Wind Turbine Shutdowns and Upgrades in Denmark: Timing Decisions and the Impact of Government Policy.

• Author: Cook, Jonathan A.

1. INTRODUCTION

   Due to concerns about climate change, local air pollution, fossil fuel price volatility, energy security, and possible fossil fuel scarcity, governments at many levels around the world have begun implementing policies aimed at increasing the production share of renewables in the electricity sector. These support policies have taken several different forms (e.g., Renewable Portfolio Standards, feed-in-tariffs, tax credits, etc.), and proponents argue that they are necessary for these nascent industries to continue to develop technological improvements, achieve economies of scale, and compete with existing industries. Wind energy was one of the earliest renewable generation technologies to be promoted, and its maturity and low costs relative to other renewables have made it a leading option for many countries in the early phases of pursuing climate goals.

   For policymakers, an important long-run question related to the development of renewable industries is how government policies affect decisions regarding the scrapping or upgrading of existing assets. How much of the shutdowns and upgrades can be attributed to the policies as opposed to technological progress? How do policies affect the timing of owner decisions and the subsequent path of the industry?

   This paper aims to shed some light on these questions by developing a dynamic structural econometric model of wind turbine shutdowns and upgrades in the context of Denmark and using it to estimate the underlying profit structure for turbine owners. In particular, we model wind turbine owners' decisions about whether and when to add new turbines to a pre-existing stock, scrap an existing turbine, or replace old turbines with newer versions (i.e., upgrade). Shutting down and/or upgrading existing productive assets are important economic decisions for the owners of those assets and are also the fundamental decisions that underlie the development of new, growing industries.

   To date, empirical research addressing the economics of wind energy has tended to focus on production costs, investment decisions, or policy options for increasing the penetration of wind energy in electricity grids. Engineering studies have regularly calculated the cost of producing electricity from wind turbines and compared it with existing fossil-fuel generators (Darmstadter, 2003; Krohn et al., 2009). Trancik et al. (2015) describe the evolution of wind energy in recent decades, and find that wind energy is now nearly cost-competitive with natural gas- and coal-fired power plants in many regions of the world. Hartley and Medlock (2017) find that until fossil fuels are abandoned, however, the price of energy is insufficient to cover even the operating costs of renewable energy production, let alone provide a competitive return on the capital employed. Krekel and Zerrahn (2017) analyze whether the presence of wind turbines has negative externalities for people in their surroundings, and find that negative externalities exist but are spatially and temporally limited; Lang et al. (2014) find that wind turbines have no statistically significant negative impacts on house prices. Jacobsson and Johnson (2000) come at the problem from a technology innovation and diffusion perspective, and provide an analytical framework for examining the process of technical change in the electricity industry. Hartley (2018) examines the costs of replacing fossil fuels by wind generation and storage, and compares wind power with generation based on nuclear and storage. Oliveira et al. (2019) present an empirical analysis of the displacement of C[O.sub.2] emissions associated with wind generation in the Irish electricity market.

   Previous studies of scrapping decisions in the electricity industry have been either analytic, numerical, or reduced-form. Fleten et al. (2017) use a numerical real options analysis to study the effects of regulatory uncertainty and cash flow uncertainty on decisions to shut down, start up, and abandon existing peak power plants; we build on the methods used by Fleten et al. (2017) by estimating a dynamic model econometrically. Mauritzen (2014) estimates a reduced-form model of wind turbine scrapping decisions; we build on the work of Mauritzen (2014) by developing and estimating a dynamic structural econometric model, by utilizing additional data, by extending the model to include both shutdown and upgrade decisions, and by analyzing the effects and cost-effectiveness of government policy.

   The previous literature on wind policy has been aimed at describing the policies that have been implemented (Allison and Williams, 2010); evaluating different wind energy policies based on their ability to promote new investments (Agnolucci, 2007; May, 2017), wind production (Aldy et al., 2019), or innovation (Covert and Sweeney, 2019); examining whether current policies encourage investments in socially optimal renewable capacity additions (Novan, 2015); or comparing the policies of different countries with emerging wind industries (Klaassen et al., 2005). Hitaj (2013) analyzes the effects of government policies on wind power development in the United States. Ciarreta et al. (2017) compare feed-in-tariffs and tradable green certificates in the Spanish electricity system. Munksgaard and Morthorst (2008) provide an excellent description of the trends in feed-in-tariffs and the market price of electricity in Denmark, and forecast future investments in wind energy based on an estimated internal rate of return. Fell and Linn (2013) use a simulation model to compare the cost-effectiveness of renewable electricity policies, including renewable portfolio standards, production subsidies, and feed-in-tariffs, in the Electricity Reliability Council of Texas (ERCOT) region. Reguant (2019) analyzes the efficiency and distributional implications of large-scale renewable policies, including carbon taxes, feed-in-tariffs, production subsidies, and renewable portfolio standards, using data from the California electricity market.

   The "bottom-up" style of modeling we use in this paper is in direct contrast to many previous "top-down" approaches to examining trends in the wind industry, and the structural nature of our model gives insights into key economic and behavioral parameters. Understanding the factors that influence individual decisions to invest in wind energy and how different policies can affect the timing of these decisions is important for policies both in countries that already have mature wind industries, as well as in regions of the world that are earlier in the process of increasing renewable electricity generation (e.g. most of the U.S.).

   We apply our dynamic structural econometric model to owner-level panel data for Denmark over the period 1980-2011 to estimate the underlying profit structure for small wind producers (who constitute the vast majority of turbine owners in the Danish wind industry during this time period), and evaluate the impact of technology and government policy on wind industry development. Our structural econometric model explicitly takes into account the dynamics and interdependence of shutdown and upgrade decisions, and generates parameter estimates with direct economic interpretations.

   Results from our dynamic structural econometric model indicate that the growth and development of the Danish wind industry were driven primarily by government policies as opposed to technological improvements. We use the parameter estimates to simulate counterfactual policy scenarios in order to analyze the relative effectiveness and cost-effectiveness of the Danish feed-in-tariff and replacement certificate programs. Results show that both of these policies significantly impacted the timing of shutdown and upgrade decisions made by small wind producers and accelerated the development of the wind industry in Denmark. We also find that when compared with the feed-in-tariff; a declining feed-in-tariff; and the replacement certificate program and the feed-in-tariff combined, the replacement certificate program was the most cost-effective policy both for increasing payoffs of small wind producers and also for decreasing carbon emissions.

   The balance of our paper proceeds as follows. We describe the Danish wind industry in Section 2. We describe our dynamic structural econometric model in Section 3. We present the results in Section 4. Section 5 concludes.

2. THE DANISH WIND INDUSTRY

   For many countries, questions regarding wind turbine shutdown and upgrade decisions will become increasingly relevant in the near future as existing turbines approach the end of their expected lifetimes (usually around 20 years) and technology continues to improve. This is already the case in Denmark, where a concerted effort to transition away from fossil fuels began in the late 1970's soon after the first oil crisis. Since then, the long-term energy goal of the Danish government has been to have 100% of the country's energy supply come from renewable sources.

   With a long history of designing turbines that stretches back to the late 19th century (Heymann, 1998), wind power was Denmark's leading technological choice to offset electricity production from fossil fuels. To this end, the Danish government implemented several policies designed to encourage wind investments throughout the country. As a result of this sustained policy goal, Denmark became a leader in both turbine design and installed wind capacity during the 1980s and 1990s, and has one of the most mature modern wind industries in the world. Denmark has dominated other countries in wind deployment per capita and per GDP, and currently produces the equivalent of roughly 40% of its electricity demand in wind power (Trancik et al., 2015).

   We focus on the wind industry in Denmark over the period 1980-2011, and use data from a publicly available database containing all turbines constructed in Denmark during that time period (DEA, 2018)...