30 MW and corresponded to $101 million of incentives paid. While originally slated to run through 2004, recently the program was modified and extended through the end of 2007. PV systems participating in the program are being monitored to support evaluation of the program. These data have been used to assess impacts of the Program on peak demand and energy consumption. These data have also been incorporated into the Program’s cost-effectiveness assessment. Well over one-half of the PV systems have already been subject to metering yielding 15-minute interval generator output data. The cumulative size of the directly monitored PV systems currently exceeds 33 MW as of late 2005. In 2004, the statewide California Independent System Operator (ISO) electrical system peak occurred on September 8 during the 16th hour (from 3 to 4 PM PDT). During this hour the electrical demand for the California ISO reached 45,562 MW. On this day, there were 235 PV systems funded under the SGIP installed and operating; interval-metered data are available for 107 of these projects. The resulting estimate of peak demand impact coincident with the ISO peak load totals 9,938 kW. The estimated peak demand impact corresponds to 0.39 kW per 1.0 kWRebated of PV system size and is based on rebated capacity. Those unfamiliar with PV system size ratings and PV system operating characteristics may be surprised that the overall weighted-average peak demand impact was not substantially higher at this hour and time of year. To help put this result in perspective, it can be compared to a simple engineering estimate of peak power output based on published information regarding PV system performance. First, we begin with 1 kW [basis: rebated size] of horizontal PV system capacity. For purposes of determining rebates, PV system sizes are calculated as the product of cumulative estimated module DC power output under PTC conditions and inverter maximum DC to AC conversion efficiency. Factors such as manufacturing tolerance, soiling, module mismatch, temperature effects, and wiring losses may result in actual full-sun power output levels of about 0.76 kW/kWRebated. When the 3 to 4 PM angle of incidence effects for the month of September are included the expected output value drops significantly further. The peak-day operating characteristics of the 107 PV projects for which peak-day interval-metered data were available are summarized in the box plot of Figure 4. System sizes were used to normalize power output values prior to plotting summary statistics of PV output profiles for individual projects. The normalized values represent PV power output per unit of system size. Treatment in this manner enables direct comparison of the power output characteristics of PV systems of varying sizes. The vertically oriented boxes represent ranges within which 75% of project-specific values lie. The vertical lines represent the total range (i.e., maximum and minimum) of project-specific values. The energy production of the group of metered PV systems varied according to season. In Figure 7, normalized energy production by month is illustrated (on the right axis). These values represent the monthly average capacity factor for the on-line PV system capacity. As expected, normalized energy production levels reach their maximum values in the summer season and decrease towards the winter season as the intensity and duration of incident solar radiation falls off, coupled with increased incidence of storms and other weather disturbances off the Pacific Ocean, which affect the availability of solar radiation upon the PV modules.

Solar power energy in some countries can be the most potential renewable energy to overcome lack of energy and environmental problems. Indonesia is one of the examples. One of the promising cities to install photovoltaic (PV) systems is Makassar, which has average 5.83 kWh/m2/day of solar irradiance (Meyta, 2011). However, until 2016, there is still no solar panel installation in Makassar (PLN, 2015). In addition, general lack of research in assessing potential of PV systems in Makassar makes PV system difficult to develop. This study therefore set out to assess PV system potential in Makassar which its objectives are to determine 1) total available area for rooftop and large-scale PV systems in Makassar, 2) economy feasibility and 3) environmental impact due to PV installation. Three cases have been analyzed in this study, first, PV systems for residential rooftop, second, PV systems for large-scale (mega solar) in Makassar, and third, PV systems for large scale in outside Makassar and radius 20 km from center of Makassar. ArcGIS10.3 software is carried out to estimate available area for PV installation. Furthermore, RetScreen 4 software was used to conduct PV system capacity and its energy yield and to evaluate economy analysis such as internal rate of return and cost of energy. As the result, the total available area for residential rooftop PV system is evaluated to be 13.8 km2, which potential installed capacity is estimated to be 2044 MW. Total available area for large-scale PV system in Makassar and outside Makassar are 19.3 km2 and 231.3 km2, which estimated 851 MW and 10,179 MW of installed capacity, respectively.

Solar ship, which integrates the solar photovoltaic (PV) system into its own ship power system, is becoming one kinds of most promising and fastest developing green ship. Since the electric energy transformed by PV system is provided to the power load through the ship's distribution system, the output power of synchronous generator will be reduced in proportion. Especially, if the matching relationship among solar PV system, energy storage system and the power load requirement is precisely analyzed and the operation characteristics and reliability of solar inverter have already meet the strict test standards for marine equipment, the design capacity of synchronous generators could also be reduced. The off-grid mode and grid mode are the main way of integrated application of solar power photovoltaic system of ship. And the solar PV system is a kind of inverter power supply, which is essentially based on the electronic inverted technology, so PV system can be regarded as a ‘fragile power source’ with ‘zero inertia’. Therefore, the influence of solar photovoltaic grid-connected system to the power flow and power quality of the ship power system cannot be ignored. And the effect of photovoltaic system on the power quality of transient and steady-state and flow calculation remains to be studied. This paper mainly research the changes of power load flow calculation(PLFC) on the system, using the toolbox PSAT of MATLAB Simulink. This paper research the PLFC on the system of different solar photovoltaic systems access points, and analysis the experimental results. The results show that, under the premise of the normal operation of the ship electric power system, the improvement of the capacity of solar photovoltaic system in ship , and different access modes of photovoltaic grid-connected system, have slight impact on the power flow of power system, indicating that the photovoltaic grid-connected system in ship is stable, an appropriate increase in the capacity of PV system is feasible. The results is of certain significance of secure application of grid connected photovoltaic system in this paper.

The transition to renewable energy sources is pivotal in addressing global climate change challenges, with rooftop solar photovoltaic (PV) systems playing a crucial role. For informed decision-making in energy policy, it is important to have a comprehensive understanding of both the economic and environmental performance of rooftop solar PV. This study provides a high-resolution analysis of existing rooftop solar PV systems in Switzerland by assessing the robustness of the potential estimation to properly derive the amount of electricity generated by individual systems, and subsequently quantify the levelized cost of electricity and life cycle greenhouse gas (GHG) emissions of electricity generation from PV and compare them with those of grid electricity supplies. Our results indicate substantial geographical variations between potential estimations and real-world installations, with notable underestimations of approximately 1.3 Gigawatt-peak, primarily for systems around 10 kWp in size, mainly due to the quality of input data and conservative estimation. The study finds that in many regions and for most of the installed capacity, electricity generated from rooftop PV systems is more economical than the grid electricity supply, mainly driven by factors including high electricity prices, larger installations and abundant solar irradiance. The GHG emissions assessment further emphasizes the importance of methodological choice, with stark contrasts between electricity certificate-based approaches and others that are based on the consumption mix. This study suggests the need for more accurate geographical potential estimations, enhanced support for small-scale rooftop PV systems, and more incentives to maximize the potential of their roof area for PV deployment. As Switzerland progresses towards its renewable energy goals, our research underscores the importance of informed policymaking based on a retrospective analysis of existing installations, essential for maximizing the potential and benefits of rooftop solar PV systems.

BackgroundTechnology is deployed to take the advantage of the ultimate energy from the sun (solar energy) to be used as heat or clean electricity. This energy is classified as “sustainable energy” or “renewable energy” because it requires a short period to naturally replenish the used energy. The application of solar energy involves the conversion of the natural energy resource into a usable form, either as heat or as electricity. The device consists of solar cells made from semiconductor materials, such as silicon, cadmium telluride, gallium arsenide, and so on. Solar potential is both location- and climate-dependent; it is characterised by low energy intensity and intermittency, which limit its application; an improvement in photovoltaic (PV) system performance will facilitate more deployment of the clean electricity system. Therefore, this study provides PV potential and system information required for reliable and optimised solar PV systems at chosen locations. This work uses a 5-stage solar PV system assessment and system performance evaluation utilising Solargis Prospect software. The PV potential and system performance of nine selected site locations in South Africa was conducted using this method. The nine PV site locations are Bloemfontein (Free State), Germiston (Gauteng), Mahikeng (North-West), Mbombela (Mpumalanga), Musgrave (Kwazulu-Natal), Musina (Limpopo), Port Nolloth (Northern Cape), Port Elizabeth (Eastern Cape), and Worcester (Western Cape).ResultThe results of the study were categorised into PV meteorological and system performance parameters as follows. Photovoltaic meteorological parameters—the site in Mahikeng has the highest global horizontal irradiance (GHI), 2156 kWh/m2, and a corresponding specific PV power output (1819.3 kWh/kWp), closely followed by Bloemfontein (2111.5 kWh/m2, 1819.4 kWh/kWp) and Port Nolloth (2003.2 kWh/m2, 1820.5 kWh/kWp). The lowest GHI (1645.1 kWh/m2) and specific PV power output (1436.6 kWh/kWp) were recorded in Musgrave. Photovoltaic system performance parameters—the range of performance ratio (PR) between 75.8 and 77.7% was reported across the nine sites. This ratio met the acceptable benchmark of PR. The highest specific PV power output loss, 118.8 kWh/kWp, was obtained at sites in Bloemfontein, Mahikeng, and Port Nolloth, while the lowest, 93.8 kWh/kWp, was in Musgrave.ConclusionsThe results of the solar PV potential assessment and the evaluation of PV systems performance in the chosen sites across the nine provinces of South Africa show huge PV potential and energy yield. From the results, it was observed that the range of the yearly average of: (1) GHI among the sites is 1645.1–2156 kWh/m2; (2) direct normal irradiation among the sites is 1785.3–2559.3 kWh/m2; (3) diffuse horizontal irradiation among the sites is 512.5–686kWh/m2; (4) global tilted irradiation among the sites is 1849.2–2397.1 kWh/m2; (5) the temperature (TEMP) among the sites is 16–23 °C; (6) specific PV power output (PVOUT specific) among the sites is 1436.6–1820.5 kWh/kWp; (7) total PV power output (PVOUT total) among the sites is 14.366–2397.1 MWh; and (8) the performance ratio among the sites is 75.8–77.7%. Based on the solar resource and performance results of the PV system obtained, the deployment of monocrystalline solar PV technology in all the considered sites across South Africa is technically viable.

The quantity of rooftop solar photovoltaic (PV) installations has grown rapidly in the US in recent years. There is a strong interest among decision makers in obtaining high quality information about rooftop PV, such as the locations, power capacity, and energy production of existing rooftop PV installations. Solar PV installations are typically connected directly to local power distribution grids, and therefore it is important for the reliable integration of solar energy to have information at high geospatial resolutions: by county, zip code, or even by neighborhood. Unfortunately, traditional means of obtaining this information, such as surveys and utility interconnection filings, are limited in availability and geospatial resolution. In this work a new approach is investigated where a computer vision algorithm is used to detect rooftop PV installations in high resolution color satellite imagery and aerial photography. It may then be possible to use the identified PV images to estimate power capacity and energy production for each array of panels, yielding a fast, scalable, and inexpensive method to obtain rooftop PV estimates for regions of any size. The aim of this work is to investigate the feasibility of the first step of the proposed approach: detecting rooftop PV in satellite imagery. Towards this goal, a collection of satellite rooftop images is used to develop and evaluate a detection algorithm. The results show excellent detection performance on the testing dataset and that, with further development, the proposed approach may be an effective solution for fast and scalable rooftop PV information collection.

Neighbouring shading effect on photovoltaic panel system: Its implication to green building certification scheme

Photovoltaic (PV) systems are gaining importance in the present electrical distribution systems due to government policies and initiatives, hence the power production cost is also decreasing day by day. This paper focuses on the impacts of rooftop solar PV systems on secondary distribution system, which is rated to 30kW grid tied solar power plant. While studying the impacts of rooftop solar PV system on secondary distribution system, it is necessary to study power quality issues arising due to the integration of rooftop solar PV system and also possible solution to mitigate power quality problems. The study has been done on three different cases, first with the 30kW grid tied solar PV system alone, then 30kw grid tied solar PV system with 5 rooftop PV added to the system, finally 30kw grid tied PV system with 5 rooftop PV system with and without adding hybrid filters to the system and the results are obtained using MATLAB which shows the reduction in harmonics after the addition of hybrid filters to the system. Also, an advanced net metering is modelled in this paper which enforces the consumers to install harmonic filters to bring down the THD within limits, thus the consumer will have to pay penalty charges if the THD value exceeds the permissible levels.

The rooftop photovoltaic (PV) system that uses a power optimization device at the module level (MLPE) has been theoretically proven to have an advantage over other types in case of reducing the effect of partial shading. Unfortunately, there is still a lack of studies about the energy production of such a system in real working conditions with the impact of partial shading conditions (PSC). In this study, we evaluated the electrical energy production of the PV systems which use two typical configurations of power optimization at the PV panel level, a DC optimizer and a microinverter, using their real datasets working under PSC. Firstly, we compared the energy utilization ratio of the monthly energy production of these systems to the reference ones generated from PVWatt software to evaluate the effect of PSC on energy production. Secondly, we conducted a linear decline model to estimate the annual degradation rate of PV systems during a 6-year period to evaluate the effect of PSC on the PV’s degradation rate. In order to perform these evaluations, we utilized a mixed-effects model, a practical approach for studying time series data. The findings showed that the energy utilization ratio of PVs with MLPE was reduced by about 14.7% (95% confidence interval: −27.3% to −2.0%) under PSC, compared to that under nonshading conditions (NSC). Another finding was that the PSC did not significantly impact the PV’s annual energy degradation rate, which was about −50 (Wh/kW) per year. Our finding could therefore be used by homeowners to help make their decision, as a recommendation to select the gained energy production under PSC or the cost of a rooftop PV system using MLPE for their investment. Our finding also suggested that in the area where partial shading rarely happened, the rooftop PV system using a string or centralized inverter configuration was a more appropriate option than MLPE. Finally, our study provides an understanding about the ability of MLPE to reduce the effect of PSC in real working conditions.

With over 8,000 inhabited islands, the distribution of fuels and electricity is extremely challenging in Indonesia. Photovoltaic (PV) energy systems could offer new opportunities and could become increasingly important for the future electricity mix of Indonesia. To stimulate this transition, it is necessary that existing barriers to a successful implementation of PV systems are indicated in order to be tackled. This thesis adds to this goal by enhancing the technical knowledge about PV systems in Indonesia. This has been achieved by modelling and simulation of PV systems. The main research question in this thesis is: What can be learned from experiences with and modelling of PV systems for the stimulation of PV in the future electricity mix in Indonesia? Since the successful implementation of PV systems depends on several factors, PV systems have been evaluated at three different levels: the national, system and product level. At the national level, the potential and costs of PV systems are modelled and assessed. For this purpose, a distinction has been made for grid-connected and off-grid PV systems. For both PV system configurations the potential nominal installed capacity and levelized cost of electricity (LCOE) of PV systems has been determined for each of the provinces of Indonesia. To assess the cost-effectiveness the LCOE has been compared with the generation cost of electricity. At the system level, a pilot grid-tied PV system - which has been installed in Jayapura in the province of Papua during this project - has been analysed. Jayapura regularly suffers from power outages due to aged diesel generators and a weak electricity grid. The performance of the grid-tied PV system in such a weak electricity grid has been evaluated. Subsequently, at the product level, monitoring data from this PV system are used to simulate the power output of the PV system, evaluating the appropriateness of existing models for the determination of the power output under tropical weather conditions. Finally, to increase the accuracy of short-term PV power output simulations, a new PV module temperature model has been proposed.

The objective of this paper is to analyze the performance of the rooftop photovoltaic (PV) system, taking into account its shading impact on the rooftop surface and the eventual cooling load of the building. This paper tests three approaches of the rooftop PV system: zero tilt angle flat PV configuration; PV configuration with a monthly adjusted tilt angle; and PV configuration with a dual-axis sun tracking system. Each of the PV configurations is optimized to do the following: minimize the self-shading among the adjacent arrays; maximize the rooftop surface shading to curtail the cooling load; maximize the net energy yield; and minimize the net levelized cost of energy (LCOE) of the PV system. The existing building model is developed in SketchUp Pro. The model is simulated in an EnergyPlus environment to calculate the building's cooling energy consumption with different shading scenarios in various PV configurations. Various rooftop PV configurations are designed and simulated in a System Advisor Model (SAM) to analyze the effect of self-shading of the adjacent PV arrays on the PV performance. The optimal distance between the arrays (for maximum net energy yield and minimum net LCOE) is found to be 1.5 m. The net LCOE of the optimal scenario is 5.247 ¢/kW h and 4.112 ¢/kW h for monthly tilt and dual-axis tracking arrangements, respectively. The economic surplus of the optimized system is 0.422 ¢/kW h and 0.258 ¢/kW h for the monthly tilt and dual-axis tracking arrangements, respectively, as compared to the ground-mounted system.

Rooftop photovoltaics (PV) systems are attracting residential customers due to their renewable energy contribution to houses and to green cities. However, customers also need a comprehensive understanding of system design configuration and the related energy return from the system in order to support their PV investment. In this study, the rooftop PV systems from many high-volume installed PV systems countries and regions were collected to evaluate the lifetime energy yield of these systems based on machine learning techniques. Then, we obtained an association between the lifetime energy yield and technical configuration details of PV such as rated solar panel power, number of panels, rated inverter power, and number of inverters. Our findings reveal that the variability of PV lifetime energy is partly explained by the difference in PV system configuration. Indeed, our machine learning model can explain approximately 31 % ( 95 % confidence interval: 29–38%) of the variant energy efficiency of the PV system, given the configuration and components of the PV system. Our study has contributed useful knowledge to support the planning and design of a rooftop PV system such as PV financial modeling and PV investment decision.

Since on-grid rooftop photovoltaic (PV) installation is rapidly growing, and the interconnection requests of a new rooftop PV installation are still increasing, the improvement of PV hosting capacity of large-scale rooftop PV penetration needs to be studied. In this paper, the strategy to improve PV hosting capacity using reactive power control of PV inverters is provided. Since the load demand and PV output vary with the time, the results are provided in time-series. Monte Carlo based method is constructed to model the random nature of PV penetration concerning PV size and location. Furthermore, an evaluation study is provided to obtain the appropriate PV power factor setting of which the PV hosting capacities are the highest. Firstly, several possible settings of PV power factor are constructed to conduct an evaluation study of reactive power control scenarios. Secondly, the best setting is chosen concerning the ability for generating the highest PV hosting capacity. In addition, a case study is provided to assess the best setting presented by the evaluation study. The results show that rooftop PV penetration with lagging power factor setting of PV inverters generates higher PV hosting capacity compared to rooftop PV penetration with unity power factor setting, with an improvement rate of 96%.