The economic incentive to install a solar photovoltaics ('PV') system depends increasingly on using PV generation on-site ('self-consumption') rather than receiving payments from generating solar energy and exporting it to the grid. There is, however, remarkably little empirical evidence on self-consumption. This paper begins to address this gap by analysing one-minute electricity monitoring data for 302 households that participated in a UK smart grid demonstration project. We calculate annual self-consumption levels and find that they are 855 kWh/year per household on average, or 45% of PV generation. We conduct a simple regression analysis to estimate self-consumption and use the results to show that self-consumption for an average UK household with electricity demand of 4000 kWh/year and 2.9 kWp PV system would be 966 ± 38 kWh/year, equivalent to a 24% reduction in average annual electricity demand from the grid. Our methodology can be readily applied to measure and predict self-consumption in other solar markets as well, which has increasingly important implications for valuing solar investments, setting feed-in tariffs, and examining the impacts of PV on networks and retail sales.

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The market for residential solar photovoltaic (PV) systems in the United States has experienced tremendous growth over the past decade, with installed capacity more than doubling between 2014 and 2016. The residential PV market's continued growth prompts new questions about the nature of competition between solar installers and how this competition, or lack thereof, affects the prices consumers pay. It is often assumed that more competition leads to lower prices, but this is not universally true. For example, some studies have shown that factors such as brand loyalty could lead to a negative relationship between concentration and price in imperfectly competitive markets (Borenstein 1985;Holmes 1989). As such, the relationship between prices and market concentration is an open empirical question because theory could predict either a positive or negative relationship.In this paper, we study the relationship between solar PV TPO prices and market (installer) concentration (i.e., market competitiveness). To do this, we build a novel dataset of TPO contract terms for the residential solar PV market in the San Diego Gas & Electric service territory. This allows us to construct the net present cost (NPC) of each system based upon the leasing terms. We combine numerous public and proprietary datasets that allowed us to match solar PV system-level data to TPO contract prices and to construct eight different variables that measure market structure.Determining a relationship between prices and installer concentration is challenging for several reasons. Most significantly, prices and market structure are simultaneously determined by each other-the amount of competition a seller faces influences the price they can command, while prices determine a seller's market share. Previous studies have examined recent solar PV pricing trends over time and between markets Nemet et al., 2016, Gillingham et al., 2014Barbose and Darghouth, 2015;. While these studies of solar PV pricing are able to determine correlations between prices and market factors, they have not proven causation. Our study aims to fill that gap by focusing on identifying the causal relationship between market structure and prices paid by consumers.We contribute to the growing literature on solar markets by addressing two key missing pieces. First, we study TPO system pricing as measured by the contract terms agreed upon between the consumer and the third party. This is different from studying the host-owned (HO) market in which the residential customers own the solar system. In the case of TPO, a third-party owns the solar system and leases it to the residential customer, resulting in a different pricing structure and business model. Other studies to date have focused on the HO market because of data limitations. Our access to and evaluation of proprietary contracts obtained through a non-disclosure agreement allows us to overcome the barrier of TPO pricing data availability.Second, while previous studies reveal interesting insights about the correlations between mark...

Human innovations have created widespread human prosperity. However, they are also threatening the global environmental systems on which our economy and civilisation depend. The likely solutions to these challenges-such as the transition to clean energy systems-will require yet more innovation. This article presents five policy proposals that would support more innovation of the environmentally beneficial kind and less innovation of the environmentally harmful kind. We argue that the appropriate portfolio of innovation policies for protecting global environmental systems includes: 1) pricing natural capital; 2) providing and targeting R&D support towards environmentally-beneficial innovations, based on the evidence acquired through more rigorous experimental designs; 3) providing earlystage deployment subsidies for environmentally-friendly technologies in particular circumstances; 4) supporting collaborative R&D to leverage complementary capabilities in various types of organisations; and 5) reducing barriers to private-sector environmental finance. Policies in these five areas could help redirect innovation towards environmentallyfriendly economic activities.

We formalize pass-through over-shifting as a simple yet under-utilized test for market power. We apply this test in the market for solar energy. Specifically, we estimate the pass-through of solar subsidies to solar system prices using rich micro-level transaction and subsidy data from California. Buyers of solar systems capture nearly the full subsidy, while there is more-thancomplete pass-through to lessees. We conclude that solar markets are imperfectly competitive by ruling out alternative explanations for over-shifting, and reinforce this conclusion with a test of solar demand curvature. This procedure can serve to detect market power beyond the solar market.

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One energy policy objective in the United States is to promote the adoption of technologies that provide consumers with stable, secure, and clean energy. Recent work provides anecdotal evidence of natural gas (NG) and renewable electricity (RE) synergies in the power sector, however few studies quantify the value of investing in NG and RE systems together as complements. This paper uses discounted cash flow analysis and real options analysis to value hybrid NG-RE systems in distributed applications, focusing on residential and commercial projects assumed to be located in the states of New York and Texas. Technology performance and operational risk profiles are modeled at the hourly level to capture variable RE output and NG prices are modeled stochastically as geometric Ornstein-Uhlenbeck (OU) stochastic processes to capture NG price uncertainty. The findings consistently suggest that NG-RE hybrid distributed systems are more favorable investments in the applications studied relative to their single-technology alternatives when incentives for renewables are available. In some cases, NG-only systems are the favorable investments. Understanding the value of investing in NG-RE hybrid systems provides insights into one avenue towards reducing greenhouse gas emissions, given the important role of NG and RE in the power sector.