Transmission-constrained Electricity Market Research Articles

Behavioural market power indices in a transmission‐constrained electricity market

This study proposes new behavioural indices of market power (MP) in order to analyse bidding behaviour of units in a transmission-constrained electricity market. The indices calculate actual MP exercised by generators of the market. The proposed indices check whether a generator exerts an influence on the wholesale price and it is able to change the price at studied trading period. If the generator is capable of raising the wholesale price, the proposed indices calculate exact values for the generator's withholding. The first proposed index measures financial withholding exercised by marginal generators and the second one calculates physical withholding of players taking into account the impact of withdrawal of output on the wholesale price. The proposed indices are quantified for modified PJM 5-bus system and compared with the former behavioural indices to verify their accuracy. In addition, modified IEEE 30-bus system is considered to clarify the transparent applications of the indices for more complicated system.

A Unifying Market Power Measure for Deregulated Transmission-Constrained Electricity Markets

Market power assessment is a prime concern when designing a deregulated electricity market. In this paper, we propose a new functional market power measure, termed transmission constrained network flow (TCNF), that unifies three large classes of transmission constrained structural market power indices in the literature: residual supply based, network flow based, and minimal generation based. Furthermore, it is suitable for demand-response and renewable integration and hence more amenable to identifying market power in the future smart grid. The measure is defined abstractly, and allows incorporation of power flow equations in multiple ways; we investigate the current market operations using a DC approximation and further explore the possibility of including detailed AC power flow models through semidefinite relaxation, and interior-point algorithms from Matpower. Finally, we provide extensive simulations on IEEE benchmark systems and highlight the complex interaction of engineering constraints with market power assessment.

A Novel Bus-Aggregation-Based Structure-Preserving Power System Equivalent

The challenges power systems engineers are facing today require the development of new system planning tools for analyzing generation and environmental policy options in the transmission-constrained electricity market. The requirements of a power-system equivalent to be used with such tools are very different from those assumed in the traditional network reduction process. To solve this issue, a novel structure-preserving network equivalent is proposed in this paper for modeling large power systems in the context of analyzing policy options and emissions. In the proposed method, a power system is first clustered into zones based on the similarity of the power transfer distribution factors (PTDFs); network reduction is achieved by aggregating buses (generators/loads) on a zonal basis and modeling inter-zonal transactions (power flows) using equivalent transmission lines. The proposed equivalent is superior to existing bus-aggregation-based equivalents in its accuracy under both the base case and change-case operating conditions. In addition, the method is more computationally efficient than other bus aggregation methods proposed heretofore. This paper also examined several classic clustering techniques and identified their performance and computational efficiencies when applied to very large power systems. The proposed network equivalencing approach is tested on an illustrative six-bus system as well as the 62,000-bus and 80,000-branch Eastern Interconnection (EI).

Optimal Strategies for Multiple Participants in Electricity Markets

This letter presents the solution framework for calculating multi-participant Nash equilibria in a transmission-constrained electricity market. The proposed framework, which is generally applicable to various gaming conditions in electricity markets, is used here for non-cooperative complete information game between market participants with discrete bidding strategies. The example in this letter shows the effectiveness of the proposed framework in finding the Nash equilibrium.

Firm-Based Measurements of Market Power in Transmission-Constrained Electricity Markets

In this paper, two different approaches to analyzing firm-based market power considering transmission constraints are proposed. One is an application of the transmission-constrained residual demand Jacobian, while the other is a generalization of the “residual supply index” to the case of transmission constraints. These two approaches provide complementary evaluations of market power. Medium- and large-scale system examples are provided to demonstrate computational efficiency, and both approaches could be applied to real-world electricity markets.

Zonal Supply Curve Estimation in Transmission-Constrained Electricity Markets

Electricity system operations are often affected by energy policies, but spatial differences in policy impacts are difficult to model. We develop a method for estimating zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods (not necessarily engineering) and with publicly-available data. Our nonlinear statistical model uses fuel prices and zonal electric loads to determine piecewise supply curves, each segment of which represents the influence of a particular fuel type on the zonal electricity price. Our problem thus requires the simultaneous estimation of the slope of each supply-curve segment, as well as the thresholds defining the endpoints of each segment. We illustrate our methodology by estimating zonal supply curves for the utility zones in the PJM electricity grid. We use our supply curves to estimate regional impacts of a policy initiative in the state of Pennsylvania that requires utilities to reduce annual and peak electric load. For most utilities in Pennsylvania, it would reduce the influence of natural gas on electricity price formation and increase the influence of coal. We also find that the policy reduces electricity prices in most other regions, although the impacts are not uniform across regions.

New Indices of Market Power in Transmission-Constrained Electricity Markets

In this paper, we introduce four new indices of market power in transmission-constrained electricity markets that are based on economic principles together with faithful representation of the effects of Kirchhoff's laws.

Does a regional greenhouse gas policy make sense? A case study of carbon leakage and emissions spillover

The Regional Greenhouse Gas Initiative (RGGI) is a state-level effort by ten northeast states in the U.S. to control CO 2 emissions from the electric sector. The approach adopted by RGGI is a regional cap-and-trade program, which sets a maximal annual amount of regional CO 2 emissions that can be emitted from the electric sector. However, incoherence of the geographic scope of the regional electricity market is expected to produce two undesirable consequences: CO 2 leakage and NO x and SO 2 emissions spillover. This paper addresses these two issues using transmission-constrained electricity market models. The results show that although larger CO 2 leakage is associated with higher allowance prices, it is negatively related to CO 2 prices if measured in percentage terms. On the other hand, SO 2 and NO x emissions spillover increase in commensurate with CO 2 allowance prices. Demand elasticity attenuates the effect of emissions trading on leakage and emissions spillover. This highlights the difficulties of designing a regional or local climate policy.

Hybrid Coevolutionary Programming for Nash Equilibrium Search in Games With Local Optima

The conventional local optimization path and coevolutionary processes are studied when "local Nash equilibrium (NE) traps" exist. Conventional NE search algorithms in games with local optima can misidentify NE by following a local optimization path. We prove that any iterative NE search algorithms based on local optimization cannot differentiate real NE and "local NE traps". Coevolutionary programming, a parallel and global search algorithm, is applied to overcome this problem. In order to enhance the poor convergence of simple coevolutionary programming, hybrid coevolutionary programming is suggested. The conventional NE algorithms, simple coevolutionary programming, and hybrid coevolutionary algorithms are tested through a simple numerical example and transmission-constrained electricity market examples.