One Price Fits All? On Inefficient Siting Incentives for Wind Power Expansion in Germany under Uniform Pricing.

• Author: Schmidt, Lukas

1. INTRODUCTION

   1.1 Motivation

   With wind power capacities expected to play a central role in reducing greenhouse gas emissions, the decision as to where to install these systems becomes increasingly important. First, spatially distributed locations can flatten the variable nature of their electricity feed-in (balancing effects) and hence reduce the need for dispatchable generation capacities. Second, sites with high wind yield usually do not coincide with main load centers (cf. Borenstein, 2012). A large concentration of wind power plants at attractive but remote sites imposes challenges to the grid. Selecting the location of wind power plants is thus often a trade-off between high wind yield and grid congestion. This trade-off becomes more critical with increasing market shares of renewable energy sources (RES).

   The paper analyzes this problem by considering the example of Germany. About 25% of the electricity demand in Germany was covered by wind energy in 2019 (cf. AGEB, 2021), and further expansion is a clear political goal goal (cf. EEG, 2021). The typical pattern of remote locations offering better wind conditions also applies to Germany: Wind yield peaks in Northern Germany close to both the North Sea and the Baltic Sea. Demand for electricity, however, is highest in the densely populated, industry-rich areas of Southern and Western Germany. As a direct consequence, integrating RES generation into the grid has posed a challenge in recent years. (1) The current country-wide market design, which imposes a uniform electricity price, does not take grid bottlenecks into account. As a result, scheduled generation may be adjusted after market-clearing to align with grid restrictions, often referred to as redispatch. (2) Both redispatch volumes and costs have risen over recent years. Coordinating wind power expansion with grid bottlenecks is crucial to minimize electricity supply costs.

   In liberalized electricity systems, grid expansion--in terms of increasing transmission capacity--is subject to regulatory decisions, whereas wind power plants are built by private investors. Due to long approval and construction periods, grid expansion projects are fixed for the long term, usually before the decision to invest in new generation capacity is made. (3) German and European regulatory authorities usually review and approve grid expansion projects at least 10 years in advance (cf. Bundesnetzagentur, 2019). Since this analysis covers the time horizon up to 2030, grid expansion is considered to be a given, even though the optimal grid expansion may differ between the nodal and the uniform market design. The expansion of wind power, on the other hand, is subsidized by the German government, as is the case in many other European countries. In addition to the revenue generated via the electricity market, wind turbines also receive a market premium for electricity fed into the grid. The value of the market premium is determined in capacity-based pay-as-bid auctions: new wind power projects bid according to their expected revenue, which is calculated based on the expected electricity prices, expected wind yield at the respective location and the correlation between wind availability and electricity price. Incentives for spatial diversification only arise due to the variations in wind feed-in (4) patterns across regions and the resulting balancing effects (cf. Schmidt et al., 2013). However, wind yield often prevails over balancing effects under uniform pricing due to high correlation of feed-in patterns (cf. Eising et al., 2020). As a result, wind power investors seek to maximize wind feed-in. In order to reduce the concentration of wind power investments in regions with high wind yields, the German government introduced a wind bonus-malus component into the auctions that is determined based on the expected wind yield (cf. EEG, 2021). The component aims to create incentives for constructing wind power plants in locations with lower wind yield. Nevertheless, wind power has continued to be primarily deployed at high wind-yield sites in Northern Germany.

   The expansion of intermittent electricity generation exerts negative externalities on the electricity grid. Pricing of externalities is the economically desirable instrument to overcome their detrimental effects (cf. e.g., Hogan, 1999; Borenstein, 2012; Wagner, 2019). While uniform prices fail to reflect grid externalities, nodal pricing regimes internalize these in market prices, to reflect the cost of both generation and grid constraints (cf. Weibelzahl, 2017). If, e.g., wind power feed-in in Northern Germany is too high to be integrated into the grid, low electricity prices arise there. If such situations occur frequently, the electricity price level drops and investments in wind power become unprofitable. This mechanism creates dynamic incentives in nodal price regimes for an efficient coordination of investments in wind energy with the existing grid (cf. Green, 2007). This also applies to investments in demand-side or flexibility assets: building energy-intensive industries becomes more attractive in regions with lower electricity prices, flexibility is added to regions with large fluctuations in the electricity price.

   In order to counteract problems with the grid integration of wind energy under uniform pricing, the amendment to the Renewable Support Scheme in 2017 (Erneuerbaren-Energien-Ge-setz 2017) introduced the so-called "grid expansion area" (Netzausbaugebiet). Within this designated area, investments are restricted to prevent excessive expansion of wind turbines at windy but grid-critical locations. Furthermore, spatially-differentiated grid tariffs for generators (cf. e.g., Haucap and Pagel, 2014; Grimm et al., 2019) can penalize wind power generation at grid-critical sites and hence positively affect social welfare (cf. e.g., ACER, 2015; Daxhelet and Smeers, 2007). Several European countries have introduced spatially-differentiated generator-components (g-com-ponents) in their grid tariff schemes, including e.g., Sweden, the UK and Norway (cf. ENTSO-E, 2019). While node-specific g-components can replicate the efficient investment signals of nodal pricing, the simplefied g-component approach eases information gathering for investors and tariff setting for regulators. Since distorted signals of uniform prices develop mainly along the North-South axis (cf. Obermiiller, 2017), this paper follows the Swedish grid tariff design and assess latitude-dependent g-components (THEMA, 2019).

   This paper quantifies the effects of nodal and uniform prices on the spatial distribution of wind power expansion. Welfare losses stemming from distorted incentives set by uniform prices as well as distributional effects resulting from the introduction of nodal prices are also examined. Furthermore, this paper evaluates to what extent welfare losses resulting from inefficient wind power siting can be mitigated by complementing uniform pricing with latitude-dependent g-components in grid tariffs or defining grid expansion areas.

   1.2 Related Literature

   This paper builds on two strands of literature: The first strand uses the concept of market values to evaluate the financial worth of power generation facilities. In recent years, several articles have used market values to analyze efficient RES expansion pathways. Joskow (2011), for example, introduces market values to evaluate intermittent power generators. Among others, Grubb (1991), Jagemann (2014) and Hirth (2013) discuss how RES market penetration affects market value. Some studies find that higher penetration of RES undermines their market value due to cannibalization effects (see e.g., Prol et al., 2020). In the case of increasing wind capacities, high intermittent feed-in, especially when there is a high degree of simultaneity, may result in a drop in the electricity price and thus lower the market revenue of wind power plants. Grothe and Musgens (2013), Elberg and Hagspiel (2015) and most recently Eising et al. (2020) use market values to shed light on the optimal distribution of wind power plants in Germany. However, these papers only consider uniform pricing. Accordingly, the market values only reflect the correlation of local wind feed-in with the uniform price signal and do not address grid restrictions. Consequently, the problem of coordination between RES deployment and grid bottlenecks is not examined.

   The second strand includes papers that either examine the trade-off between grid expansion and investment or analyze nodal market designs as a theoretically efficient instrument to solve this coordination problem. Lamy et al. (2016) examine the trade-off between grid expansion and investments in wind power plants at less attractive locations and find that wind power plants close to load centers are economically desirable. Opportunity costs of choosing sites with lower wind yields are lower than the avoided grid expansion costs. However, in a scenario comparison for Germany Boing et al. (2017) find the opposite. Grid expansion imposes fewer costs than an increased deployment of wind power plants in the low-wind area of Southern Germany. In an early work on nodal prices, Green (2007) investigates the welfare effects of switching from uniform to nodal prices in England/Wales. He finds that, in a static setting, the introduction of nodal prices avoids welfare losses of 1.5% with regards to the spot market revenues of electricity producers. He suggests that the efficient, dynamic incentive effects of nodal prices should significantly increase welfare gains. Leuthold et al. (2008) conduct a similar, static investigation of uniform and nodal market designs for Germany and find comparable welfare effects. They also emphasize the advantages of nodal prices in a dynamic context. Most recently, Triolo and Wolak (2021) estimate that switching from uniform to nodal pricing in Texas reduced supply costs of thermal power...