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[en] This article analyzes the financial impact of distributed energy resources (DERs) owned and operated by commercial customers on the load serving entities (LSEs). DERs reduce the customers' electricity bills and hence the revenues collected by their LSE. However, changes in customer demand profiles can potentially reduce the aggregated system demand profile, and therefore, reduce the LSE's costs in wholesale markets. Analysis of these financial impacts indicates that the LSE's lost revenue ultimately outweighs its reduced expenses. This is largely due to a significant reduction in revenue from demand charges. Dispatchable DERs, including energy storages and demand response, result in more financial losses for LSEs than photovoltaics. The financial losses LSEs face indicate that redesigning commercial customer tariffs is necessary in order for LSEs to accommodate customer owned DERs properly. Several suggestions on modifying commercial tariffs are presented. - Highlights: • We analyze the financial impacts on load serving entities of DERs owned by commercial customers. • Under the selected commercial tariff, load serving entities suffer economic losses. • Energy storages and demand response results in more financial losses for LSE than photovoltaics. • We provide some suggestions for tariff modifications.
[en] This paper first proposes a modeling framework to study diffusion of innovations which exhibit strong interaction with the institution systems across which they diffuse. A unique character of such generic innovation is that specific applications are continually developed during its diffusion. This self-propagation in continual applications generation, which is dependent upon the cumulative installed base of the technological innovation, can be modeled to lead to a dynamic changing carrying capacity in an otherwise simple logistic diffusion curve. The cumulative installed base is dependent upon the price of technology and the cost learning dynamics. This paper utilizes a multi-factors learning function to represent such learning dynamics. Empirical estimates from our model are compared with those from other logistics curve formulations and are shown to better fit the annual PV production data during the past quarter century in the case of Japan. The very fact that the potential of this class of innovation can be leveraged only if it interacts closely with the institution highlights the importance of institutional determinants of adoption and diffusion of such innovations like PV. We therefore attempt to put forward an institutional framework, based on viewing PV as a technology platform, to consider PV diffusion beyond mathematical and empirical modeling. Some future research directions are also proposed. (author)
[en] The last twenty years have seen the growth of both solar PV manufacturing capacity and deployment in China, yet this growth has followed a very erratic path. This study applies the concept of socio-technical regime to identify factors which have made this path so erratic. We examine four stages in China's solar PV policy from mid-1990s to 2013 and show that each is characterized by different combinations of policy program. These changes in government policy and in the resultant trajectory of the solar PV sector are attributed to three main sets of variables. The most important of these are events which shape the wider policy priorities of China's government. Secondary factors include the government's poor management of the policy interaction between the domestic solar PV manufacturing industry and the deployment of solar PV across the country, as well as policy learning within government. The general lesson from this study is that the development path of a single element of a national strategy for the low-carbon transition is likely to be erratic, subject as it is to a range of political and economic forces, and to experimentation and learning. - Highlights: • The concept of the socio-technical regime is applied to the study. • Four stages of China's solar PV policy are examined. • Factors causing policy shifts in policy priorities and policy instruments are identified • The erratic path of China's solar PV policy is explained. • China's latest solar PV policies during 2013 are highlighted
[en] Due to Taiwan's limited energy resources, the development of solar photovoltaic (PV) in Taiwan has become one of the most important solutions for meeting future energy supply needs and ensuring environmental protection. A huge amount of researches about renewable energy sources has emerged recently in response to these issues. However, the amount of researches considering the effects of various influential parameters on the efficiency and performance of PV systems remains small, and is still limited to some specific parts of PV systems. In particular, researches considering thoughtfully the influence of government subsidies on PV financial assessment are still in development. This paper proposes an approach to analyze the benefit of installing a PV system under the impact of government financial subsidies, focusing especially on feed-in-tariff (FIT) and tax abatement policies for industrial users in Taiwan. In addition, a method for selecting the most appropriate policies is proposed for the government through the analysis of both user demand and the government's PV installation capacity target. - Highlights: • Analyzing the benefit of installing a PV system impacted by the government subsidy. • Analyzing the role of policy in the financial model of PV system. • Estimating the performance of PV system under the real weather condition. • Methods to select the policies which satisfy demands of both government and users. • Methods to select the policies which ensure cost-effectiveness of government's support.
[en] Liberalisation and the ever larger share of variable renewable energies (VRES), e.g. photovoltaic (PV) and wind energy, affect security of supply (SoS). We develop a system dynamics model to analyse the impact of VRES on the investment decision process and to understand how SoS is affected. We focus on the Swiss electricity market, which is currently undergoing a liberalisation process, and simultaneously faces the encouragement of VRES and a nuclear phase out. Our results show that nuclear production is replaced mainly by PV and imports; the country becomes a net importer. This evolution points to a problem of capacity adequacy. The resulting price rise, together with the subsidies needed to support VRES, lead to a rise in tariffs. In the presence of a high share of hydro, the de-rated margin may give a misleading picture of the capacity adequacy. We thus propose a new metric, the annual energy margin, which considers the energy available from all sources, while acknowledging that hydro-storage can function as a battery. This measure shows a much less reassuring picture of the country’s capacity adequacy. - Highlights: •We model the long-term dynamics of the Swiss electricity market. •Nuclear power is expected to be partially replaced by PV and imports. •These changes in the energy mix and exchange patterns cause prices to rise. •Import dependency and price rise are symptoms of a decreasing capacity adequacy. •The annual energy margin shows a less reassuring picture than the de-rated margin.
[en] Aim: Policy-makers typically track the rapidly evolving U.S. residential photovoltaic (PV) market by relying on price data reported by PV installers/integrators to incentive programs. Recent years have witnessed a shift toward third-party-owned (TPO) business models, in which the absence of a cash purchase price obscures data interpretation. Appraisals—often based on estimates of the average fair market value across a diverse fleet of systems—are one way TPO prices are reported. Scope: This study investigates residential PV system price drivers to improve the accuracy, consistency, and relevance of PV price-tracking efforts. Our econometric approach evaluates system price drivers using California Solar Initiative data, controlling for system, installer, and geographic variables. Conclusions: We find that reported prices for confirmed appraised systems are $1.13/W higher than non-appraised systems and do not respond to hypothesized price drivers. For non-appraised systems, we find preliminary evidence of market distortions based on the impact of the incentive level, module cost and household income on reported price. Further, unspecified installer heterogeneity—possibly due to differences in products, cost structure or reporting practices—is a substantial price driver. Using estimates, we develop a price model to approximate non-appraised system prices. -- Highlights: •This analysis evaluates residential PV price drivers using an econometric model. •Reported prices for appraised systems are $1.13/W higher than non-appraised. •Reported prices for appraised systems do not respond to expected price drivers. •We find some evidence of market distortions in non-appraised systems. •Installer heterogeneity is a substantial price driver for all systems
[en] Solar resource estimation risk is one of the main solar PV project risks that influences lender’s decision in providing financing and in determining the cost of capital. More recently, a number of measures have emerged to mitigate this risk. The study focuses on solar industry’s best practice energy resource estimation and assesses its financing implications to the 27 MWp solar PV project study in Brunei Darussalam. The best practice in resource estimation uses multiple data sources through the measure-correlate-predict (MCP) technique as compared with the standard practice that rely solely on modelled data source. The best practice case generates resource data with lower uncertainty and yields superior high-confidence energy production estimate than the standard practice case. Using project financial parameters in Brunei Darussalam for project financing and adopting the international debt-service coverage ratio (DSCR) benchmark rates, the best practice case yields DSCRs that surpass the target rates while those of standard practice case stay below the reference rates. The best practice case could also accommodate higher debt share and have lower levelized cost of electricity (LCOE) while the standard practice case would require a lower debt share but having a higher LCOE. - Highlights: •Best practice solar energy resource estimation uses multiple datasets. •Multiple datasets are combined through measure-correlate-predict technique. •Correlated data have lower uncertainty and yields superior high-confidence energy production. •Best practice case yields debt-service coverage ratios (DSCRs) that surpass the benchmark rates. •Best practice case accommodates high debt share and have low levelized cost of electricity.
[en] This paper compares the potential contribution of solar electric power in the form of photovoltaics to meet future US energy demand with the projected volume of oil estimated to be available in the Arctic National Wildlife Refuge. Such a comparison has practical value since it directly addresses a key policy choice under consideration in the new century, namely, that between one of the most promising untapped oil deposits in the world and one of the most rapidly growing renewable energy options
[en] The Chinese government initiated the Feed-In Tariff (“FIT”) policy for downstream power generation in August 2013. The effectiveness of the downstream FIT policy has attracted the attention of academia and government. Using the quarterly data of listed solar PV companies between 2009 and 2015, this paper provides an empirical analysis regarding the effects of the downstream FIT policy. We find that (1) the FIT policy has significantly enhanced the inventory turnover of listed PV firms and improved their profitability; (2) the FIT policy has significant effects on the inventory turnover of midstream companies and mixed industry-chain companies mainly engaged in downstream operations; (3) FIT policy is more favorable towards increasing the inventory turnover of private enterprises. Our results indicate that the FIT policy can have substantial effects on the sustainable development of China's solar photovoltaic industry. - Highlights: •The article focuses on the analysis of the effect of downstream FIT policy. •We test how FIT policy affects overcapacity and profitability of solar PV companies. •We find FIT policy significantly solved the overcapacity of China’s solar PV industry. •We find FIT policy improved profitability of listed solar PV companies. •FIT policy can’t be played alone and should be combined with taxation and R&D policy.
[en] With “soft” costs accounting for well over 50% of the installed price of residential photovoltaic (PV) systems in the United States, this study evaluates the effect of city-level permitting processes on the installed price of residential PV systems and on the time required to develop those systems. The study uses a unique dataset from the U.S. Department of Energy's Rooftop Solar Challenge Program, which includes city-level permitting process “scores,” plus data from the California Solar Initiative and the U.S. Census. Econometric methods are used to quantify the price and development-time effects of city-level permitting processes on more than 3000 PV installations across 44 California cities in 2011. Results suggest that cities with the most favorable permitting practices can reduce average residential PV prices by $0.27–$0.77/W (4–12% of median PV prices in California) compared with cities with the most onerous permitting practices, depending on the regression model used. Though the empirical models for development times are less robust, results suggest that the most streamlined permitting practices may shorten development times by around 24 days on average (25% of the median development time). These findings illustrate the potential price and development-time benefits of streamlining local permitting procedures for PV systems. - Highlights: • The study uses a unique dataset from the U.S. DOE's Rooftop Solar Challenge Program. • We quantify the price and development-time effects of city-level permitting processes. • Most favorable permitting practices can reduce average residential PV prices by $0.27–$0.77/W