بهره وری اقتصادی از ادغام کردن بازارهای برق هماهنگ شده

This paper presents economic efficiency evaluation of pool coordinated electricity markets. The evaluation accounts for the overall cost of power generation, network losses and costs, and various operational constraints. We assume a non-collusive oligopolistic competition. An iterative supply function model is used to characterize the competitive behavior of suppliers. A social welfare function is defined for PoolCo market that operates over multiple hours time span. This leads to a mixed-integer non-linear programming problem. An Augmented Lagrangian approach is used to solve iteratively for global optimal operation schedules (i.e. power generation, load, and price for each bus node) while considering constraints of different sorts. An IEEE 24-bus, eight-supplier, 17-customer test system is used for illustration. The results show deflection of electricity prices from the marginal costs of power generation. The results of 2-year (730 round) market simulations show a range of deadweight efficiency loss between 0.5

Electric power industries in the US and abroad are moving toward an era of restructuring. A general trend in many countries (e.g. New England, Chile, Argentina) is to have a mandatory power pool. This is referred to as PoolCo. The pool centrally schedules generators based on their bidding strategies to meet consumer requirements. It determines market-clearing prices, operates and controls the entire system, and maintains reliability. Much current research is concerned with the general behavior of electricity spot markets. Various references (e.g. [15], [22] and [23]) critically analyzed PoolCo structure advocated by Ref. [12]. Ref. [16] presents analyses for estimating prices of a pure PoolCo market with identical profit-maximizing generating firms. The results of the analysis give different measures of the price–cost margin index (PCMI) as a function of the number of identical firms, the level of capacity non-availability, and the accuracy of demand forecasts. The authors of Refs. [8], [9] and [10] analyzed the UK electricity market using a supply function equilibria (SFE) model. The model gives competitive behavior of suppliers in meeting time-varying demands. The work was first developed in Ref. [14], for studying suppliers' competitive behavior under uncertain demand. For the purpose of characterizing the market behavior at the industry level, the UK market was modeled as a duopoly market, thus the work closely follows Klemperer and Meyer's formulation and conclusion for a homogeneous product. Green et al.'s study shows a range of equilibrium supply schedules for symmetric duopolists. Assuming no capacity constraints, it was concluded that no asymmetric SFE exist and that the market behavior characterized at the industry level differs very little between symmetric and asymmetric duopolistic markets. The SFE model has been extended in Ref. [5] to account for a competitive fringe and several strategic players. The results show that a piece-wise affine SFE exists for linear demand and non-negative generation limits, under the assumption that bidders submit either affine supply functions or piece-wise supply function with relatively small pieces. The assumption of bidders submitting a supply function with small number of pieces has been relaxed in Ref. [6]. The authors analyze the properties of the equilibrium and numerically estimate candidate equilibrium supply functions by iterating in the function space of allowable bids. Refs. [7], [11], [17], [18] and [20] have also applied the SFE model to analyze the electricity market under different assumptions and with different successes. Based on such modeling aspects, one can easily obtain an estimate of the deadweight efficiency loss as a standard for evaluating economic efficiency, or an estimate of the PCMI as a measure of the exercise of market power. It has been argued in Ref. [4] that the Herfindhal–Hirschman index and PCMI measures of market power are fixed and do not capture market variations. The models of market analyses so far, either consider competition at the industrial level [8], [9] and [10], or competition among identical generating firms [16]. Furthermore, these analyses do not account for the competitive behavior of individual diverse generation resources, network losses and costs, and the various system and unit operational constraints. All these have major impacts on the economic efficiency of such markets. In Ref. [4], the economic efficiency evaluation has been presented in electricity markets operating on the basis of a coordinated multilateral trading concept. In this paper, we present an evaluation approach of PoolCo-based electricity markets. The evaluation accounts for the overall cost of power generation, network losses and costs, and various operational constraints. We assume a non-collusive oligopolistic competition. A social welfare function is defined for PoolCo market that operates over multiple hours time span. This leads to a mixed-integer non-linear programming problem. The Augmented Lagrangian approach presented in Refs. [2] and [3] is used to solve iteratively for global optimal operation schedules (i.e. dispatch of resources and system loads and determination of hourly market-clearing prices) while considering constraints of different sorts. The references mainly present the main results of the approach and associated computational procedures for solving the hydrothermal scheduling problem. The paper is organized as follows: Section 2 defines an energy marketplace. An evaluation modeling framework is introduced in Section 3. Section 4 presents results of a test case. The paper is concluded in Section 5.

The modeling framework presented in this work provides a basis for evaluating the economic efficiency of pool coordinated electricity markets. The framework considers competitive behavior of individual units, overall costs of power generation, network losses and costs, system operational constraints and behavioral variations of different classes of consumers. Results of the IEEE test system show deflection of electricity prices from the marginal costs of power generation on an average of 12% PCMI and a 2.6% deadweight efficiency loss. These results contrasts largely with the results of Ref. [16] which show an average PCMI of 11% in a market with 10 identical firms. Note that a 12% PCMI in our case is a result of a market with 26 competing diverse units. This indicates that competition at the generation resource level, network losses and costs, and unit and system constraints have major impacts on the economic efficiency and the exercise of market power in PoolCo markets. As a matter of fact, the numerical results of this paper could vary significantly from one system to another. Variations are impacted by the system characteristics, such as network topology and associated loading capabilities and the number and capacities of competing units. The results of 2 years (730) market simulations show a range of deadweight efficiency loss between 0.5 and 10% compared to that of Multilateral Coordinated Market which results in a range between 0.9 and 6% for the same test cases, [1] (Proposition 1 ([19]), Proposition 2 ([1]) and Proposition 3 ([1])).