Scheduling and Pricing of Coupled Energy and Primary, Secondary, and Tertiary Reserves

Galiana, F.D.; Bouffard, François; Arroyo, José M.; Restrepo, José Félix

doi:10.1109/jproc.2005.857492

Cited by 275 publications

(186 citation statements)

References 34 publications

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“…For its practical application within a market environment, though, it must be first complemented with a set of prices and payments that make market participants satisfied with the resulting day-ahead dispatch. In this vein, Galiana et al (2005) andFuller (2007) define prices for both energy and reserve capacity. However, determining who should pay for such reserve and to which extent is still a 3 major source of conflict and debate (Hogan, 2005).…”

Section: Introductionmentioning

confidence: 99%

Electricity market clearing with improved scheduling of stochastic production

Morales

Zugno

Pineda

2014

European Journal of Operational Research

107

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

107

122

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“…[15] However, in Europe, UCTE defines operating reserves in three categories: primary, secondary and tertiary control reserves. [2,13] This approach address operating reserves services from the point of view of their time of deployment following the occurrence of a contingency as well as the corresponding control strategies behind their deployment. [11] During the primary regulation interval, generators automatically adjust to disturbances as their speed governors respond to deviations from the nominal system frequency through their droop characteristics.…”

Section: Classification and Definition Of Operating Reservesmentioning

confidence: 99%

“…[11] During the primary regulation interval, generators automatically adjust to disturbances as their speed governors respond to deviations from the nominal system frequency through their droop characteristics. [13] In the secondary regulation called AGC, generators automatically vary their generation set points proportionally to some participation factors with the goal of nullifying the area control error in following normal load variations. Finally, during the tertiary regulation interval, typically with time constants exceeding 10 min, a variation of the predisturbance set points is scheduled for each credible contingency within the prescribed generation, demand, and transmission flow limits, while ensuring that the area control error is zero and that power balances at every bus.…”

Section: Classification and Definition Of Operating Reservesmentioning

confidence: 99%

A New Required Reserve Capacity Determining Scheme with Regard to Real time Load Imbalance

Park¹,

Kim²,

Yoon³

2015

Journal of Electrical Engineering and Technology

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-Determination of the required reserve capacity has an important function in operation of power system and it is calculated based on the largest loss of supply. However, conventional method cannot be applied in future power system, because potential grid-connected distributed generator and abnormal temperature cause the large load imbalance. Therefore this paper address new framework for determining the optimal required reserve capacity taking into account the real time load imbalance. At first, we introduce the way of operating reserve resources which are the secondary, tertiary, Direct Load Control (DLC) and Load shedding reserves to make up the load imbalance. Then, the formulated problem can be solved by the Probabilistic Dynamic Programming (PDP) method. In case study, we divide two cases for comparing the cost function between the conventional method and the proposed method.

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“…These are called frequency control reserves (FCRs) as an essential part of ancillary services (AS), consist of primary control reserve, secondary control reserve and tertiary control reserve based on a framework in Union for the Co-ordination of Transmission of Electricity (UCTE), which is the major portion of the European Network of Transmission System Operators for Electricity (ENTSO-E). These reserve services are generally procured through a market mechanism [1,[4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Determination of Secondary Reserve Requirement Through Interaction-dependent Clearance Between Ex-ante and Ex-post

Kim¹,

Park²,

Yoon³

2014

Journal of Electrical Engineering and Technology

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-This paper discusses a method for the determination of frequency control reserve requirement with consideration of the interaction between ex-ante planning and real-time balancing. In proposed method, we consider the fact that the delivered energy for tertiary control reserve is determined based on required capacity for secondary control reserve and the expected amount of load errors. Uncertain load errors are derived by Brownian motion, an optimization method is suggested using a stochastic programming. In a short, we propose an interactive dependent method for determining secondary control reserve requirement based on the principle that it satisfies to minimize the total cost. As a result, this paper provides will analyze for an example model to demonstrate the capabilities of the method.

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Scheduling and Pricing of Coupled Energy and Primary, Secondary, and Tertiary Reserves

Cited by 275 publications

References 34 publications

Electricity market clearing with improved scheduling of stochastic production

Electricity market clearing with improved scheduling of stochastic production

A New Required Reserve Capacity Determining Scheme with Regard to Real time Load Imbalance

Determination of Secondary Reserve Requirement Through Interaction-dependent Clearance Between Ex-ante and Ex-post

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