Stochastic security for operations planning with significant wind power generation

Bouffard, François; Galiana, F.D.

doi:10.1109/pes.2008.4596307

Cited by 134 publications

(96 citation statements)

References 27 publications

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“…To clear the forward market using stochastic programming (Birge & Louveaux, 2011), which allows modeling future balancing needs and costs in a probabilistic framework, thus yielding the day-ahead energy dispatch that minimizes the expected system operating costs. One of the major advantages of this approach is that it endogenously solves for the optimal amount of reserve capacity to be left to the balancing market, weighing the expected costs and benefits of such capacity Bouffard & Galiana, 2008;Morales et al, 2009;Papavasiliou et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Electricity market clearing with improved scheduling of stochastic production

Morales

Zugno

Pineda

2014

European Journal of Operational Research

105

122

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In this paper, we consider an electricity market that consists of a day-ahead and a balancing settlement, and includes a number of stochastic producers. We first introduce two reference procedures for scheduling and pricing energy in the day-ahead market: on the one hand, a conventional network-constrained auction purely based on the least-cost merit order, where stochastic generation enters with its expected production and a low marginal cost; on the other, a counterfactual auction that also accounts for the projected balancing costs using stochastic programming. Although the stochastic clearing procedure attains higher market efficiency in expectation than the conventional day-ahead auction, it suffers from fundamental drawbacks with a view to its practical implementation. In particular, it requires flexible producers (those that make up for the lack or surplus of stochastic generation) to accept losses in some scenarios. Using a bilevel programming framework, we then show that the conventional auction, if combined with a suitable day-ahead dispatch of stochastic producers (generally different from their expected production), can substantially increase market efficiency and emulate the advantageous features of the stochastic optimization ideal, while avoiding its major pitfalls.A two-node power system serves as both an illustrative example and a proof of concept. Finally, a more realistic case study highlights the main advantages of a smart day-ahead dispatch of stochastic producers.Dear Editor of European Journal of Operational Research, Today's electricity market design is the result of adapting traditional practices, such as unit commitment, economic dispatch or contingency analysis, to a competitive structure. These practices were conceived in view of a generation mix mostly formed by dispatchable power plants, and are now to be revisited so that stochastic producers can enter the competition in a fair and efficient manner.In this line, researchers have recently advocated a market-clearing mechanism that co-optimizes the forward (day-ahead) and the anticipated real-time energy dispatches using stochastic programming. Even though, ideally, this mechanism attains maximum market efficiency, it results in an energy-only market settlement that requires flexible producers to accept economic losses for some realizations of the stochastic production, which raises concerns on its practical applicability.Starting from this point, this paper shows that, if stochastic production is conveniently scheduled in the day-ahead market, the conventional settlement of this market can notably approach the behavior of the stochastic ideal, while sidestepping its theoretical drawbacks. To this end, we construct a bilevel programming formulation that determines the optimal value of stochastic production that should be considered to clear the day-ahead market under the conventional settlement.We firmly believe that this research work could positively contribute to your Journal. We thank you in advance for considering this...

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Section: Introductionmentioning

confidence: 99%

Electricity market clearing with improved scheduling of stochastic production

Morales

Zugno

Pineda

2014

European Journal of Operational Research

105

122

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“…The bidding strategy in the spot market is exclusively studied in [5][6][7][8][9], that is out of the scope of this paper. The DA market clearing prices is illustrated in Figure 1.…”

Section: Day-ahead Marketmentioning

confidence: 99%

“…The objective in this case is to maximize the profit that WPP can obtain from the RT market. The term of BES cost is rejected from (8). The problem constraints remain the same in (10) and (11).…”

Section: Case 1: Without Bes Cost Considerationmentioning

confidence: 99%

“…Then, the optimal charging/discharging of BES is to maximize the overall profit (i.e., the income after subtracting the BES cost) as in (8). This results in the optimal dispatch (p RT [k]), state of charge (SoC[k]) of BES in Figures 7(a,b), respectively.…”

Section: Case 2: With Bes Cost Considerationmentioning

confidence: 99%

“…Secondly, the bidding approach attempts to optimize the bidding strategy of WPPs in the spot market [5][6][7][8][9]. This strategy takes into account both the asymmetry of regulation prices (up and down regulation) and the availability of the probabilistic error of prediction tools.…”

Section: Introductionmentioning

confidence: 99%

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A New Battery Energy Storage Charging/Discharging Scheme for Wind Power Producers in Real-Time Markets

Nguyen

Yoon

2012

Energies

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Under a deregulated environment, wind power producers are subject to many regulation costs due to the intermittence of natural resources and the accuracy limits of existing prediction tools. This paper addresses the operation (charging/discharging) problem of battery energy storage installed in a wind generation system in order to improve the value of wind power in the real-time market. Depending on the prediction of market prices and the probabilistic information of wind generation, wind power producers can schedule the battery energy storage for the next day in order to maximize the profit. In addition, by taking into account the expenses of using batteries, the proposed charging/discharging scheme is able to avoid the detrimental operation of battery energy storage which can lead to a significant reduction of battery lifetime, i.e., uneconomical operation. The problem is formulated in a dynamic programming framework and solved by a dynamic programming backward algorithm. The proposed scheme is then applied to the study cases, and the results of simulation show its effectiveness.

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Operation optimization of integrated energy systems based on heat storage characteristics of heating network

Pan

Wang

et al. 2020

Energy Science & Engineering

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With the development of multi‐energy technology, the electric‐heat integrated energy system has become an important research direction for multi‐energy joint supply. The dynamic characteristics and energy storage capacity of heat supply network provide potential for joint dispatching of electric heating energy system. Aiming at the problem of electric‐heat joint dispatching, this paper presents an operation optimization model of electric‐heat integrated energy system considering the virtual energy storage characteristics of heat supply network. Firstly, according to the characteristics of transmission delay and user temperature fuzzy, the virtual energy storage characteristics of heat supply network are studied, and a model of the dynamic transfer of energy in the heat system was built. Then, the operation optimization model of the electric‐heat integrated energy system is established to minimize the operation cost. In order to improve the robustness of scheduling optimization results, the Monte Carlo Simulation embedded Quantum Particle Swarm Optimization algorithm is proposed to solve the model. In order to prove the validity of the proposed model, this paper selects a park (a 36 node thermal system) in the northwest region of China as a simulation case. The results show that the operation optimization method considering the virtual energy storage of heat supply network will greatly enhance the complementary potential of the electric‐heat integrated energy system and reduce the operation cost of the system.

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Stochastic security for operations planning with significant wind power generation

Cited by 134 publications

References 27 publications

Electricity market clearing with improved scheduling of stochastic production

Electricity market clearing with improved scheduling of stochastic production

A New Battery Energy Storage Charging/Discharging Scheme for Wind Power Producers in Real-Time Markets

Operation optimization of integrated energy systems based on heat storage characteristics of heating network

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