Modelling demand response aggregator behavior in wind power offering strategies

Mahmoudi, Nadali; Saha, Tapan Kumar; Eghbal, Mehdi

doi:10.1016/j.apenergy.2014.07.108

Cited by 60 publications

(23 citation statements)

References 23 publications

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“…The retailer decides about the optimal price that maximize its profit, while the consumer optimizes its consumption based on the specified price. Mahmoudi et al [17] presented bilevel programing in which a wind power producer determines its favorable price to buy DR for covering its stochastic generation and then the aggregator determines its DR involvement. The authors of [18] proposed an interesting bilevel model for implementing DR programs between retailers and customers.…”

Section: Introductionmentioning

confidence: 99%

Optimal contract pricing of load aggregators for direct load control in smart distribution systems

Shayegan-Rad¹,

Zangeneh²

2019

Turk J Elec Eng & Comp Sci

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Distribution system operators (DSOs) are interested in demand side participation programs as an efficient and secure resource to manage electricity supply and demand. However, it is usually difficult for DSOs to aggregate demand response of large/small consumers. Thus, in some electricity markets, an entity called an aggregator is defined to aggregate the load response of consumers. In this paper a bilevel scheduling model is proposed to determine the long-term optimal contract price between the DSO and aggregator for executing direct load control in smart distribution systems. The DSO and aggregator are considered as two different agents with individual objectives in the proposed bilevel scheduling model. On the one hand, the aggregator maximizes its profit by bidding load reduction of the large consumers to the DSO by executing a direct load control (DLC) mechanism, and on the other hand, the DSO tries to minimize its overall cost to supply all consumers. The DSO has two options to follow the variation of its consumers' demand:purchasing energy from the electricity market and executing DLC programs. The bilevel programming formulation is transferred into an equivalent single level programming problem using its Karush-Kuhn-Tucker optimality conditions. Moreover, the uncertainties of the electricity market price, demand of consumers, and generation of a wind power plant are modeled via point estimate method. Two typical case studies are implemented to demonstrate the effectiveness of the proposed scheduling model.

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Section: Introductionmentioning

confidence: 99%

Optimal contract pricing of load aggregators for direct load control in smart distribution systems

Shayegan-Rad¹,

Zangeneh²

2019

Turk J Elec Eng & Comp Sci

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“…[11][12][13][14][15][16] Some of these strategies exploit the equilibrium in oligopolistic markets 15 or assume a risk-constrained behavior. 16 Although not the goal of this work, interested readers on optimal coordination between wind and other energy resources such as CHP, 17 hydro, 18 demand response, 19,20 among others 21,22 are referred.…”

Section: Introductionmentioning

confidence: 99%

Optimal offering and allocation policies for wind power in energy and reserve markets

et al. 2017

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Proliferation of wind power generation is increasingly making this power source an important asset in designs of energy and reserve markets. Intuitively, wind power producers will require the development of new offering strategies that maximize the expected profit in both energy and reserve markets while fulfilling the market rules and its operational limits. In this paper, we implement and exploit the controllability of the proportional control strategy. This strategy allows the splitting of potentially available wind power generation in energy and reserve markets. In addition, we take advantage of better forecast information from the different day‐ahead and balancing stages, allowing different shares of energy and reserve in both stages. Under these assumptions, different mathematical methods able to deal with the uncertain nature of wind power generation, namely, stochastic programming, with McCormick relaxation and piecewise linear decision rules are adapted and tested aiming to maximize the expected revenue for participating in both energy and reserve markets, while accounting for estimated balancing costs for failing to provide energy and reserve. A set of numerical examples, as well as a case study based on real data, allow the analysis and evaluation of the performance and behavior of such techniques. An important conclusion is that the use of the proposed approaches offers a degree of freedom in terms of minimizing balancing costs for the wind power producer strategically to participate in both energy and reserve markets. Copyright © 2017 John Wiley & Sons, Ltd.

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“…At day-ahead stage, in regard to DR resources participating in both energy and reserve scheduling, a robust model is given in [38] to schedule smart distribution network to immunize uncertainties. Aiming to mitigate the impact of wind power variability, an agent-based modeling framework is used to represent hierarchical power systems [39], and a DR aggregator is employed by a wind power producer to make offering strategies [40]. In view of control schemes, thermostatic loads are aggregated to manage frequency and energy imbalances in power systems [41].…”

Section: Introductionmentioning

confidence: 99%

Strategy-making for a proactive distribution company in the real-time market with demand response

Zhang

Wang

et al. 2016

Applied Energy

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This paper proposes a methodology to optimize the trading strategies of a proactive distribution company (PDISCO) in the real-time market by mobilizing the demand response. Each distribution-level demand is considered as an elastic one. To capture the interrelation between the PDISCO and the real-time market, a bi-level model is presented for the PDISCO to render continuous offers and bids strategically. The upper-level problem expresses the PDISCO's profit maximization, while the lower-level problem minimizes the operation cost of the transmission-level real-time market. To solve the proposed model, a primal-dual approach is used to translate this bi-level model into a single-level mathematical program with equilibrium constraints. Results of case studies are reported to show the effectiveness of the proposed model.

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Modelling demand response aggregator behavior in wind power offering strategies

Cited by 60 publications

References 23 publications

Optimal contract pricing of load aggregators for direct load control in smart distribution systems

Optimal contract pricing of load aggregators for direct load control in smart distribution systems

Optimal offering and allocation policies for wind power in energy and reserve markets

Strategy-making for a proactive distribution company in the real-time market with demand response

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