Solar Photovoltaic Adoption Research Articles

Residential consumers’ experiences in the adoption and use of solar PV

Public policy in many nations is seeking to transition energy generation towards renewable sources such as solar photovoltaic (PV). Reviews of past policy aimed at increasing consumer acceptance of renewable energy sources have identified that policy implementation may not align with policy objectives of energy professionals. The research and analysis of consumers and their interaction with solar PV policy is important in assessing policy outcomes and how these can be better delivered or adapted. This paper reports on an in depth qualitative analysis of 22 persons under different feed-in tariff (FiT) policy settings to explore consumer experiences in acquiring solar PV and their energy use behaviour. The responses of participants indicate there were different motivations and energy use behaviour that were based on the policy in which solar PV was acquired and these may provide insight into policy development or follow up studies.

Comparing energy payback and simple payback period for solar photovoltaic systems

Installing a solar photovoltaic (PV) array is both an environmental and a financial decision. The financial arguments often take priority over the environmental because installing solar is capital-intensive. The Simple Payback period (SPB) is often assessed prior to the adoption of solar PV at a residence or a business. Although it better describes the value of solar PV electricity in terms of sustainability, the Energy Payback period (EPB) is seldom used to gauge the merits of an installation. Using published estimates of embodied energies, EPB was calculated for four solar PV plants utilizing crystalline-Si technology: three being actual commercial installations located in the northeastern U.S., and a fourth installation based on a simulated 20-kilowatt roof-mounted system, in Wroclaw, Poland. Simple Payback was calculated based on initial capital cost, and on the availability of avoided electricity costs based on net-metering tariffs, which at present in the U.S. are 1:1 credit ratio, and in Poland is 1:0.7 credit ratio. For all projects, the EPB time was estimated at between 1.9 and 2.6 years. In contrast, the SPB for installed systems in the northeastern U.S. ranged from 13.3 to 14.6 years, and was estimated at 13.5 years for the example system in Lower Silesia, Poland. The comparison between SPB and EPB shows a disparity between motivational time frames, in which the wait for financial return is considerably longer than the wait for net energy harvest and the start of sustainable power production.

Analysis and model-based predictions of solar PV and battery adoption in Germany: an agent-based approach

In order to tackle energy challenges faced in Germany, a Feed-in Tariff program was created in 2004 to aid the adoption of solar PhotoVoltaic (PV) systems where owners of such systems are paid a certain amount for each unit of electricity generated. Solar PV electricity generation is limited due to its intermittency but this can be managed using batteries. In this paper, we study the adoption of PV and battery (PV-battery) systems in Germany, and evaluate policies that could improve the adoption of these systems and their impact on the electric grid. To do this, we create an agent-based model that is simulated to estimate the impacts of different policies; this model is informed by an online survey with respondents from Germany. Simulating adoption over a period of 10 years, the results show that increasing electricity prices could result in improved PV-battery adoption in Germany better than reducing PV-battery system prices could. In addition, given the high level of affinity of people towards PV systems in Germany, disconnection from the grid would be a viable option within the next 10 years.

Assessment of potential for photovoltaic roof installations by extraction of roof tilt from light detection and ranging data and aggregation to census geography

Large-scale adoption of solar photovoltaics (PV) in the built environment requires automation of roof suitability surveying over large geographical areas. Furthermore, as local PV installation density increases, electricity network operators require clearer information on the overall impact the large number of different rooftop PV systems will have on the stability of the local network. Knowledge of roof features (tilt angle, azimuth angle, area) and localised in-plane irradiance data is essential to meet both of these requirements. Such information is currently not available (except by individual roof surveying by PV consultants) and has to be generated. This paper demonstrates the automated extraction of building roof plane characteristics from existing wide-area, aircraft-based LiDAR (Light Detection and Ranging) data. These characteristics are then aggregated statistically and scaled-up to produce a UK-wide map of average roof tilt variation. Validation of roof tilt with site measurements taken by four different methods demonstrates a mean absolute error of 3 degrees. For major roof plane azimuth angles, banded into compass octants, accurate detection was achieved in 100% of cases, validated by inspection of aerial photography. This is sufficient for calculating in-plane irradiance for a more detailed automated assessment.

Locked post-fossil consumption of urban decentralized solar photovoltaic energy: A case study of an on-grid photovoltaic power supply community in Nanjing, China

Due to enhanced economic production as well as incentivized demanding supply management (DSM) strategies, solar photovoltaics (SPV) have experienced a phenomenal global annual growth rate but with a very limited contribution from the personal consumption sector, especially that of on-grid decentralized SPV. One of the reasons for this lies in the difficulties involved in unlocking the traditional production paradigm and lifestyle, based on centuries of conventional fossil-energy consumption. In response, this paper examines the case of Nine Dream Island in Nanjing, China, a pioneer of post-fossil emerging power supply communities providing on-grid SPV, to reveal the obstacles that lie beyond technological and economic factors involved. Empirical data including in-depth interviews illustrate the politico economic strategies of these communities in creating a new post-fossil production and consumption paradigm. In particular, it is suggested that, despite the National Development and Reform Commission’s economic driving force in the form of 0.42¥/kWh state subsidies in Nanjing, the complex pattern of governance structures and institutional arrangement characteristics overwhelmingly impedes public acceptance of a low-carbon model of production and consumption. Overall, the paper helps to shed light on the development and adoption of SPV as a post-fossil consumption and production technology in new market countries where administration forces provide a more important role in creating a new path-dependence for the adaptation of innovation technologies.

Innovation subsidies versus consumer subsidies: A real options analysis of solar energy

Given the interest in the commercialization of affordable, clean energy technologies, we examine the prospects of solar photovoltaics (PV). We consider the question of how to transition to a meaningful percentage of solar energy in a sustainable manner and which policies are most effective in accelerating adoption. This paper develops a stochastic dynamic model of the adoption of solar PV in the residential and commercial sector under two sources of uncertainty – the price of electricity and cost of solar. The analytic results suggest that a high rate of innovation may delay adoption of a new technology if the consumer has rational price expectations. We simulate the model across alternative rates technological change, electricity prices, subsidies and carbon taxes. It is shown that there will be a displacement of incumbent technologies and a widespread shift towards solar PV in under 30 years – and that this can occur without consumer incentives and carbon pricing. We show that these policies have a modest impact in accelerating adoption, and that they may not be an effective part of climate policy. Instead, results demonstrate that further technological change is the crucial determinant and main driver of adoption. Further, results indicate that subsidies and taxes become increasingly ineffective with higher rates of technological change.

Overcoming barriers and uncertainties in the adoption of residential solar PV

In recent years decreasing hardware costs have driven down the installed price of solar photovoltaic (PV) systems and spurred adoption. However, system cost is not the only barrier faced by solar adopters. Potential adopters also face various informational barriers, leading to high indirect costs during the information search process. There is a significant gap in the literature for empirical work on solar adoption linking how the information context (installer marketing; neighbors with solar, i.e., peer effects; etc.) interacts with a potential adopter's motivations to impact decision outcomes. To address this gap we present results of a new survey on the decision-making process of residential PV adopters in northern California. The main aspects of our analysis include: salient motivating factors, information gathering process, peer effects, role of installers, and factors driving the choice of outright purchase versus third-party ownership (e.g., leasing) modes of adoption. We find that installers and neighbors play important, but often supplementary, roles throughout the decision-making process and have influence on both the decision to adopt as well as on the mode of adoption. Furthermore, expected financial returns and concerns about operations and maintenance are the main determining factors for the mode of adoption.

Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach

Abstract Energy technology adoption is a complex process, involving social, behavioral, and economic factors that impact individual decision-making. This paper uses an empirical, geographic information system (GIS)-integrated agent-based model of residential solar photovoltaic (PV) adoption to explore the importance of using empirical household-level data and of incorporating economic as well as social and behavioral factors on model outcomes. Our goal is to identify features of the model that are most critical to successful prediction of the temporal, spatial, and demographic patterns that characterize the technology adoption process for solar PV. Agent variables, topology, and environment are derived from detailed and comprehensive real-world data between 2004 and 2013 in Austin (Texas, USA). Four variations of the model are developed, each with a different level of complexity and empirical characterization. We find that while an explicit focus only on the financial aspects of the solar PV adoption decision performs well in predicting the rate and scale of adoption, accounting for agent-level attitude and social interactions are critical for predicting spatial and demographic patterns of adoption with high accuracy.

Community Organizations and Active Peer Effects in the Adoption of Residential Solar PV

Solar Community Organizations (SCOs) are formal or informal organizations and citizen groups that help reduce the barriers to the adoption of residential solar photovoltaic (PV) by (1) providing access to credible and transparent information about the localized benefits of residential PV and (2) actively campaigning to encourage adoption within their operational boundaries. We study the peer effect, or social interaction, process catalyzed by SCOs to understand the impact of these organizations on the residential PV market. Using a standardized search methodology across spatial scales (state; city; neighborhoods), we identify and characterize the operations of 228 SCOs formed in the U.S. between 1970 and 2012. We also present case studies of four successful SCOs and find that a common thread of why these SCOs are successful involves effectively leveraging trusted community networks combined with putting together a complete information and financial-tools package for use by interested communities. Finally, our findings suggest that empirical studies that attempt statistical identification and estimation of peer effects should pay close attention to the role of SCOs, as the social interactions engendered by SCOs may be correlated both with the level of social learning as well the socio-demographic characteristics of the communities of interest.