Comparative Analysis of Small and Large Capacity Sized On-grid, Rooftop Solar PV Systems - An LCA Approach

2020 ◽  
pp. 587-597
Author(s):  
N. Leela Prasad ◽  
M. Shreyas ◽  
P. Usha Sri
Keyword(s):  
Comparative Analysis ◽  
Solar Pv ◽  
Large Capacity ◽  
Pv Systems ◽  
Rooftop Solar

Grid Parity of Residential Building Rooftop Solar PV in India

2021 ◽  
pp. 19-40
Author(s):  
Rakesh Dalal ◽  
Kamal Bansal ◽  
Sapan Thapar
Keyword(s):  
Residential Building ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Indian Government ◽  
Pv System ◽  
Pv Systems ◽  
Grid Parity ◽  
Solar Pv System ◽  
Utility Grid ◽  
Rooftop Solar

Rooftop solar photovoltaic(PV) installation in India have increased in last decade because of the flat 40 percent subsidy extended for rooftop solar PV systems (3 kWp and below) by the Indian government under the solar rooftop scheme. From the residential building owner's perspective, solar PV is competitive when it can produce electricity at a cost less than or equal grid electricity price, a condition referred as “grid parity”. For assessing grid parity of 3 kWp and 2 kWp residential solar PV system, 15 states capital and 19 major cities were considered  for the RET screen simulation by using solar isolation, utility grid tariff, system cost and other economic parameters. 3 kWp and 2 kWp rooftop solar PV with and without subsidy scenarios were considered for simulation using RETscreen software. We estimate that without subsidy no state could achieve grid parity for 2kWp rooftop solar PV plant. However with 3 kWp rooftop solar PV plant only 5 states could achieve grid parity without subsidy and with government subsidy number of states increased to 7, yet wide spread parity for residential rooftop solar PV is still not achieved. We find that high installation costs, subsidized utility grid supply to low energy consumer and financing rates are major barriers to grid parity.

scholarly journals The Upper Limit of Distributed Solar PV Capacity in Riyadh: A GIS-Assisted Study

2019 ◽  
Vol 11 (16) ◽  
pp. 4301
Author(s):  
Elshurafa ◽  
Muhsen
Keyword(s):  
Energy Requirement ◽  
Peak Load ◽  
Shopping Mall ◽  
Financial Policy ◽  
Solar Pv ◽  
Solar Systems ◽  
Pv Systems ◽  
Upper Limit ◽  
The City ◽  
Rooftop Solar

Rooftop solar photovoltaic (PV) systems, commonly referred to as distributed generation (DG) solar systems, are deemed important contenders in future sustainable cities. Because deploying DG systems is associated with technical, financial, policy, and market implications that impact utilities, governments, and businesses, quantifying the potential of DG systems that could be deployed in a certain jurisdiction ex ante helps inform the decision-making process for all stakeholders. To that end, the upper limit of rooftop PV systems that could be deployed in Riyadh, the capital of Saudi Arabia, was assessed with the aid of geographic information systems (GIS). By relying on urban land lot data for different categories, i.e., zones, and the maximum allowable area that could be built within a certain lot using prevailing building codes and regulations, the rooftop area suitable for PV deployment within Riyadh Metro was quantified. The analysis was restricted to rooftops in residential, mosque, shopping mall, and health care buildings only. Following the quantification of the rooftop area, the upper limit of rooftop solar PV capacity that can be deployed in the city of Riyadh was found to be 4.34 GW. This capacity represents nearly 22% of the peak load and can satisfy approximately 9% of the energy requirement in the central region, the region in which Riyadh resides.

scholarly journals Analyzing the impact of dust accumulation and different cleaning mechanism on efficiency of solar photovoltaic panel

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Atul Kumar1 ◽  
Srivastava Manish2
Keyword(s):  
Renewable Energy Sources ◽  
Dust Particles ◽  
Energy Sources ◽  
Pollution Level ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Photovoltaic Panel ◽  
Pv Systems ◽  
The Impact ◽  
Rooftop Solar

Electricity generation around the world is mainly produced by using non-renewable energy sources especially in the commercial buildings. However, Rooftop solar Photovoltaic (PV) system produced a significant impact on environmental and economical benefits in comparison to the conventional energy sources, thus contributing to sustainable development. Such PV’s system encourages the production of electricity without greenhouse gas emissions that leads to a clean alternative to fossil fuels and economic prosperity even in less developed areas. However, efficiency of rooftop solar PV systems depends on many factors, the dominant being geographical (latitude, longitude, and solar intensity), environmental (temperature, wind, humidity, pollution, dust, rain, etc.) and the type of PV (from raw material extraction and procurement, to manufacturing, disposal, and/or recycling) used. During the feasibility analysis of the environment, geographical conditions are keep in well consideration, but the pollution level of the city is always overlooked, which significantly influences the performance of the PV installations.           Therefore, this research work focused on the performance of rooftop solar PV installed in one of the most polluted city in India. Here, the loss in power generation of rooftop solar PV has been studied for the effect of deposited dust particles, wind velocity before and after the cleaning of the panels. The actual data has been utilized for the calculation of the energy efficiency and power output of the PV systems. According to the results, it has been concluded that dust deposition, wind speed and pollution level in city significantly reduces the efficiency of solar photovoltaic panel. Hence, an overview of social and environmental impacts of PV technologies is presented in this paper along with potential benefits and pitfalls.

Characteristic profile

2021 ◽  
Vol 1 (1) ◽  
pp. 95-106
Author(s):  
Julian De Hoog ◽  
Maneesha Perera ◽  
Peter Ilfrich ◽  
Saman Halgamuge
Keyword(s):  
Forecast Error ◽  
Forecast Accuracy ◽  
Distribution Networks ◽  
Energy Markets ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Short Term ◽  
Pv Systems ◽  
Resolution Dataset ◽  
Rooftop Solar

The rapid uptake of rooftop solar photovoltaic systems is introducing many challenges in the management of distribution networks, energy markets, and energy storage systems. Many of these problems can be alleviated with accurate short term solar power forecasts. However, forecasting the power output of distributed rooftop solar PV systems can be challenging, since many complex local factors can affect solar output. A common approach when forecasting such systems is to extract the daily seasonality from the time series using some form of seasonality model, and then forecast only the residuals that remain after seasonality extraction. In this work, we explore in detail the effectiveness of three commonly used seasonality models, and we propose a new one, called the "characteristic profile". We find that when seasonality models are integrated into the forecasting process, significant gains in forecast accuracy may be obtained - particularly for machine learning based approaches, which have a reduction in forecast error of 5-25%. Among the seasonality models, the characteristic profile demonstrates the highest forecast accuracy, resulting in reductions in forecast error of 8% or more compared to forecasting models that do not take seasonality into account. The benefits of this approach are particularly pronounced when forecasting solar PV systems that are curtailed, suffer from local shading, or consist of multiple sets of panels having different orientations and tilts. Our results are demonstrated on a high resolution dataset obtained from 258 sites in Western Australia over the course of a full year.

Modelling the time duration until the adoption of residential rooftop solar photovoltaic (PV) systems

2021 ◽  
pp. 1-32
Author(s):  
Mohammad Hamed ◽  
Adnan AlMasri ◽  
Zakariya Dalala ◽  
Raed Alsaleh
Keyword(s):  
Mixed Logit ◽  
Significant Proportion ◽  
Economic Benefits ◽  
Solar Pv ◽  
Pv System ◽  
Time Duration ◽  
Pv Systems ◽  
Intention To Adopt ◽  
Solar Pv System ◽  
Rooftop Solar

Abstract This paper addresses two key decisions by households to adopt rooftop solar PV systems and the length of time until the adoption. It is hypothesized that these decisions are controlled by different mechanisms and should be modelled independently. This is the first attempt to formally estimate the length of time until the adoption to the authors' knowledge. Two models are presented in this paper. The first is a mixed logit to model the respondents' intention to adopt a solar PV system, and the second is a random parameters ordered probit to estimate the length of time until the adoption. Estimation results show that the number of electrical appliances, the households' interest to harness economic benefits, and the type and characteristics of the dwelling motivate households to select a shorter duration until the adoption. Results also show that the majority (77.80%) of respondents with EVs are highly likely to adopt a rooftop system and select a shorter time duration until adoption. In addition, a significant proportion (83.23%) of respondents with high monthly electricity bills are more likely to adopt a rooftop PV system and select a shorter time duration. Results show that the average monthly electricity bill for households with a PV system has decreased by 74.04%. Reducing monthly electricity bills is a key instigator for adopting a rooftop PV system. Our results confirm the hypothesis that even if there is an intent to adopt a rooftop solar PV system, the length of time until the adoption is controlled by another mechanism.

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