Grid Investment and Support Schemes for Renewable Electricity Generation.

AuthorWagner, Johannes
PositionReport
  1. INTRODUCTION

    A large number of electricity systems, for example in the United States or Europe, have been liberalized and restructured over the last decades. A central part of these restructuring efforts is unbundling, which describes the vertical separation of the monopolistic network from the potentially competitive parts of the system, namely generation, wholesale and retail. In unbundled electricity systems, separate entities such as private generation investors and regulated transmission operators make investment decisions based on their individual agenda. Nevertheless, there exist strong interactions between these decisions because of the physical properties of the electricity system, which leads to a coordination problem between generation investment and grid investment. New power plants can for example increase network congestion and therefore force extensions which could be avoided by choosing a different location for the investment. (1)

    To address the outlined coordination problem, a proactive approach to transmission planning is increasingly proposed, in which the transmission operator attempts to optimize the aggregated electricity system by taking into account consumer welfare, generation costs and transmission costs. Consequently, the transmission planner explicitly considers the effect of grid extensions on the decision problem of generation investors in order to implement an overall welfare optimal system configuration. Anticipatory planning processes therefore extend the traditional approaches to transmission investment, which focus primarily on reliability issues and technical feasibility instead of an economically optimal total system configuration.

    The need for cost effective transmission planning is intensified by the increasing importance of electricity generation from intermittent renewable energy sources such as wind and solar. Because of the weather dependency of these energy sources, the best locations for wind and solar power plants are typically distributed and located away from load centers. As a result, the integration of large amounts of generation capacity based on wind and solar energy into the electricity system requires substantial investments into the electricity grid. (2) Despite these integration challenges, renewable energy investors face favorable regulations regarding grid connection in many countries, which often oblige the grid operator to connect new generation capacities based on renewable energy sources. (3) Consequently, the regulatory framework frequently promotes reactive approaches to transmission planning.

    Investment into electricity generation from renewable energy sources is largely driven by support mechanisms such as feed-in tariff systems, feed-in premium systems or capacity subsidies. (4) A crucial difference between these subsidy systems is how producers of renewable electricity are exposed to market signals. Under feed-in tariffs renewable generators receive a fixed payment for every produced kilowatt hour of electrical energy. Consequently, generators are entirely isolated from market signals. With capacity subsidies on the other hand, producers of renewable energy are fully exposed to market signals because they generate revenue only due to electricity sales in the wholesale market. Feed-in premiums combine the described approaches by paying a fixed premium on top of the wholesale electricity price to renewable energy producers.

    Against the described backdrop, this paper analyzes the influence of the subsidy scheme for renewable electricity generation on the locational choice of renewable energy investors and the subsequent implications for grid investments. Of particular interest are inefficiencies which arise due to deviations from the socially optimal allocation of renewable generation capacities when transmission investment follows renewable energy investment. Building on that, anticipatory behavior of the transmission operator is assessed as a potential remedy to avoid inefficient system configurations. To analyze these issues a highly stylized model with one demand node, two possible locations for renewable generation investment and lumpy transmission investment is developed. Electricity generation at the two locations is stochastic with different total expected generation and imperfectly correlated generation patterns. Renewable energy investments are subsidized by a feed-in tariff scheme, a feed-in premium system or direct capacity payments in order to reach an exogenous renewable target. (5) The analysis is conducted for wind power, however the results apply for all intermittent and location dependent renewable energy sources such as solar or marine energy.

    The analysis shows, that none of the assessed support mechanisms guarantees an efficient allocation of generation capacities. In a feed-in tariff system, investors develop only the wind location with the highest expected generation because they are isolated from market signals. Consequently, social benefits from developing both locations, which arise because of the imperfect correlation between wind generation at both sites, are not realized. With capacity payments on the other hand, investors do receive market signals but grid investment costs are external. As a result, investors diversify locations even if the social benefit does not justify the additional grid investment costs, which are necessary to integrate the second wind location into the system. In a feed-in premium system, investors generate revenue from fixed premium payments and from market participation. Hence, investors act either as in a feed-in tariff system or as in a system with capacity payments, depending on which of the two revenue streams dominates. Building on these results I find, that the efficient system configuration can be implemented by anticipatory transmission investment. The results imply, that the locational choice of investors depends on the choice of the subsidy mechanism and that a more active role of the grid operator can help to efficiently integrate renewable energy sources into electricity systems.

    The described results are derived in a stylized model framework. Nevertheless, the implications are of high policy relevance. The coordination between investment into generation capacities based on renewable energy sources and investment into transmission lines is a practical issue in a large variety of countries which plan to increase the share of renewable energy in electricity generation. Practical examples for the United States, the European Union, Mexico, Panama, Egypt, Brazil and the Philippines are provided in Madrigal and Stoft (2012). Additionally, numerical studies show that the analyzed inefficiencies are already of relevance in practice. Obermuller (2017) shows that the current regulatory framework in Germany overincentivizes investment in Northern Germany because transmission bottlenecks are not accounted for. Similarly, Bjornebye et al. (2018) show for Norway that wind power investment at inefficient locations, which is encouraged by the current regulation, could increase the required grid expansion by 55%. Building on these practical examples, the present paper derives some general conclusions and intends to derive practical implications for policy makers based on theoretical economics.

    The paper is mainly related to two literature streams. The first relevant literature stream examines the efficiency of different subsidy schemes for electricity generation from renewable energy sources. Hiroux and Saguan (2010) give an overview of the advantages and disadvantages of different support schemes with respect to the integration of large amounts of wind power into the European electricity system. They argue that support schemes should expose wind power producers to market signals in order to incentivize system optimal choices of wind sites and maintenance planning or to incorporate portfolio effects. Klessmann et al. (2008) on the other hand point out that market exposure increases risk for investors, which leads to a higher required level of financial support in order to stimulate investments. The impact of renewable energy subsidies on the spatial allocation of wind power investments is explicitly studied in Schmidt et al. (2013) and Pechan (2017). Schmidt et al. (2013) analyze the spatial distribution of wind turbines under a feed-in premium and a feed-in tariff scheme based on an empirical model for Austria. They find that the feed-in premium system leads to substantially higher diversification of locations for wind power generation. Pechan (2017) shows in a numerical model, that a feed-in premium system combined with nodal pricing leads to a system friendly allocation of wind power if existing transmission lines are congested. All mentioned papers do not consider capacity payments or the required grid extensions to integrate the wind power capacity into the electricity system.

    The second relevant literature stream is focused on the coordination problem between transmission and generation investment in liberalized power markets and the effects of anticipatory transmission investment. Sauma and Oren (2006) and Pozo et al. (2013) show that a proactive transmission planner can induce generation companies to invest in a more socially efficient manner by anticipating investments in generation capacity. Hoffler and Wambach (2013) show that generation investment can lead to overinvestment or underinvestment in the electricity grid when private investors do not take the costs and benefits of network extensions into account. They also show that a capacity market can incentivize private investors to make socially efficient locational choices. The implications of renewable subsidies on the coordination problem are not part of the mentioned studies. The interactions of renewable portfolio standards and transmission planning are examined in Munoz et al. (2013). They show that ignoring...

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT