Emission Trading Systems and the Optimal Technology Mix

Cap and trade mechanisms enjoy increasing importance in environmental legislation worldwide. The most prominent example is probably given by the European Union Emission Trading System (EU ETS) designed to limit emissions of greenhouse gases, several other countries already have or are planning the introduction of such systems. One of the important aspects of designing cap and trade mechanisms is the possibility of competition authorities to grant emission permits for free. Free allocation of permits which is based on past output or past emissions can lead to inefficient production decisions of firms’ (compare for example B¨ohringer and Lange (2005), Rosendahl (2007), Mackenzie et al. (2008), Harstad and Eskeland (2010)). Current cap and trade systems grant free allocations based on installed production facilities, which lead to a distortion of firms’ investment incentives, however. It is the purpose of the present article to study the impact of a cap and trade mechanism on firms’ investment and production decisions and to analyze the optimal design of emission trading systems in such an environment

Investment Incentives and Electricity Spot Market Design

In liberalized electricity markets strategic firms compete in an environment characterized by fluctuating demand and non-storability of electricity. While spot market design under those conditions by now is well understood, a rigorous analysis of investment incentives is still missing. Existing models, as the peak-load-pricing approach, analyze welfare optimal investment and find that optimal investment is higher with more competitive spot markets. In this article we want to extend the analysis to investment decisions of strategic firms that anticipate competition on many consecutive spot markets with fluctuating (and possibly uncertain) demand. We study how the degree of spot market competition affects investment incentives and welfare and provide an application of the model to electricity market data. Our results show that more competitive spot market prices strictly decrease investment incentives of strategic firms. The reduction of investment incentives can be so intense to even offset the beneficial impact of more competitive spot market design. Those results obtain with and without free entry. Our analysis thus demonstrates that investment incentives necessarily have to be taken into account for a meaningful assessment of proper electricity spot market design

Information Disclosure in Open Non-Binding Procurement Auctions: an Empirical Study

The outcome of non-binding reverse auctions critically depends on how information is distributed during the bidding process. We use data from a large European procurement platform to study the impact of different information structures, specifically the availability of quality information to the bidders, on buyers' welfare and turnover of the platform. First we show that on the procurement platform considered bidders indeed are aware of their rivals' characteristics and the buyers preferences over those non-price characteristics. In a counterfactual analysis we then analyze the reduction of non-price information available to the bidders. As we find, platform turnovers in the period considered would decrease by around 30%, and the buyers' welfare would increase by the monetary equivalent of around 45% of turnover of the platform

Transparency in Buyer-Determined Auctions: Should Quality be Private or Public?

We study non-binding procurement auctions where both price and non-price characteristics of bidders matter for being awarded a contract. The outcome of such auctions critically depends on how information is distributed among bidders during the bidding process. As we show theoretically, whether it is in the buyer's interest to conceal or to disclose non-price information most importantly depends on how important the quality aspects of the good to be procured are to the buyer: The more important the quality aspects are to the buyer, the more interesting concealment becomes. We then empirically study the impact of a change in the information structure using data from a large European online procurement platform for different categories of goods. In a counterfactual analysis we analyze the reduction of non-price information available to the bidders. In the data we find that the choice of information structure indeed matters. Confirming the hypothesis obtained in our theoretical framework, we find that in auction categories where bidders' non-price characteristics are of little importance for the decisions of the buyers, concealment of non-price information decreases buyers' welfare by up to 6% due to reduced competitive pressure leading to higher bids. In contrast, for categories where bidders' non-price characteristics strongly influence buyers' decisions concealment of non-price information increases buyers' welfare by up to 15%

Transmission and Generation Investment in Electricity Markets: The Effects of Market Splitting and Network Fee Regimes

In this paper we propose a three–level computational equilibrium model that allows to analyze the impact of the regulatory environment on transmission line expansion (by the regulator) and investment in generation capacity (by private firms) in liberalized electricity markets. The basic model analyzes investment decisions of the transmission operator (TO) and private firms in expectation of an energy only market and cost-based redispatch. In different specifications we consider the cases of one versus two price zones (market splitting) and analyze different approaches to recover network cost, in particular lump sum, capacity based, and energy based fees. In order to compare the outcomes of our multi–stage market model with the first best benchmark, we also solve the corresponding integrated planer problem. In two simple test networks we illustrate that energy only markets can lead to suboptimal locational decisions for generation capacity and thus, imply excessive network expansion. Market splitting heals those problems only partially. Those results obtain for both, capacity and energy based network tariffs, although investment slightly differs across those regimes

Robust Market Equilibria under Uncertain Cost

This work studies equilibrium problems under uncertainty where firms maximize their profits in a robust way when selling their output. Robust optimization plays an increasingly important role when best guaranteed objective values are to be determined, independently of the specific distributional assumptions regarding uncertainty. In particular, solutions are to be determined that are feasible regardless of how the uncertainty manifests itself within some predefined uncertainty set. Our mathematical analysis adopts the robust optimization perspective in the context of equilibrium problems. First, we present structural insights for a single-stage, nonadjustable robust setting. We then go one step further and study the more complex two-stage or adjustable case where a part of the variables can adjust to the realization of the uncertainty. We compare equilibrium outcomes with the corresponding centralized robust optimization problem where thesum of all profits are maximized. As we find, the market equilibrium for the perfectly competitive firms differs from the solution of the robust central planner, which is in stark contrast to classical results regarding the efficiency of market equilibria with perfectly competitive firms. For the different scenarios considered, we furthermore are able to determine the resulting price of anarchy. In the case of non-adjustable robustness, for fixed demand in every time step the price of anarchy is bounded whereas it is unbounded if the buyers are modeled by elastic demand functions. For the two-stage adjustable setting, we show how to compute subsidies for the firms that lead to robust welfareoptimal equilibria.Comment: 26 page

Energy storage in residential and commercial buildings via Liquid Organic Hydrogen Carriers (LOHC)

This contribution proposes the usage of Liquid Organic Hydrogen Carriers (LOHC) for the establishment of a decentralised energy storage network. Due to the continually increasing amount of renewable energy within the power grid, in particular in countries of the European Union, a huge demand for storage capacities develops that can hardly be met by large-scale systems alone. Because of their high storage density and good manageability LOHC substances permit the local storage of excess energy in residential and commercial buildings. Following the approach of a CHP system ('combined heat and power' or more precisely a `combined heat and storage' system), thermal losses from the storage processes can be used for heating (and cooling) purposes in order to increase the overall efficiency. An evaluation of the economic feasibility identifies possible approaches to generate income from storage operation. The usage of exhaust heat for heating proves to significantly support the business case by providing a considerable financial contribution that is usually not exploitable for centralised storage units

On optimal scarcity prices

This article contributes to the debate of missing money (compare Joskow(2007a)). This debate has seriously questioned the desirability of limiting scarcity prices in markets with fluctuating demand by emphasizing their potentially negative impact on firms' investment decisions in the long run. A prominent example are recently liberalized electricity markets, where competition authorities have imposed price caps3 or adopted other measures to mitigate high scarcity prices. The impact of reduced scarcity prices in the long run still is only incompletely explored. We thus analyze investment of firms in base load and peak load technologies in a market with fluctuating demand under imperfect competition. We show that an appropriately chosen limitation of scarcity prices is not only beneficial in the short run but also in the long run. It leads to a strict increase of investment in peak load technologies, leaving investment in base load technologies unchanged. Furthermore, we characterize the optimal limit on scarcity prices.Investment incentives Fluctuating demand Scarcity rents Missing money