Revisiting minimum profit conditions in uniform price day-ahead electricity auctions

We examine the problem of clearing day-ahead electricity market auctions where each bidder, whether a producer or consumer, can specify a minimum profit or maximum payment condition constraining the acceptance of a set of bid curves spanning multiple time periods in locations connected through a transmission network with linear constraints. Such types of conditions are for example considered in the Spanish and Portuguese day-ahead markets. This helps describing the recovery of start-up costs of a power plant, or analogously for a large consumer, utility reduced by a constant term. A new market model is proposed with a corresponding MILP formulation for uniform locational price day-ahead auctions, handling bids with a minimum profit or maximum payment condition in a uniform and computationally-efficient way. An exact decomposition procedure with sparse strengthened Benders cuts derived from the MILP formulation is also proposed. The MILP formulation and the decomposition procedure are similar to computationally-efficient approaches previously proposed to handle so-called block bids according to European market rules, though the clearing conditions could appear different at first sight. Both solving approaches are also valid to deal with both kinds of bids simultaneously, as block bids with a minimum acceptance ratio, generalizing fully indivisible block bids, are but a special case of the MP bids introduced here. We argue in favour of the MP bids by comparing them to previous models for minimum profit conditions proposed in the academic literature, and to the model for minimum income conditions used by the Spanish power exchange OMIE

Is combination of nodal pricing and average participation tariff the best solution to coordinate the location of power plants with lumpy transmission investments?

This paper evaluates the opportunity and efficiency to introduce a two-part tariff to coordinate the location of power plants with lumpy transmission investments. Nodal pricing sends the short run component of such a two-part tariff and we study the case where the average participation tariff sends the long run one. We argue that this solution is helpful because the average participation tariff tackles lumpiness of transmission capacity while being as cost-reflective as possible. Our proposition is evaluated based on a double optimization model where a TSO minimizes the transmission cost while a generator minimizes its own cost that may take into account network constraints and include the average participation tariff. Numerical simulations are performed on a two-node network evolving during twenty years with increasing demand. The joint implementation of nodal pricing and the average participation tariff stays the best combination to coordinate as efficiently as possible the generation and transmission investments, although the optimal set of generation and transmission investments may not be reached because of transmission lumpiness. The simulations show also that implementing locational network tariffs is prioritary over implementing nodal pricing to coordinate more efficiently the location of generation with lumpy transmission investment. In the considered examples, the average participation tariff allows a more efficient location of generation even when the congestion management scheme being redispatch sends no short run locational signal.Generation investment; Lumpy transmission investment; Long run coordination; Locational signals; Efficiency evaluation

A Capacity Market that Makes Sense

We argue that a capacity market is needed in most restructured electricity markets, and present a design that avoids the many problems found in the early capacity markets. The proposed locational capacity market pays suppliers based on their demonstrated ability to supply energy or reserves in shortage hours—hours in which there is a shortage of operating reserves. Thus, only supply that contributes to reliability is rewarded. The capacity price responds to market conditions. When capacity is scarce the capacity price is high; when capacity is plentiful the capacity price is low or zero. Market power in the capacity market is addressed by setting the capacity price based on actual capacity, rather than bid capacity, so generators cannot increase the capacity price by withholding supply. Ex post peak energy rents (the short-run energy profits of a benchmark peaking unit) are subtracted from the capacity price. Thus, a supplier does not have an incentive to create real-time shortages—the high shortage price resulting from a shortage is subtracted from the capacity price, so there is no net gain from the high price. By defining a capacity product closely tied to reliability and directly addressing market power both in the capacity market and in the spot energy market, the proposed design results in a market participants can trust to encourage efficient behavior both in the short run and long run.Auctions, Electricity Auctions, Capacity Auctions, Market Design

A MIP framework for non-convex uniform price day-ahead electricity auctions

It is well-known that a market equilibrium with uniform prices often does not exist in non-convex day-ahead electricity auctions. We consider the case of the non-convex, uniform-price Pan-European day-ahead electricity market "PCR" (Price Coupling of Regions), with non-convexities arising from so-called complex and block orders. Extending previous results, we propose a new primal-dual framework for these auctions, which has applications in both economic analysis and algorithm design. The contribution here is threefold. First, from the algorithmic point of view, we give a non-trivial exact (i.e. not approximate) linearization of a non-convex 'minimum income condition' that must hold for complex orders arising from the Spanish market, avoiding the introduction of any auxiliary variables, and allowing us to solve market clearing instances involving most of the bidding products proposed in PCR using off-the-shelf MIP solvers. Second, from the economic analysis point of view, we give the first MILP formulations of optimization problems such as the maximization of the traded volume, or the minimization of opportunity costs of paradoxically rejected block bids. We first show on a toy example that these two objectives are distinct from maximizing welfare. We also recover directly a previously noted property of an alternative market model. Third, we provide numerical experiments on realistic large-scale instances. They illustrate the efficiency of the approach, as well as the economics trade-offs that may occur in practice

The efficiency of short run and long run locational signals to coordinate generation location with lumpy transmission investments

International audienceThis paper addresses the problem of interaction between short run and long run locational signals and the coordination between generation investments and lumpy transmission investments. The short run locational signals we evaluate are sent by nodal pricing and the long run ones are sent by the average participation use-of-the-network tariff. Their joint implementation is also deemed. Numerical simulations are performed on a two-node network evolving during twenty years with increasing demand. The efficiency of these locational signals to coordinate the location of generation with lumpy transmission investments is measured. An independent Transmission System Operator invests to minimize the total cost of the network, that is to say the sum of the cost of congestion with the cost of transmission investments. And a unique generator behaving competitively chooses the location of her investments depending on two elements: the locational difference in generation investment costs and the costs of the network she may pay with short run nodal prices and with the long run average participation tariff. The network tariff varies with the transmission investments. And the transmission capacity greatly influences nodal prices. We find out that neither short run nodal prices nor long run average participation tariffs can thoroughly coordinate efficiently generation and transmission investments because of the lumpiness of transmission line capacities

Three essays on pricing and risk management in electricity markets

A set of three papers forms this dissertation. In the first paper I analyze an electricity market that does not clear. The system operator satisfies fixed demand at a fixed price, and attempts to minimize cost as indicated by independent generators\u27 supply bids. No equilibrium exists in this situation, and the operator lacks information sufficient to minimize actual cost. As a remedy, we propose a simple efficient tax mechanism. With the tax, Nash equilibrium bids still diverge from marginal cost but nonetheless provide sufficient information to minimize actual cost, regardless of the tax rate or number of generators.;The second paper examines a price mechanism with one price assigned for each level of bundled real and reactive power. Equilibrium allocation under this pricing approach raises system efficiency via better allocation of the reactive power reserves, neglected in the traditional pricing approach. Pricing reactive power should be considered in the bundle with real power since its cost is highly dependent on real power output. The efficiency of pricing approach is shown in the general case, and tested on the 30-bus IEEE network with piecewise linear cost functions of the generators.;Finally the third paper addresses the problem of optimal investment in generation based on mean-variance portfolio analysis. It is assumed the investor can freely create a portfolio of shares in generation located on buses of the electrical network. Investors are risk averse, and seek to minimize the variance of the weighted average Locational Marginal Price (LMP) in their portfolio, and to maximize its expected value. I conduct simulations using a standard IEEE 68-bus network that resembles the New York - New England system and calculate LMPs in accordance with the PJM methodology for a fully optimal AC power flow solution. Results indicate that the network topology is a crucial determinant of the investment decision as line congestion makes it difficult to deliver power to certain nodes at system peak load. Determining those nodes is an important task for an investor in generation as well as the transmission system operator