Capacity Bids Research Articles

Can Producers Apply a Capacity Cutting Strategy to Increase Prices? The Case of the England and Wales Electricity Market

Promoting competition among electricity producers is primarily targeted at ensuring low electricity prices for consumers. Producers could, however, withhold part of production facilities (i.e., apply a capacity cutting strategy) and thereby push more expensive production facilities to satisfy demand for electricity. This behavior could eventually lead to a higher price determined through a uniform price auction. In this paper, using the case of the England and Wales wholesale electricity market, we empirically examine whether producers can indeed apply a capacity cutting strategy. We analyze the bidding behavior of producers during high- and low-demand trading periods across trading days and find direct and indirect evidence for producers' successful manipulation of capacity bids targeted at increasing a wholesale electricity price. We also examine whether the regulatory reforms to improve competition were successful at mitigating the extent of strategic capacity manipulation.

Resource Adequacy and the Impacts of Capacity Subsidies in Competitive Electricity Markets

Motivated by recent interventions by the states of New Jersey and Maryland and the introduction of PJM’s Minimum Offer Price Rule (MOPR) for capacity markets, we analyze the impact of subsidized government investments in electrical generation on electricity markets. We extend the model of Joskow and Tirole (2007) to address the interconnected nature of the PJM grid by considering a market with two different locations connected by transmission lines. We assume that these lines are constrained during peak periods in a manner similar to Borenstein, Bushnell, and Stoft (2000). We find that government intervention has significant potential for adverse effects on grid resource adequacy and reliability. In our analysis, subsidized investment in baseload capacity is never optimal. Government provision of base capacity displaces competitive capacity in the short run and likely discourages the provision of peak capacity. In the long run, the threat of intervention imposes costs on suppliers in the form of an expected regulatory taking. As a result, resource adequacy decreases in both markets. If governments respond to this state of affairs by subsidizing further supply additions, expectations of intervention are reinforced and competitive capacity supply further diminishes. MOPR attempts to mitigate this vicious cycle by screening out non-economic capacity bids. To the extentMOPR succeeds in this goal and market participants view it as a credible policy, subsidized capacity additions do not perturb the efficiency of market outcomes as long as any charges to consumers to support the subsidy are lump sum in nature. In this case, subsidized resources simply succeed in capturing rents from taxpayers.

A Reactive Power Capacity Market Using Annual Auctions

This paper presents a new approach to design reactive power capacity markets. Under this approach annual auctions to procure reactive power capacity are conducted by the system operator. Two products are defined, reactive power generation and absorption capacity, which can be supplied by different independent VAR sources, such as generators, SVCs, capacitor banks and shunt reactors. Reactive power capacity is allocated using an optimization algorithm that matches capacity bids and system reactive power needs, for peak and low demand hours. The reactive power requirements are calculated taking into account system contingencies and the dynamic performance of the VAR sources under these situations. Another key proposal of the paper is the distribution of costs of the reactive power capacity market to the agents responsible for contingencies according to the use of the service by each market participant. This remuneration approach provides fair and efficient economic signals to all market participants. The applicability of the approach is illustrated with two case studies.

Operating reserve capacity requirements and pricing in deregulated markets using probabilistic techniques

A new probabilistic methodology to evaluate the operating reserve requirements of power systems in deregulated energy markets is presented. The main objectives are the assessment of reserve requirements for all submarkets (i.e. regulation, spinning, non-spinning and replacement), and the determination of the maximum acceptable bid prices in these submarkets and eliminating possible speculations. In order to balance reliability and costs, the proposed methodology is based on merging the loss of load cost index into the capacity bidding process for all operating reserve submarkets, thus avoiding the a priori establishment of an arbitrary risk index as a reference criterion. The results of studies using different test systems, including the IEEE-reliability test system and a configuration of the Brazilian South-Southeastern system, are presented and discussed

A generation pricing method with capacity bidding

Due to historic reasons China encounters some special difficulties in ESI (electricity system industry) restructuring. An easy and simple electricity value equivalent (es-EVE) method for day-ahead pool purchase pricing of China is therefore presented in this paper. The es-EVE method is different from two-part and one-part tariffs. It is more like the UK’s method in form, but revised for China with some new concepts and procedure. The main contributions of it include: (1) Find two kinds of eigenvalue, namely EVEs, in an optimization model, (2) Define new concepts of virtual units and feasible region, (3) Twice merit orderings are employed successively to find marginal price. They are simple maximum and minimum comparison procedures and so on. The special economic significance of the method for China is discussed, and some suggestion for ESI restructuring based on es-EVE method are provided. A case study is offered at the end of the paper.

Optimal Bidding Strategy in Spinning Reserve Market

In this paper, the problem of building the optimal bidding strategies for competitive suppliers in the California-type spinning reserve market is addressed. In this market, each supplier is required to submit a capacity bid and an energy bid simultaneously, and selection of spinning reserve suppliers is solely based on the capacity bids and the required spinning reserve amount broadcast by the independent system operator (ISO). In this procedure, the uniform market clearing price rule is employed. W inners of capacity bids may be asked to provide energy in ISO's real time dispatch according to system operation requirements, and the dispatch of energy supply is based on energy bids with application of the uniform market clearing price rule. It is assumed that each supplier bids a linear capacity supply function and a linear energy supply function into the spinning reserve market, and each supplier chooses the coeffi cients in these two supply functions to maximize benefits, subject to expectations about how rival suppliers will bid. A stochastic optimization model is first developed to describe this problem, and a genetic algorithm based method is then employed to solve it. A numerical example is utilized to illustrate the essential features of the method.

Institutional capacity and metropolitan governance: the Greater Toronto Area

Attempts to bring the administrative structures and functions of our major agglomerations into line with the new socio–economic and political realities have raised major questions concerning the governance of metropolitan regions. The ability of such areas to anticipate, respond to, and cope with the tensions induced by major urban change raise serious challenges to governmental institutions at all levels in their search for increased competitiveness and administrative efficiency, social equity and accountability, and the expression of political power. Indeed, the emergence of new institutional arenas and networks within city regions are clearly linked to wider shifts in governance, where institutional capital and diversity is central to improvements to capacity bidding strategies. Toronto's recent experience of attempting to simultaneously reorganise the structures and responsibilities of metropolitan government, the delivery of public services and the management of urban form, is thus of considerable interest, since it has long been perceived as a “model of metropolitan governance”.

A new approach to evaluate generation capacity bids

Decision making on capacity addition has become highly complex as the power industry worldwide is undergoing regulatory changes. This paper argues the use of mathematical models to aid the decision makers to select generation capacity bids. A three-stage optimization scheme is developed to accurately estimate the benefits from a specific project. A multiobjective framework to capture both quantitative as well as qualitative information (through expert judgement) has been employed. The model can be used to estimate the marginal benefit from a project and calculate a composite index to rank them in order of their desirability. A case study for modified IEEE 30-bus test system illustrates the methodological issues.

The impact of learning rate and constraints on production line performance

Learning curve theory has been an important consideration for capacity planning and bid preparation since the 1940's. Constraint theory is a relatively new approach to managing manufacturing systems. This paper examines the implications each of these theories has for the other. Several important relationships are identified using a deterministic simulation of a simple production line which is influenced by learning and the presence of a system constraint. The rate of improvement of several measures of system performance follows the learning rate, but because of the role played by the constraint, other measures of performance actually get worse.