Developing Bidding and Offering Curves of a Price-Maker Energy Storage Facility Based on Robust Optimization

Shafiee, Soroush; Zareipour, Hamidreza; Knight, Andrew M.

doi:10.1109/tsg.2017.2749437

Cited by 54 publications

(20 citation statements)

References 30 publications

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“…A large number of previous papers [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] have modelled price-making ESSs and quantitatively analysed their ability to exercise market power. However, the modelling approaches adopted in these works exhibit certain limitations.…”

Section: Background and Motivationmentioning

confidence: 99%

“…, producer i behaves as a price-maker and submits an offer price higher than its actual marginal costs (v i, t λ i, b G , ∀b) to the market at t. v. Each demand participant j submits a decreasing stepwise bid curve (capturing the effect of demand's price elasticity [17,19,20,27,34]) to the market at every period t, consisting of a number of blocks c. The price/quantity bids are time-specific and location-specific parameters, capturing the differentiated preferences of consumers across different time periods and the differentiated geographical conditions. Demand participants are assumed price-takers, bidding based on their actual technoeconomic parameters.…”

Section: Modelling Assumptionsmentioning

confidence: 99%

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Investigating the impacts of price‐taking and price‐making energy storage in electricity markets through an equilibrium programming model

Papadaskalopoulos

Moreira

et al. 2018

IET Generation, Transmission & Distribution

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The envisaged decarbonisation of electricity systems has attracted significant interest around the role and value of energy storage systems (ESSs). In the deregulated electricity market, there is a need to investigate the complex impacts of ESSs, considering the potential exercise of market power by strategic players. This study aims at comprehensively analysing the impacts of both price-taking and price-making storage behaviours on energy market efficiency, corresponding to potential settings with small and large storage players, respectively. In order to achieve this and in contrast to previous papers, this work develops a multi-period equilibrium programming market model to determine market equilibrium stemming from the interactions of independent strategic producers and ESSs, while capturing the time-coupling operational constraints of ESSs as well as network constraints. The results of case studies on a test market capturing the general conditions of the GB electricity system demonstrate that the introduction of ESSs mitigates market power exercise and improves market efficiency, with this beneficial impact being higher when ESSs act as price takers. When the electricity network is congested, the location of ESSs also affects the market outcome, with their beneficial impact on market efficiency being higher when they are located in higher-priced areas. − , χ n, m, t + dual variables of constraints (13) (£/MW) ψ n, t − , ψ n, t + dual variables of constraints (14) (£/rad) δ t dual variables of constraints (15) (£/rad) IET Gener. Transm. Distrib.

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Section: Background and Motivationmentioning

confidence: 99%

Section: Modelling Assumptionsmentioning

confidence: 99%

Investigating the impacts of price‐taking and price‐making energy storage in electricity markets through an equilibrium programming model

Papadaskalopoulos

Moreira

et al. 2018

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

show abstract

“…Concerning the solving algorithm, the bi-level optimization model is usually reduced to a mixed-integer linear programming problem using the duality theory and the Karush-Kuhn-Tucker optimality conditions, or through mathematical program equilibrium constraints (MPEC). MPEC approach often imposes a high computational burden due to its complicated mathematical formulation, which makes it challenging to solve for large-scale systems [22]. Focus on the monthly energy market in China, [12] presents a bi-level optimization model for developing optimal bidding strategies of power producer in the monthly sequential contract and balancing markets.…”

Section: Introductionmentioning

confidence: 99%

“…PQC describes how the market-clearing price changes as the quota of the price maker changes. PQC is at the beginning used for bidding optimization of the generators [3,6,7], and now is also used for demand-side bidding [15,22]. To distinguish the PQCs for generators and demand-side retailers, they are named generation PQC (GPQC) and demand PQC (DPQC), respectively [16].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Bidding of Price-Maker Retailers With Demand Price Quota Curves Under Price Uncertainty

Wang

Zhang

et al. 2020

IEEE Access

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This paper proposes an optimal bidding method of price-maker retailers in the electricity market with demand price quota curves (DPQC)-based probability distribution function (PDF) estimation of the market price. Different from traditional game-theory methods or agent-based methods, the proposed DPQC-based PDF estimation method unnecessity to have full knowledge of the strategies of each rival or the market operation. In detail, the DPQC method is applied to consider the impacts of the market clearing price from the price-maker retailers themselves, and the PDF model is utilized to consider the market price uncertainty. The technical key point of the proposed method is to amend the PDF along with the PQCs dynamically. Moreover, the DPQC-based PDF estimation with one-segment and multi-segment bidding rules are presented, respectively. The optimization model of the bidding problem is formulated then, and we use the genetic algorithm to solve it. The case study shows that the proposed method can help the price-maker retailers better to consider the price impacts from their bidding behaviors, and enable them to make a higher profit in the electricity market. INDEX TERMS Demand price quota curve (DPQC), optimal bidding, price-maker, power market.

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Bidding strategy of hybrid power plant in day‐ahead market as price maker through robust optimization

Darvishi

Sheisi

Aghaei

2020

Int Trans Electr Energ Syst

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Developing Bidding and Offering Curves of a Price-Maker Energy Storage Facility Based on Robust Optimization

Cited by 54 publications

References 30 publications

Investigating the impacts of price‐taking and price‐making energy storage in electricity markets through an equilibrium programming model

Investigating the impacts of price‐taking and price‐making energy storage in electricity markets through an equilibrium programming model

Optimal Bidding of Price-Maker Retailers With Demand Price Quota Curves Under Price Uncertainty

Bidding strategy of hybrid power plant in day‐ahead market as price maker through robust optimization

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