Improvement of Sensitivity-Based Nonlinear Solver for Bidding Strategy Problem of Electricity Markets

Mallaki, Mehrdad; Naderi, Mehdi Salay; Gharehpetian, Gevork B.; Abedi, Mehrdad

doi:10.1109/icee.2018.8472691

Cited by 2 publications

(6 citation statements)

References 10 publications

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“…Generally, the sensitivity-based solvers are faced with two major issues in finding the solution of optimization problems: ① procuring a local optimal solution; ② consuming long computation time. In order to resolve these two issues, two techniques are used in this study, i.e., passing MCP and dynamic step size, which are introduced and described in detail in [22]. These techniques are briefly discussed here.…”

Section: Structure Modeling and Problem Formulationmentioning

confidence: 99%

“…In each iteration of the game, each player solves this linear minimization problem shown in (22) for several times in order to optimize its strategic factor and bidding price, as shown in Fig. 1.…”

Section: B Uncertainty In MC Of Opponents (Modeling Incomplete Information Game)mentioning

confidence: 99%

“…According to (22), Γ and ΔMC j + are effective parameters in the RO method considering the uncertainty of competitors' behavior. In this section, the sensitivity of results to these two parameters is separately analyzed.…”

Section: MC Uncertainty (Case 3)mentioning

confidence: 99%

See 2 more Smart Citations

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Mallaki

Naderi

Abedi

et al. 2021

Journal of Modern Power Systems and Clean Energy

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Developing the electricity market at the distribution level can facilitate the energy transactions in distribution networks with a high penetration level of distributed energy resources (DERs) and microgrids (MGs). However, the lack of comprehensive information about the marginal production cost of competitors leads to uncertainties in the optimal bidding strategy of participants. The electricity demand within the network and the price in the wholesale electricity market are two other sources of the uncertainties. In this paper, a day-aheadmarket-based framework for managing the energy transactions among MGs and other participants in distribution networks is introduced. A game-theory-based method is presented to model the competition and determine the optimal bidding strategy of participants in the market. Robust optimization technique is employed to capture the uncertainties in the marginal cost of competitors. Additionally, the uncertainties in demand are modeled using a scenario-based stochastic approach. The results obtained from case studies reveal the merit of considering competition modeling and uncertainties.

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Section: Structure Modeling and Problem Formulationmentioning

confidence: 99%

Section: B Uncertainty In MC Of Opponents (Modeling Incomplete Information Game)mentioning

confidence: 99%

See 1 more Smart Citation

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Mallaki

Naderi

Abedi

et al. 2021

Journal of Modern Power Systems and Clean Energy

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this scheme, real behaviors of the thermal-wind GenCos-quadratic structure-as well as the effect of techno-economic-environmental measures and day-ahead market clearing mechanism on bidding strategies are overlooked. A supply function equilibrium (SFE) model with incomplete information is used in Gong et al 11 to optimally adjust the strategic coefficient of the GenCos. In this SFE model, the competitive behavior of the GenCos is analyzed with only one strategic coefficient-the slope of the bidding curve-without taking into account technoeconomic-environmental measures.…”

Section: Background and Motivationmentioning

confidence: 99%

“…The first type of modeling deals with the unilateral generation-side bidding strategy problem within energy-only electricity markets. 6–17 In Aien and Fotuhi-Firuzabad, 6 an unscented transformation-based model is presented for the bidding strategy of the price-taker GenCos in an oligopoly market. In this simple, single-level methodology, the market-clearing mechanism is considered as uniform pricing and techno-economic-environmental measures are neglected; subsequently, in such a situation, the market competitive level and profitability are largely diminished.…”

Section: Introductionmentioning

confidence: 99%

Bilateral bidding strategy in joint day-ahead energy and reserve electricity markets considering techno-economic-environmental measures

Shivaie

Kiani-Moghaddam

Weinsier

2021

Energy & Environment

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In this study, a new bilateral equilibrium model was developed for the optimal bidding strategy of both price-taker generation companies (GenCos) and distribution companies (DisCos) that participate in a joint day-ahead energy and reserve electricity market. This model, from a new perspective, simultaneously takes into account such techno-economic-environmental measures as market power, security constraints, and environmental and loss considerations. The mathematical formulation of this new model, therefore, falls into a nonlinear, two-level optimization problem. The upper-level problem maximizes the quadratic profit functions of the GenCos and DisCos under incomplete information and passes the obtained optimal bidding strategies to the lower-level problem that clears a joint day-ahead energy and reserve electricity market. A locational marginal pricing mechanism was also considered for settling the electricity market. To solve this newly developed model, a competent multi-computational-stage, multi-dimensional, multiple-homogeneous enhanced melody search algorithm (MMM-EMSA), referred to as a symphony orchestra search algorithm (SOSA), was employed. Case studies using the IEEE 118-bus test system—a part of the American electrical power grid in the Midwestern U.S.—are provided in this paper in order to illustrate the effectiveness and capability of the model on a large-scale power grid. According to the simulation results, several conclusions can be drawn when comparing the unilateral bidding strategy: the competition among GenCos and DisCos facilitates; the improved performance of the electricity market; mitigation of the polluting atmospheric emission levels; and, the increase in total profits of the GenCos and DisCos.

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Improvement of Sensitivity-Based Nonlinear Solver for Bidding Strategy Problem of Electricity Markets

Cited by 2 publications

References 10 publications

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Bilateral bidding strategy in joint day-ahead energy and reserve electricity markets considering techno-economic-environmental measures

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