Is a Wetter Grid a Greener Grid? Estimating Emissions Offsets for Wind and Solar Power in the Presence of Large Hydroelectric Capacity.

• Author: Castro, Miguel
• Position: Report - Statistical table

1. INTRODUCTION

   In order to achieve carbon dioxide and local pollutants abatement goals, an electric grid powered by a significant share of renewable energy is one of the proposed alternatives (Cardell and Anderson, 2015). Nevertheless, the intermittent nature of solar and wind power and the nascent utility scale electricity storage make it challenging to assess the emissions offsets of these power sources. Overcoming these methodological difficulties is necessary to estimate the economic value of renewable energy and to evaluate related policies such as feed-in tariffs, renewable portfolio standards and subsidies.

   In this paper, using historical data on the randomness of hourly solar and wind generation from 2013 to 2015, I estimate how much C[O.sub.2], S[O.sub.2] and NOx these sources abate in the electric grid in California, a worldwide leader in renewable energy adoption. The novel challenge lies in identifying the marginal generation and emissions offsets caused by adding two intermittent sources to a grid that has a significant share of hydropower. Previous literature, centered on grids with small fractions of hydro generation, has identified emissions offsets related to the instantaneous displacement of the highest marginal cost fossil generators by zero marginal cost renewables through the merit order effect (Kaffine et al., 2012; Cullen, 2013; and Novan, 2015). (1)

   Nevertheless, daily solar and wind power cycles introduce dynamics that reallocate hydro-power, alter fossil generation and emissions. Responding to arbitrage incentives, incoming wind and solar generation cause hydro to shift to those hours with the lowest increase in renewable output. Hydro reservoirs play the role of facilitating the intertemporal allocation. Capturing this dynamic effect on emissions offsets and on the value of wind and solar requires modelling not only the contemporaneous or static effect but the overall dynamic effect.

   Using a time series regression, I model the static displacement of the highest marginal cost fossil generators and the existence of hydropower reallocation. The results show that, on average, each additional MWh of solar generation instantaneously displaces 0.565 MWh of fossil generation and reallocates 0.129 MWh of hydropower while each additional MWh of wind displaces 0.731 MWh of fossil power and reallocates 0.044 MWh of water generation. Considering the change in electricity imports causes the full effect to be a one to one displacement.

   The reallocated hydropower is switched to a different hour of the day, where it displaces another fossil fuel plant and offsets even more emissions. Wind and solar generation exhibit mostly a daily intermittency pattern. Hence, using a dynamic model that aggregates hourly into daily data, I estimate the appropriate average marginal carbon dioxide emissions offsets of solar (0.46t C[O.sub.2]/MWh) to be larger than those of wind (0.319 tC[O.sub.2]/MWh). Results from a Hausman test on the endogeneity of wind and solar generation, using their weather based hour-ahead forecasts as instruments, show that their hourly and daily variation is exogenous and does not affect the identification of marginal generation and emissions offsets.

   Furthermore, these offsets vary throughout time: they increase during spring and summer since more polluting fossil generators supply the seasonal larger demand, and they slightly decline as years go by due to new renewable capacity substituting these polluting plants. Accounting for displaced electricity imports, I estimate solar and wind carbon offsets to increase substantially to 0.615 and 0.465 tC[O.sub.2]/MWh, respectively.

   It is worth noting that the dynamic model complies with the net zero hydropower displacement condition for a fixed reservoir: the gain in one period has to be compensated with a loss at a different time. Results show that, on average, the larger daily solar intermittency leads to hydro reallocation within one day while the less pronounced wind power variation leads to a two-day arbitrage. Since solar power delivers most generation at the midday and decays in the afternoon it leads to hydro arbitrage that substitutes combustion turbines with the cleaner steam turbines. On the other hand, wind power peaks at midnight and decreases during the day, which leads to a substitution of generators with similar emissions intensities: combined cycle for steam turbines. Therefore, solar power delivers larger carbon and sulfur dioxide offsets than wind. These dynamics were contingent on having dry years during 2013-2015, which allowed a significant share of hydro to be reallocated due to the less stringent flow requirements during dry periods.

   These findings highlight that accounting for the dynamic interactions between the three renewable sources is necessary for assessing the proper external benefits and value of intermittent renewables. In California hydropower enhances the emissions offsets of solar power. Using the US social cost of carbon central estimate (IAWG, 2015) and marginal damages estimates for S[O.sub.2] and NOx (Muller and Mendelhson, 2009), solar power external benefits range between 9.78 and 30.08 per USD/MWh while for wind the range is 8.31 to 19.2 USD/MWh. Summing up, the external benefits of renewable energy vary per technology and throughout time, and their incentives and subsidies should reflect this.

   From a broader perspective, the proposed dynamic modelling is key for understanding electricity generation and emissions in grids with increasing adoption of storage technologies since the same insights about hydropower reallocation would apply to profit maximizing storers. Furthermore, several emerging economies with electric grids powered by a significant share of hydropower are increasingly adopting wind and solar plants. To the extent that these countries dispatch generators based on the lowest marginal cost (via wholesale market) this paper's methodology is a good approach for assessing the heterogeneous value of their renewable energy emissions offsets and guiding the (re)design of related incentives and policies.

2. ESTIMATING INTERMITTENT RENEWABLE ENERGY CARBON AND POLLUTION OFFSETS

   Using either historical data or projections of fossil fuel generation, load and intermittent renewable energy, several studies have quantified the pollution and carbon offsets that occur when electricity coming from solar or wind power plants substitutes for any fossil based electricity on the grid. Callaway et al. (2017) focus on how additional intermittent renewable generation (solar and wind) and energy efficiency measures displace carbon emissions in six power system regions of the United States (CAISO, ERCOT, ISONE, MISO, NYISO, PJM). They estimate the marginal emissions for each hour by regressing emissions on dispatchable fossil generation, and then compute the "average emissions displacement rates" using the previous estimate and projections of renewable energy production.

   Cullen (2013) recognizes that adding wind power (intermittent supply) has a different effect on the electricity grid and dispatch schedule than reducing load (demand) or fossil generation (dispatchable supply). Using historical data for Texas (ERCOT), the author regresses conventional generation types on the exogenous wind electricity production and other controls to infer what changes occur to the power mix when an intermittent supply of renewable energy is added. This estimate along with EPA's average annual emission rates for fossil fuel plants is used to compute offset emissions.

   The study highlights that in order to capture the dynamic factors such as startup, shut down, and ramping effects that play into the generators' decision making, we need to incorporate lags of wind generation as controls in the econometric model. The static and dynamic models yield

   different results: the latter finds fewer emissions offsets coming from coal and more coming from the expensive and inefficient steam and gas turbine generators. Neither model finds significant hydropower offsets, but it is worth noting that hydro is less than 1% of total capacity and generation in Texas (Cullen, 2013).

   Kaffine et al. (2013 and 2012) uses historical patterns of wind power in ERCOT to directly estimate emissions offsets by regressing the amount of pollutants and carbon on renewable energy production, demand, temperature, and other controls. Novan (2015) captures the hourly variation in electricity demand, wind generation and marginal generators throughout the day by modelling generation and emissions as a function of the interactions between wind power generation and load, while controlling for certain fixed effects.

   Hence, this research finds that wind power causes larger emissions offsets than solar in Texas, given that the former displaces coal base power during low demand night hours. Furthermore, new capacity increases in wind power would bring larger emissions offsets while solar capacity increases would not. The author also considers a dynamic model, which renders similar results to its static counterpart. This implies that wind power causes mainly instantaneous emissions offsets. It is worth noting that wind causes practically zero hydropower offsets in a grid where water has a share of less than 1%.

   In this paper I estimate how much C[O.sub.2], S[O.sub.2] and NOx wind and solar power abate in California, a worldwide leader in renewable energy adoption. The novel challenge lies in identifying the marginal generation and emissions offsets caused by adding two intermittent sources to an electric system that has a significant share of hydropower. Hence, I contribute to the literature by estimating emissions offsets in the presence of dynamics that reallocate hydropower, alter fossil generation and emissions. Capturing this dynamic effect on emissions offsets and on the value of wind and solar requires modelling not only the contemporaneous or static...