Day-ahead Auction Research Articles

Optimal recharging strategy for battery-switch stations for electric vehicles in France

Most papers that study the recharging of electric vehicles focus on charging the batteries at home and at the work-place. The alternative is for owners to exchange the battery at a specially equipped battery switch station (BSS). This paper studies strategies for the BSS to buy and sell the electricity through the day-ahead market. We determine what the optimal strategies would have been for a large fleet of EVs in 2010 and 2011, for the V2G and the G2V cases. These give the amount that the BSS should offer to buy or sell each hour of the day. Given the size of the fleet, the quantities of electricity bought and sold will displace the market equilibrium. Using the aggregate offers to buy and the bids to sell on the day-ahead market, we compute what the new prices and volumes transacted would be. While buying electricity for the G2V case incurs a cost, it would have been possible to generate revenue in the V2G case, if the arrivals of the EVs had been evenly spaced during the day. Finally, we compare the total cost of implementing the strategies with the cost of buying the same quantity of electricity from EDF. • Optimal strategies for buying/selling electricity through day-ahead auction market. • Given fleet size power bought and sold would change market price and volume. • New prices computed using aggregate offers to buy/sell power in 2010 and 2011. • Timing of arrival of EVs critical in V2G case. If evenly spaced BSS makes money. • Strategies are very robust even when French and German markets were coupled Nov. 2010.

Electricity market auction settings in a future Danish electricity system with a high penetration of renewable energy sources – A comparison of marginal pricing and pay-as-bid

The long-term goal for Danish energy policy is to be free of fossil fuels through the increasing use of renewable energy sources (RES) including fluctuating renewable electricity (FRE). The Danish electricity market is part of the Nordic power exchange, which uses a Marginal Price auction system (MPS) for the day-ahead auctions. The market price is thus equal to the bidding price of the most expensive auction winning unit. In the MPS, the FRE bid at prices of or close to zero resulting in reduced market prices during hours of FRE production. In turn, this reduces the FRE sources’ income from market sales. As more FRE is implemented, this effect will only become greater, thereby reducing the income for FRE producers. Other auction settings could potentially help to reduce this problem. One candidate is the pay-as-bid auction setting (PAB), where winning units are paid their own bidding price. This article investigates the two auction settings, to find whether a change of auction setting would provide a more suitable frame for large shares of FRE. This has been done with two energy system scenarios with different shares of FRE. From the analysis, it is found that MPS is generally better for the FRE sources. The result is, however, very sensitive to the base assumptions used for the calculations.

PROFIT–BASED UNIT COMMITMENT PROBLEM WITH BILATERAL CONTRACTS

This paper addresses the thermal unit commitment problem for power generation companies that operating in the market environment. The model for this problem is formulated as a deterministic optimization task where the optimal solution obtained using the 0/1 mixed-integer linear programming technique. The main feature of the model is that it provides a comprehensive and accurate representation of operating costs and operating constraints for thermal units. The model have been incorporated a long-term bilateral contracts with defined profiles power and price, and forecasted market for hourly prices for day-ahead auction. Solution is achieved using the homogeneous and self-dual interior point method for linear programming with a branch and bound optimizer for binary programming. The effectiveness of the proposed model is demonstrated through case study with detailed discussion.

Implicit auctioning on the Kontek Cable: Third time lucky?

Implicit auctioning in Europe is about eliminating cross-border trade inefficiencies by internalizing cross-border trade into the day-ahead auction procedures of the Power Exchanges that are already organizing trade nationally. On the Kontek Cable, implicit auctioning has first been implemented with “no coupling” between the relevant Power Exchanges, followed by a “volume coupling” implementation, and finally a “one way price coupling” implementation that is still operational today. The main contribution of this paper is to compare the theoretical properties of these three implementations and to analyze their performance empirically. We find that the third implementation is significantly outperforming the previous two implementations, but in this third implementation stakeholders partly abandoned the “volume coupling” approach they initially believed to be a viable alternative and institutionally easier to implement.

On Clearing Coupled Day-Ahead Electricity Markets

The European power grid can be divided into several market areas where the price of electricity is determined in a day-ahead auction. Market participants can provide continuous hourly bid curves and combinatorial bids with associated quantities given the prices. The goal of the auction is to determine cross-border flow and market clearing prices. Whereas this can be done rather efficiently in the absence of combinatorial structure, in the case of electricity markets the determination of a market clearing price is hard. We present and solve a non-discriminatory market model to determine clearing prices that maximize the economic surplus of all participants. The determined prices are consistent throughout the market areas. At first it would seem that one price for all market areas is appropriate. This however is not true. We will explain these price differentials as consequences of the underlying optimization problem.

The effect of contingency analysis on the nodal prices in the day-ahead market

We look at the effect of modeling branch-outage contingencies on locational marginal prices. To model contingencies in the day-ahead auction, we formulate a two-stage stochastic program. Rather than follow the current practice of including a list of possible contingencies that must be satisfied, we incorporate a larger set of contingencies in the model and allow contingencies to result in load reductions/outages at a cost. The model can be used and interpreted in two ways. One is to look at the tradeoff between reliability and outage costs. Another is to consider the load losses resulting from a contingency to be consumer offers of load reductions in response to line outages as part of the day-ahead auction. In analyzing the model structure, we find that the prices in the model closer in definition to those currently used in the day-ahead auction do not maximize expected surplus because the day-ahead auction produces prices that assume shortages will never occur. This raises issues with the design of auctions with important stochastic elements in the market. We present results for a 68-node grid with 86 branches (lines and transformers) to illustrate how prices and expected values change as the costs of outages are varied.

Market coupling and the importance of price coordination between power exchanges

In Europe, market coupling stands for a further integration of wholesale trading arrangements across country borders. More specifically, it refers to the implicit auctioning of cross-border physical transmission rights via the hourly auctions for electric energy organized by power exchanges (PEXs) one day ahead of delivery. It therefore implies that the PEXs can optimize the clearing of their day-ahead auctions. Due to verticals in the aggregated order curves, the optimal solution can be settled at different prices. In order for prices to give correct locational signals for network development, generation and consumption, price coordination between exchanges is necessary. The paper illustrates this issue, its relevance and discusses how to deal with it.

Hydrothermal self-scheduling problem in a day-ahead electricity market

This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis.

Simultaneous bidding in day-ahead auctions for spot energy and power systems reserve

In this paper a novel approach for simultaneous bidding in day-ahead auctions for spot energy and power systems reserve is presented. For the spot market a relatively simple method is considered as a competitive market is assumed. For the reserve market the bidder is considered to behave strategically and the behavior of the competitors is summarized in a joint probability distribution of the market price. This results in a method for simultaneous bidding, where the bidding prices and capacities on the spot and reserve markets are calculated by maximizing a stochastic non-linear objective function of expected profit.

Markets Design, Bidding Rules, and Long Memory in Electricity Prices

In uniform price, sealed-bid, day-ahead electricity auctions, the market price is set at the intersection between aggregate demand and supply functions constructed by a market operator. Each day, just one agent - the marginal generator - owns the market-clearing plant. Moreover, day-ahead auctions are embedded in multi-segment systems, wherein diverse protocols coexist and change over time. This complex environment leads to adoption of simple, adaptive bidding rules. Specifically, such a market design enables the emergence of two different types of routines, depending on whether the agent is a likely marginal or inframarginal generator. However, because of the uniform price mechanism, only the bidding behavior of the former can be reflected into market prices. Depending on the specific way marginal generators process past information to set their bids - « hyperbolic » or « exponential » - electricity prices are likely to display long- or short-memory. Using an analogy with the hyperbolic discounting - a quite robust behavioral bias in humans - a long-memory view of electricity prices is proposed. This insight is confirmed by spectral analysis of daily data from NordPool and CaIPX markets, in sharp contrast with most previous empirical studies. This paper underlines the importance of institutional settings in determining the relationship between individual behavior and market outcomes, and proposes an interesting mapping of bidding rules and models of information processing into the time series properties of market prices.