This study quantifies the economic and environmental impacts associated with the change from a zonal to nodal design in the Texas electricity market. To begin, we present a framework to understand the mechanisms that lead to inefficient outcomes under a zonal market model. Then, we estimate a semiparametric partially linear conditional mean function to quantify changes in selected market metrics for the same set of underlying system conditions after versus before the implementation of the nodal market design. We estimate that daily variable costs of thermal generation given the same level of daily output fell by 3.9% with the implementation of the nodal market design. In contrast, we find that total heat input and CO2 emissions increased with the market design change. We show how changes in operation of coal and natural gas technologies contributed to these outcomes, and find that a large proportion of the daily variable cost savings was due to the synergies achieved through increased efficiency of operation of these two technologies.

Electricity retailing is at a crossroads. Technological change is eroding revenues from the traditional electricity retailing business model. However, many of these new technologies have the potential to create new products and revenue streams for electricity retailers. We assess the future of electricity retailing under two possible approaches by policymakers and regulators to addressing these challenges and new opportunities: a reactive approach and a forward-looking approach.

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.

Small businesses are typically committed to providing a positive customer experience and therefore may exhibit a response to dynamic electricity prices different from residential or industrial customers. We conduct a field experiment to determine the extent to which small businesses respond through re-configuration of typical routines throughout the experiment period versus through adjustments to specific dynamic pricing events. Using a customer-level survey of appliance ownership, we estimate the hourly response patterns of individual appliances to participation in the experiment versus individual dynamic pricing events. Consistent with our re-configuration hypothesis, small businesses primarily curtail electricity usage throughout the experiment period, although we also find a small imprecisely estimated response to dynamic pricing events on top of the re-configuration effect. Appliances not critical to a positive customer experience such as dish dryers, food storage units, lights, electric motors & pumps, and industrial heaters are the major sources of the energy savings from the re-configuration actions of these small businesses.