The basic features of an efficient short-term wholesale market design do not need to change to accommodate a significantly larger share of zero marginal cost intermittent renewable energy from wind and solar resources. A large share of controllable zero marginal cost generation does not create any additional market design challenge relative to a market with a large share of controllable positive marginal cost generation. In both instances, generation unit owners must recover their fixed costs from sales of energy, ancillary services, and long-term resource adequacy products.

We show that the negative demand shock due to the COVID-19 lock-down has reduced net-demand system demand less the amount of energy produced by intermittent renewables and net imports that must be served by controllable generation units. Introducing additional intermittent renewable generation capacity will also reduce the net-demand, which implies the lock-down can provide insights about how electricity markets will perform with a large share of renewable generation capacity. We find that the lock-down induced demand shock in the Italian electricity market has reduced day-ahead market prices by 23 EUR/MWh (-45%) but re-dispatch cost have increased by 9 EUR/MWh (+103%) per MWh of load, both relative to the average to the same magnitude for the same time period in previous years. Relating the actual re-dispatch cost to a non-COVID-19 re-dispatch cost counter-factual derived from a deep-learning model estimated using pre-COVID-19 data yields an increase of 40%. We argue that the difference between these two re-dispatch cost increases can be attributed to the increased opportunities for suppliers with controllable units to exercise market power in the re-dispatch market in these low net-demand conditions. These results imply that an increased intermittent renewable energy share is likely to increase significantly the costs of maintaining a reliable grid because of the low levels of net-demand.

The variability of solar and wind generation increases transmission network operating costs associated with maintaining system stability. These ancillary services costs are likely to increase as a share of total energy costs in regions with ambitious renewable energy targets. We examine how ecient deployment of intermittent renewable generation capacity across locations depends on the costs of balancing real-time system demand and supply. We then show how locational marginal network taris can be designed to implement the ecient outcome for intermittent renewable generation unit location decisions. We demonstrate the practical applicability of this approach by applying our theory to obtain quantitative results for the California electricity market.

Hourly plant-level wind and solar generation output and real-time price data for one year from the California ISO control area is used to estimate the vector of means and the contemporaneous covariance matrix of hourly output and revenues across all wind and solar locations in the state. Annual hourly output and annual hourly revenues mean/standard deviation efficient frontiers for wind and solar resource locations are computed from this information. For both efficient frontiers, economically meaningful differences between portfolios on the efficient frontier and the actual wind and solar generation capacity mix are found. The relative difference is significantly larger for aggregate hourly output relative to aggregate hourly revenues, consistent with expected profit-maximizing unilateral entry decisions by renewable resource owners. Most of the hourly output and hourly revenue risk-reducing benefits from the optimal choice of locational generation capacities is captured by a small number of wind resource locations, with the addition of a small number of solar resource locations only slightly increasing the set of feasible portfolio mean and standard deviation combinations. Measures of non-diversifiable wind and solar energy and revenue risk are computed using the actual market portfolio and the risk-adjusted expected hourly output or hourly revenue maximizing portfolios.

Electricity tariff reforms will be an essential part of the clean energy transition. Existing tariffs rely on average cost pricing and often set a price per unit that exceeds marginal cost. The higher price encourages over-adoption of residential solar panels and under-adoption of electric alternatives to fossil fuels. However, an efficient tariff based on fixed charges and marginal cost pricing may harm low-income households. We propose an alternative methodology for setting fixed charges based on the predicted willingness-to-pay of each household. Using household data from Colombia, we show the fiscal burden and economic inefficiency of the existing tariffs. We then show how our new tariff methodology could improve economic efficiency and create incentives for the adoption of clean energy technologies, while still leaving low-income households better off.

Charging full requirements customers for distribution network services using the traditional cents per kilowatt-hour (KWh) price creates economic incentives for consumers to invest in distributed generation technologies, such as rooftop solar photovoltaics, despite the fact that marginal cost of grid-supplied electricity is lower. This paper first assesses the economic efficiency properties of this approach to transmission and distribution network pricing and whether current approach to distribution network pricing implies that full-requirement customers cross-subsidize distributed solar customers. Using data on quarterly residential distribution network prices and distributed solar installations from California’s three largest investor-owned utilities I find that larger amounts of distributed solar capacity and more geographically concentrated solar capacity predict higher distribution network prices and average distribution network costs. This result continues to hold even after controlling for average distribution network costs for the utility, Using these econometric model estimates, I find that 2/3 of the increase in residential distribution network prices for each of the three utilities between 2003 and 2016 can attributed to the growth distributed solar capacity. The paper then investigates the extent of the legal obligation that distributed solar generation customers have to pay for sunk costs of investments in the transmission and distribution networks. The paper closes with a description of an alternative approach to distribution network pricing that is likely to increase the economic signals for efficient electricity consumption and the incentive for cost effective installation of distributed solar generation capacity.

We report results from a large field experiment that with a few hours prior notice provided Danish residential consumers with dynamic price and environmental signals aimed at causing them to shift their consumption either into or away from certain hours of the day. The same marginal price signal is found to cause substantially larger consumption shifts into target hours compared to consumption shifts away from target hours. Consumption is also reduced in the hours of the day before and after these into target hours and there is weaker evidence of increased consumption in the hours surrounding away target hours. The same into versus away results hold for the environmental signals, although the absolute size of the eects are smaller. Using detailed household-level demographic information for all customers invited to participate in the experiment, both models are re-estimated accounting for this decision. For both the price and environmental treatments, the same qualitative results are obtained, but with uniformly smaller quantitative magnitudes. These selection-corrected estimates are used to perform a counterfactual experiment where all of the retailer’s residential customers are assumed to face these dynamic price signals. We find substantial wholesale energy cost savings for the retailer from declaring into events designed to shift consumption from high demand periods to low demand perio ds within the day, which suggests that such a pricing strategy could significantly reduce the cost of increasing the share of greenhouse gas free wind and solar electricity production in an electricity supply industry.

Using hourly offer curves for the Italian day-ahead market and the real-time re-dispatch market for the period January 1, 2017 to December 31, 2018, we show how thermal generation unit owners attempt to profit from differences between a simplified day- ahead market design that ignores system security constraints as well as generation unit operating constraints, and real-time system operation where these constraints must be respected. We find that thermal generation unit owners increase or decrease their day- ahead offer price depending on the probability that their final output will be increased or decreased because of real-time operating constraints. We estimate generation unit- level models of the probability of each of these outcomes conditional on forecast demand and renewable production in Italy and neighbouring countries. Our most conservative estimate implies an offer price increase of 50 EUR/MWh if the predicted probability of day-ahead market schedule increases from zero to one. If the predicted probability of a day-ahead market schedule increases from zero to one the unit owner’s offer price is predicted to be 60 EUR/MWh less. We find that these re-dispatch costs averaged approximately nine percent of the cost of wholesale energy consumed valued at the day-ahead price during our sample period.