Investigating the Ability of Demand Shifting to Mitigate Electricity Producers’ Market Power

Abstract

Lagrangian multipliers associated with the capacity constraints of transmission line (,) (£/MW) , − , , + Lagrangian multipliers associated with the voltage angle constraints at node and period (£/rad) Lagrangian multiplier associated with the voltage angle value at the reference node (£/rad)

Incorporating Non-Convex Operating Characteristics Into Bi-Level Optimization Electricity Market Models

“…3) As discussed in Section I-B, the examined market problem lies in the optimization of the strategic bidding decisions of a single producer i. Following the model employed in [3], [4], [6], [17], [20] the strategic behavior of producer i is expressed through a decision variable 1 ≤ k i ≤ k max i . If k i = 1, producer i behaves competitively and offers its actual marginal costs λ G i,b , ∀b to the market.…”

“…Going further, state-of-the-art bi-level optimization models presented in [2]- [17], [20] investigate the ability of strategic producers to misreport their variable costs (which also applies to the formulation and the previous case studies of this paper), while few of them explore the ability to misreport their maximum generation limits or ramp rates [7], [14], [16]. Since the proposed model enables incorporation of nonconvex operating characteristics, it allows investigating a very interesting aspect that cannot be explored with state-of-theart models: can strategic producers exercise market power and strategically increase their profits by misreporting non-convex cost components or constraints?…”

“…This popularity is justified by the large number of papers employing this methodology, including papers [2]- [25]. This list includes papers focusing on market models including only traditional generation participants [2]- [16] as well as models investigating the impact of demand side flexibility [17]- [20] and energy storage [21]- [25] in electricity markets. Furthermore, some of these papers focus on the optimization of the strategic bidding decisions of a single market player [5], [8], [9], [12], [15], [16], [18], [19], [21]- [25], while others have gone further, aiming at identifying the market equilibria stemming from the interactions of multiple players [2]- [4], [6], [7], [10], [11], [13], [14], [17], [20].…”

“…This list includes papers focusing on market models including only traditional generation participants [2]- [16] as well as models investigating the impact of demand side flexibility [17]- [20] and energy storage [21]- [25] in electricity markets. Furthermore, some of these papers focus on the optimization of the strategic bidding decisions of a single market player [5], [8], [9], [12], [15], [16], [18], [19], [21]- [25], while others have gone further, aiming at identifying the market equilibria stemming from the interactions of multiple players [2]- [4], [6], [7], [10], [11], [13], [14], [17], [20]. Finally, some of these papers have managed to incorporate realistic aspects such as network constraints [2]- [6], [9], [11], [12], [14]- [18], [20]- [25], and uncertainty faced by market players [5], [8]- [10], [12]- [16], [18], [19], [24], [25] in the developed market models.…”

Locational marginal price share: a new structural market power index

“…The market power indices may be quantity-based [7] such as Herfindahl-Hirschman index (HHI), pivotal supplier index (PSI) and residual supply index (RSI), and price-based such as output gap and Lerner index (LI) [8]. GenCos owning a great share of the market or locating at the strategic bus of the network are able to exercise market power through strategic behavior [9]. This action can be applied in two ways: capacity withholding (i.e., decreasing the power lower than the available capacity) and financial withholding (i.e., raising the bid price higher than the marginal cost).…”