Strategic bidding of an energy storage agent in a joint energy and reserve market under stochastic generation

Dimitriadis, Christos N.; Tsimopoulos, Evangelos G.; Georgiadis, Michael C.

doi:10.1016/j.energy.2021.123026

Cited by 39 publications

(5 citation statements)

References 34 publications

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“…Constraint (16) shows that the upward reserve capacity that the aggregator can provide is the sum of the upward reserve capacities of electricity producing devices, including PV, GT, SE, and the downward reserve capacities of electricity consuming devices, including electricity demand (DE). Constraint (17) shows that the downward reserve capacity that the aggregator can provide is the sum of the downward reserve capacities of PV, GT and SE. Only demand curtailment is considered in this paper, and thus demand management can only provide downward reserve which contributes to the upward reserve of the aggregator.…”

Section: Day-ahead Stage Constraints Of the Aggregatormentioning

confidence: 99%

“…The two stages are defined as "here-and-now" stage (first stage or day-ahead stage), and "wait-and-see" stage (second stage or real-time stage). The energy storage agent in [17] makes a strategic bidding decision as a price maker in energy and reserve markets under wind power generation uncertainty. The energy and reserve markets clear jointly in the first stage, and a real-time balancing market is considered after the realization of the uncertainty in the second stage.…”

Section: Introductionmentioning

confidence: 99%

“…References [14][15][16] consider the energy and reserve markets, although only in the day-ahead stage while neglecting the profit/cost in the real-time stage from the deviation of energy schedule and the reserve deployment used to balance the power system. References [11,17] consider both day-ahead and real-time market stages. However, at the real-time stage, they do not differentiate the remunerations for real-time energy service and for reserve deployment.…”

Section: Introductionmentioning

confidence: 99%

“…In [14,15], only charging and discharging power limits are considered for the reserve schedule of the electric energy storage (SE), while the SOC limit is modeled only for the energy schedule. References [16,17] neglect the ramping limit of the reserve schedule of the natural gas turbine (GT). Therefore, the reserve schedules in existing work can be unreasonable.…”

Section: Introductionmentioning

confidence: 99%

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Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets

Wang,

Xie,

Huang

et al. 2023

Prot Control Mod Power Syst

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This paper addresses a two-stage stochastic-robust model for the day-ahead self-scheduling problem of an aggregator considering uncertainties. The aggregator, which integrates power and capacity of small-scale prosumers and flexible community-owned devices, trades electric energy in the day-ahead (DAM) and real-time energy markets (RTM), and trades reserve capacity and deployment in the reserve capacity (RCM) and reserve deployment markets (RDM). The ability of the aggregator providing reserve service is constrained by the regulations of reserve market rules, including minimum offer/bid size and minimum delivery duration. A combination approach of stochastic programming (SP) and robust optimization (RO) is used to model different kinds of uncertainties, including those of market price, power/demand and reserve deployment. The risk management of the aggregator is considered through conditional value at risk (CVaR) and fluctuation intervals of the uncertain parameters. Case studies numerically show the economic revenue and the energy-reserve schedule of the aggregator with participation in different markets, reserve regulations, and risk preferences.

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Section: Day-ahead Stage Constraints Of the Aggregatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets

Wang,

Xie,

Huang

et al. 2023

Prot Control Mod Power Syst

View full text Add to dashboard Cite

show abstract

“…A non-cooperative game theoretic model was implemented in [23] to obtain the market equilibrium for P2P market participants embedded with shared energy storage units. On the other hand, a strategic bidding model was adopted in [24] for individual energy storage units considering uncertainties in wind power generation.…”

Section: Introductionmentioning

confidence: 99%

A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies

Islam

2024

Energies

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This paper presents a detailed review of the existing literature on peer-to-peer (P2P) energy trading considering market architectures, trading strategies, and enabling technologies. P2P energy trading enables individual users in the electricity network to act as sellers or buyers and trade energy among each other. To facilitate the discussion on different aspects of P2P energy trading, this paper focuses on P2P market mechanisms, relevant bidding strategies, and auction models. In addition, to solve the energy management problems associated with P2P energy trading, this paper investigates widely used solution methods such as game-theoretic models, mathematical optimisation, as well as more recent machine learning techniques and evaluates them in a critical manner. The outcomes of this investigation along with the identification of the challenges and limitations will allow researchers to find suitable P2P energy trading mechanisms based on different market contexts. Moreover, the discussions on potential future research directions are expected to improve the effectiveness of P2P energy trading technologies.

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Strategic participation of a gas-fired power plant in interdependent electricity and natural gas markets under carbon emission trading schemes

Dimitriadis

Tsimopoulos

Georgiadis

2023

Computer Aided Chemical Engineering

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Strategic bidding of an energy storage agent in a joint energy and reserve market under stochastic generation

Cited by 39 publications

References 34 publications

Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets

Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets

A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies

Strategic participation of a gas-fired power plant in interdependent electricity and natural gas markets under carbon emission trading schemes

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