Search

We study default effects in the context of a residential electricity-pricing program. In the large-scale randomized controlled trial we analyse, one treatment group was given the option to opt-in to time-varying pricing while another was defaulted into the program but allowed to opt-out. We provide dramatic evidence of a default effect on program participation, consistent with previous research. A novel feature of our study is that we also observe how the default manipulation impacts customers' subsequent electricity consumption. Passive consumers who did not opt-out but would not have opted in-comprising more than 70% of the sample-nonetheless reduce consumption in response to higher prices. Observing of this follow-on behaviour enables us to assess competing explanations for the default effect. We draw conclusions about the likely welfare effects of defaulting customers onto time-varying pricing.

We propose a novel penalized splines method to estimate a stochastic frontier model in which the frontier is linear and the inefficiency has a single index structure with unknown link function and a linear index. The approach is more flexible than the traditional methodology requiring a parametric link function and, at the same time, it does not incur the curse of dimensionality as a fully non-parametric approach. The procedure can be easily implemented using existing software. We give conditions for the model to be identified and provide some asymptotic results. We also use Monte Carlo simulations to show that the approach works well in finite samples in many situations when compared to the well specified maximum likelihood estimator. An application to the residential energy demand of US states is considered. In this case, the penalized splines approach estimates inefficiency functions that deviate substantially from those resulting from parametric maximum likelihood methods previously implemented. [ABSTRACT FROM AUTHOR]

Little is known about the effect of message framing on conservation behavior over time. In a randomized controlled trial with residential households, we use advanced metering and information technologies to test how different messages about household energy use impact the dynamics of conservation behavior down to the appliance level. Our results, based on 374million panel observations of kilowatt-hour (kWh) electricity consumption for 118 households over 9 months, show that differences in behavioral responses due to message framing become more significant over time. We find that a health-based frame, in which households consider the human health effects of their marginal electricity use, induced persistent energy savings behavior of 8–10% over 100 days; whereas a more traditional cost savings frame, drove sharp attenuation of treatment effects after 2 weeks with no significant savings versus control after 7 weeks. We discuss implications for the design of effective information campaigns to engage households in conservation behavior.

Increasing concerns about sustainability and energy conservation, coupled with the proliferation of incentives in the EU to achieve energy savings, suggest that significant improvements in energy efficiency should be realized. A policy measure that should have a direct impact on energy savings is the replacement of incandescent and halogen light bulbs by more efficient lighting technologies, which was implemented in 2009. Due to the lack of detailed data, it is not feasible to measure the effect of energy-efficient improvements on electricity consumption at the aggregate level using a bottom-up approach. To overcome this limitation, this paper analyzes hourly electricity demand in a very specific period of the day: the transition from day to night. In this short period, it is plausible that lighting is the main driver of changes in electricity demand, thus making it possible to estimate the increase in electricity consumption when lights are switched on and to analyze the effects of higher energy efficiency in lighting, if any. The results of the analysis for Spain show that during the periods 2009–2011 and 2015–2016, an estimated energy savings of 251 GWh can be attributed to a reduction in the magnitude of the lighting effect, which accounts for 20.3% of the observed decrease in electricity consumption during these two periods. [ABSTRACT FROM AUTHOR]

Trading electricity across market zones furthers competitive power prices, security of supply and the integration of renewable energy. In the European Union, flow-based market coupling is the target model to compute correct trading capacities between markets, while approximating physical grid constraints. The methodology relies on predictive, carefully designed parameters to maximize trading opportunities, while keeping congestion management at acceptable levels. This paper explains the fundamentals of flow-based market coupling. It provides an open-access model based on a test network and its data. By providing a guide to the theory and conducting several case studies, the functioning and effects of the most influential parameters are demonstrated. Innovative aspects of this paper are its illustrative nature and its answer to the following research questions: (1) What is the effect of (a) generation shift keys and (b) threshold choice on the selection of critical network elements? (2) What is the effect of (a) generation shift keys, (b) selected critical network elements and (c) security margins on market coupling and congestion management results? It also addresses the effect of higher shares of renewable energy and minimum trading capacities on flow-based market coupling. This analysis shows that (1) the effects of flow reliability margins and selected critical network elements dominate the effect of generation shift keys on flow-based market coupling domains, (2) power systems with an increasing share of renewable energy may necessitate re-adjusted parameters and (3) minimum trading capacities can be guaranteed by redispatch or altering the base case.

Current forecasts suggest that the vast majority of growth in energy demand will come from the developing world, and that China will play a major part in that growth. This paper presents evidence suggesting that the shape of the income distribution, which is typically omitted from forecasting models, plays a major role in driving household acquisition of energy-using durable goods in rural China. We use province-level data for rural households to show that the share of the population living above the poverty line is an important determinant of household appliance holdings even controlling for average household income.

This study finds that a significant and hitherto ignored determinant of home energy demand is ambient particle pollution. I access longitudinal data for Singapore, a newly affluent Asian city-nation and arguably a harbinger of what is to come in the urbanizing tropics. Singapore today combines high (yet unequal) defensive capital stocks, such as residential air conditioning, with widely varying particle pollution. Overall, residential electricity demand grows by 1.1% when PM2.5 rises by 10 µg/m3. I compare the pollution-electricity response to the well-known heat-electricity response, and show how it varies over the socioeconomic distribution. Local pollution control has the cobenefit of reducing electricity generation, via lower household demand, and thus mitigating carbon emissions. The observed inequality in defensive expenditure may also exacerbate health inequalities, as suggested by an exchange between epidemiologists and government. [ABSTRACT FROM AUTHOR]

This paper analyses the interaction between centralised carbon emissive technologies and distributed intermittent non-emissive technologies. In our model, there is a representative consumer who can satisfy her electricity demand by investing in distributed generation (solar panels) and by buying power from a centralised firm at a price the firm sets. Distributed generation is intermittent and induces an externality cost to the consumer. The firm provides non-random electricity generation subject to a carbon tax and to transmission costs. The objective of the consumer is to satisfy her demand while minimising investment costs, payments to the firm and intermittency costs. The objective of the firm is to satisfy the consumer's residual demand while minimising investment costs, demand deviation costs, and maximising the payments from the consumer. We formulate the investment decisions as McKean–Vlasov control problems with stochastic coefficients. We provide explicit, price model-free solutions to the optimal decision problems faced by each player, the solution of the Pareto optimum, and the Stackelberg equilibrium where the firm is the leader. We find that, from the social planner's point of view, the carbon tax or transmission costs are necessary to justify a positive share of distributed capacity in the long-term, whatever the respective investment costs of both technologies are. The Stackelberg equilibrium is far from the Pareto equilibrium and leads to an over-investment in distributed energy and to a much higher price for centralised energy. [ABSTRACT FROM AUTHOR]

I apply and extend a new machine-learning method to estimate heterogeneous electricity demand responses to time-varying prices in an experiment on Irish households. The most important source of heterogeneity is consumer awareness, followed by information provision and baseline consumption. In-home electricity monitors doubled responses. Other household characteristics like demographics, appliance ownership, or house characteristics, were not predictive of heterogeneous effects. Surprisingly, households appeared to violate a central law of demand theory: while they responded to the existence of a price change, they were extremely insensitive to the magnitude of the price change. This suggests that "getting the prices right" is less important than getting consumers to pay attention in the first place. [ABSTRACT FROM AUTHOR]

We analyze the gross welfare gains from real-time retail pricing in electricity markets where carbon taxation induces investment in variable renewable technologies. Applying a stylized numerical electricity market model, we find a U-shaped association between carbon taxation and gross welfare gains. The benefits of introducing real-time pricing can accordingly be relatively low at relatively high carbon taxes and vice versa. The non-monotonous change in welfare gains can be explained by corresponding changes in the inefficiency arising from "under-consumption" during low-price periods rather than by changes in wholesale price volatility. Our results may cast doubt on the efficiency of ongoing roll-outs of advanced meters in many electricity markets, since net benefits might only materialize at relatively high carbon tax levels and renewable supply shares. [ABSTRACT FROM AUTHOR]

Capacity auctions with reliability options are seen as a promising possibility to reduce the investment risk for electricity generators as well as to set incentives for sufficient investments in generating capacity. However, there has been little attention so far on the interaction between a capacity market and an increasing share of renewable energy. In a first step we formalize the functioning of capacity auctions with reliability options. We improve their incentive regulation to allow effective incentives for sufficient investments. In a second step we study, with comparative statics, how an increasing share of renewable energy, varying carbon emission costs and the existing capacity mix influence the outcome of a capacity auction. For an increasing share of renewable energy, capacity auctions direct investments to more flexible power plants. This opposes the merit order effect of renewable energy which is observed at energy-only markets. A capacity market can therefore prevent missing flexibility feared at energy-only markets as a result of an increasing share of renewable energy. [ABSTRACT FROM AUTHOR]

This paper examines the incentives for efficient pricing mechanism in markets with non-convexities. The wholesale electricity market is a prominent example. Ideally, an efficient pricing mechanism produces market signals that reflect costs and scarcities, incents price-taking behavior and yields sufficient revenues to attract new investment. However, under non-convex conditions, there is no assurance that these goals can be fully achieved, and market equilibrium may not even exist. Previous studies on markets with convexities have been focusing on the revenue sufficiency problem. Positive results on incentives are relatively scarce. This paper is intended to fill the gap. With non-convexities, quasi-equilibrium entails solving separately a non-convex allocation model and a convexified pricing model with solution support payments in settlement. We consider three convex relaxation methods, including Lagrangian dualization, convex-hull relaxation and integer relaxation (Integer relaxation refers to a convex relaxation of mixed integer programing problem in which the integer variables are linearized). We show that quasi-equilibrium pricing is dominant strategy incentive compatible in the limit and the total side payment divided by the total surplus approaches zero when the market size (e.g., measured by the number of consumers) increases to infinity. In essence, the quasi-equilibrium pricing mechanism extends efficient pricing principles from a convex market environment to one that is non-convex in ways that preserve economic efficiency, incentive compatibility and revenue sufficiency. These results are illustrated in the context of wholesale electricity markets. Since 2014, price formation issues have been vigorously debated in the U.S. including FERC's conferences and proceedings with comments from academics, policy and business communities across ISO/RTO regions. Convex-hull pricing is generally considered an ideal solution but it remains computationally prohibitive. In this paper, we identify conditions under which the integer relaxation method can produce close and sometimes even exact approximations to convex-hull pricing. In April 2019, FERC authorized the use of integer relaxation as a just and reasonable pricing method for fast-start units in PJM's energy markets. [ABSTRACT FROM AUTHOR]

Coincident peak pricing is used in several electricity markets to recover the embedded cost of infrastructure, such as transmission. In this approach, measured consumption at the time of the peak is used to set charges for that pricing period or a subsequent period. If transmission costs are truly sunk, then such a recovery is unlikely to be efficient. However, in the context of growing peak demand, new additions must be built. We consider the incentive properties of coincident peak pricing when related investments are not considered to be sunk, finding that it can reproduce the incentive properties of an ideal time-varying price. We also consider several variations on this assumption. [ABSTRACT FROM AUTHOR]

We investigate the impact that two German energy reforms—phase-out of nuclear power plants after the Fukushima incident and expansion of renewables due to fixed feed-in tariffs—had on neighbouring countries' consumers. The unilateral German reforms generated substantial negative and positive impacts, respectively, in neighbouring countries with the highest overall effect of German policy found in France, not Germany; an annual negative impact on consumers of €3.15 billion. We also find significant differences in market integration between neighbouring countries by calculating ratios between the estimated policy decisions' impacts before and after controlling for interconnector congestion. [ABSTRACT FROM AUTHOR]

Research from economics and psychology suggests that behavioral interventions can be a powerful climate policy instrument. This paper provides a systematic review of the existing empirical evidence on non-price interventions targeting energy conservation behavior of private households. Specifically, we analyze four nudge-like interventions referred to as social comparison, commitment devices, goal setting, and labeling in 44 international studies comprising 105 treatments. This paper differs from previous systematic reviews by solely focusing on studies that permit the identification of causal effects. We find that all four interventions have the potential to significantly reduce energy consumption of private households, yet effect sizes vary immensely. We conclude by emphasizing the importance of impact evaluations before rolling out behavioral policy interventions at scale. [ABSTRACT FROM AUTHOR]

Economic inefficiency can be caused by time-invariant retail electricity prices because they do not reflect variations in the cost of providing electricity during the day. Time-of-use (TOU) pricing—higher electricity prices during peak hours and lower electricity prices during off-peak hours—is by far the most common way to achieve more efficient levels of electricity consumption through reducing peak demand. The empirical evidence of the effectiveness of TOU pricing is sparse in the commercial and industrial sectors and there is no consensus in the literature on the statistical significance and magnitude of the effects. Applying a quasi-experimental design, this study evaluates an ongoing experiment of voluntary business TOU pricing plan by a major utility company in the Phoenix metropolitan area. Using the nearest-neighbor matching method, we identify control customers for the voluntary participants of the business TOU pricing. From difference-in-differences analysis, we find a statistically significant reduction in peak-hour electricity demand in response to the TOU pricing. We also find that there is no conservation effect, meaning that the total level of electricity consumption does not change under the TOU pricing. [ABSTRACT FROM AUTHOR]

Water withdrawals for the energy sector are the largest use of fresh water in the United States. Using an econometric model of monthly plant-level electricity generation levels between 2001 and 2012, we estimate the effect of water scarcity on the US electricity fuel mix. We find that hydroelectric generation decreases substantially in response to drought, although this baseline generation is offset primarily by natural gas, depending on the geographic region. We provide empirical evidence that drought can increase emissions of CO 2 and local pollutants. We quantify the social costs of water scarcity to be $330,000 per month for each plant that experiences a one-standard deviation increase in water scarcity (2015 dollars), a relationship that persists under future projections of water scarcity. [ABSTRACT FROM AUTHOR]

We evaluate a large-scale field deployment in which close to 7,000 households subject to time-of-using electricity pricing were provided with an in-home display that provides real-time feedback on electricity consumption and price. We find that receipt of the device results in a reduction in average electricity consumption of about 3%, with this effect roughly constant across hours of the day. We find evidence that households respond to this information in part by forming habits rather than adjusting their load-shifting behavior. We also find that real-time information has an ambiguous effect on household responsiveness to electricity prices, counter to existing literature where information increases responsiveness to price. [ABSTRACT FROM AUTHOR]

Currently, about one million households in the United Kingdom (UK) have installed solar photovoltaic (PV) panels with about two-thirds of them are using the panels for self-generating power. According to the UK Department of Energy & Climate Change, solar PV deployment in the UK (measured in megawatt) has grown considerably (from 95 MW in 2010 when the feed-in tariff was introduced to 11,429 MW in 2016). The popularity of the solar PV among the UK households made the government to introduce major changes to the scheme. Our paper focuses on the two major questions: Could it be that the system already favours richer consumers or certain types of network user who do not bear either the efficient or fair share of the total system distribution (and transmission) costs? Does the apportionment of charges between fixed, per kW peak and per kWh use of system charges need to be changed to be more cost reflective? We employ the data from the smart meters readings provided by the Customer-Led Network Revolution monitoring trial conducted with the 199 households in the Northern England that provides the data for the household electricity use and tariff behaviour between October 2012 and July 2014. Our analysis demonstrates that, similar to other studies conducted around the world, the increase in the solar PV resulted in a transfer of wealth and costs between customer groups. Due to their own production, UK solar PV consumers yield a lower share of the per kWh costs of the distribution system which leads to the increase of per unit charges as well as the changes in the distribution of their payment between different types of households. [ABSTRACT FROM AUTHOR]

During the last years, the German energy sector and especially its electricity market was affected by a major energy transition, the so called 'Energiewende'. This transition led to an increase of electricity production from renewable sources and thereby affected the whole electricity market. Therefore, it provides lessons for countries, which are only beginning a similar transition away from fossil fuels to renewable energy sources. The aim of this analysis is to assess if there still exists a relationship between fossil fuel and electricity prices. Due to possible structural breaks in the time series a minimum Lagrange Multiplier (LM) stationarity test is applied, which endogenously determines possible structural breaks. Subsequently a bootstrap approach is used to estimate confidence intervals (C.I.s) for the test statistic and the possible break dates. Furthermore, the stability of the cointegration vector is assessed with the test by Hansen and Johansen (. 'Some Tests for Parameter Constancy in Cointegrated VAR-Models.' The Econometrics Journal 2 (2):306-333.). The results indicate that the cointegration relationship is not stable over time. To incorporate these findings, the cointegration analysis is based on . 'Cointegration Analysis in the Presence of Structural Breaks in the Deterministic Trend.' Econometrics Journal 3 (2):216-249), which allows structural breaks in the deterministic part of the cointegration relation. These results support the assumption that the energy transition affected the relationship between fossil fuels and electricity prices, although there still exists a relatively strong cointegration relation between fossil fuel and electricity prices in the long run. [ABSTRACT FROM AUTHOR]

Optimization of the electricity markets under modern portfolio theory has a crucial role for financial decision makers. Power suppliers in deregulated electricity markets need to optimize their generation capacities and bidding strategies so as to effectively participate in bilateral contract and spot markets. Market players have to deal with continuously changing electricity prices in competitive electricity market environment during their daily routine system operations. Electricity not like the others is a unique product/service and cannot be stored economically, however it should be generated and consumed simultaneously. In addition to all, power suppliers face with fuel price, water regime, delivery, and network risks. In view of the scene described above, prudent decision making methodologies are of critical importance to maximize profit while minimizing managing risks. This paper presents a comprehensive comparison of mean-variance, down-side, and semi-variance methods for optimization in electricity markets and the corresponding methodologies to maximize the return while minimizing risk. Real Turkish day-ahead market data set between December 2009 and December 2012 is used in numerical calculations. Generation cost data of Hydraulic plants, lignite coal fired thermal power plants, and natural gas combined cycle power plants are taken into consideration in the course of optimization evaluations. In the present of real data, these methods can also be applied to renewable energy generation types. These three methods were able to be applied to all case scenarios effectively and produced efficient frontiers, optimal/minimal portfolios, and utility functions successfully. The results have revealed that the methods significantly provide decisions for power suppliers with different risk aversion levels, and for various instruments to maximize the profit while minimizing the associated market risks, and to meet generation obligations. Consequently, financial optimization under Lower Partial Moments constraints would give notable results in analyzing the efficient frontiers for electricity markets in Turkey. [ABSTRACT FROM AUTHOR]

I estimate the level of emissions cost pass-through to hourly wholesale electricity prices in Germany, based on spot market data. I control for contemporaneous shocks to demand and supply by constructing a detailed supply curve for fossil generation and intersecting it with residual demand for fossil-based electricity for every hour. Determining the marginal generator allows me to use marginal fuel and allowance costs (rather than prices) as explanatory variables in order to identify the level of cost pass-through directly and with a high level of precision. I find that allowance costs are passed through to electricity prices completely (or nearly completely) on average, but that the degree of pass-through varies over the load curve. My results suggest that there is no economic reason for free allowance allocation to the German electricity sector, and thus I support the updated allocation rules in phase 3 of the European Union Emissions Trading Scheme. [ABSTRACT FROM AUTHOR]

In Germany, substantial drops in wholesale power prices have become a regular phenomenon. While such price drops have far-reaching implications for the functioning of the power market, their underlying determinants remain poorly understood. To fill this gap, we propose a Markov regime-switching model to investigate low-price events at the European Power Exchange. Our analysis focuses on the role of energy policies that promote renewable energies and have led to significant reductions of nuclear capacities after the Fukushima accident. We find that high electricity infeed from renewable sources increases negative price spike probabilities, while the decommissioning of nuclear plants under the Nuclear Moratorium had an opposing effect. Simulations of market outcomes under different energy policies indicate that reaching ambitious renewable energy targets increases the frequency of low-price events and compromises the financial viability of conventional generation units, while a nuclear phase-out or an increase in storage capacities mitigates these effects. [ABSTRACT FROM AUTHOR]

This paper proposes a model to calculate the magnitude of the reduction in household electricity use that results from a progressive pricing policy, relative to the case where uniform pricing is implemented. To quantify such an effect, a theoretical model is developed for household electricity use, and then it is applied to the progressive pricing policy for electricity in Seoul, South Korea, to empirically derive the magnitude of the reduction in household electricity use. The results suggest that progressive pricing reduces the elasticity in demand for household electricity in the summer. That is, the progressive pricing policy has a curbing effect. Therefore, households would consume a higher amount of electricity in the summer without progressive pricing. [ABSTRACT FROM AUTHOR]

The California Independent System Operator (CAISO) has implemented Convergence Bidding (CB) on February 1, 2011 under Federal Energy Regulatory Commission's September 21, 2006 Market Redesign and Technology Upgrade Order. CB is a financial mechanism that allows market participants, including electricity suppliers, consumers and virtual traders, to arbitrage price differences between the day-ahead (DA) market and the real-time (RT) market without physically consuming or producing energy. In this paper, market efficiency is defined in terms of trading profitability, where a zero-profit competitive equilibrium implies market efficiency (Jensen in, J Financial Econ 6(2):95-101, ). We analyze market data in the CAISO electric power markets, and empirically test for market efficiency by assessing the performance of trading strategies from the perspective of virtual traders. By viewing DA-RT spreads as payoffs from a basket of correlated assets, we can formulate a chance constrained portfolio selection problem, where the chance constraint takes two different forms as a value-at-risk constraint and a conditional value-at-risk constraint, to find the optimal trading strategy. A hidden Markov model (HMM) is further proposed to capture the presence of the time-varying forward premium. This is meant to be a contribution to the modeling of regime shifts in the electricity forward premium with unobservable states. Our backtesting results cast doubt on the efficiency of the CAISO electric power markets, as the trading strategy generates consistent profits after the introduction of CB, even in the presence of transaction costs. Nevertheless, by comparing with the performance before the introduction of CB, we find that the profitability decreases significantly, which enables us to identify the efficiency gain brought about by CB. Convincing evidence for the improvement of market efficiency in the presence of CB is further provided by the test for the Bessembinder and Lemmon (J Finance 57(3):1347-1382, ) model. [ABSTRACT FROM AUTHOR]

This paper investigates the incentives market participants have in the German electricity balancing mechanism. Strategic over and undersupply positions are the result of existing stochastic arbitrage opportunities between the spot market and the balancing mechanism. Clear indications for strategic behavior can be observed in aggregate market data. These structural imbalances increase the need for reserve capacity, raise system security concerns, and therefore place significant costs on consumers. The underlying problem is the disconnect between spot market, reserve capacity market and balancing mechanism. Alternative market design options discussed in this paper suggest better alignment between these markets/mechanisms. [ABSTRACT FROM AUTHOR]