Optimum simultaneous clearing of energy and spinning reserve markets using cost/benefit analysis

Motamedi, A.; Fotuhi‐Firuzabad, Mahmud; Zareipour, Hamidreza

doi:10.1109/pes.2008.4596560

Cited by 13 publications

(12 citation statements)

References 28 publications

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“…P Gi,t and P SRi,t are the amount of thermal power generation and spinning reserves from unit i at hour t, respectively. P wj,t is the amount of wind power generation from wind farm j at hour t. The commitment status of unit i at hour t is represented by I t i [38], which is defined as:…”

Section: Study 4: Scheduling Energy and Srs In A Wind-thermal Power Smentioning

confidence: 99%

Optimal scheduling of wind-thermal power system using clustered adaptive teaching learning based optimization

Reddy

2016

Electr Eng

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This paper proposes an optimal scheduling/ allocation of energy and spinning reserves for a wind-thermal power system. There is a considerable need for the renewable energy resources in the modern power system; therefore, in this paper, wind energy generators are used. Here, two different market clearing models are proposed. One model includes reserve offers from the conventional thermal generators, and the other includes reserve offers from both thermal generators, and demand/consumers. The stochastic behavior of wind speed and wind power generation is represented by the Weibull probability density function. The objective function considered in this paper includes cost of energy provided by conventional thermal and wind generators, cost of reserves provided by conventional thermal generators and load demands. It also includes costs due to under-estimation and over-estimation of available wind power generation. Clustered adaptive teaching learning based optimization algorithm is used to solve the proposed optimal scheduling problem for both conventional and wind-thermal power systems considering the provision for spinning reserves. To show the effectiveness and feasibility of the proposed frame work, various case studies are presented for two different test systems.

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Section: Study 4: Scheduling Energy and Srs In A Wind-thermal Power Smentioning

confidence: 99%

Optimal scheduling of wind-thermal power system using clustered adaptive teaching learning based optimization

Reddy

2016

Electr Eng

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“…according to (5) and (6), when the up reserve value is determined, the load shedding expectation of system can be solved.…”

Section: Load Shedding Expectation and Wind Curtailment Expectatmentioning

confidence: 99%

“…But reliability level setting has strong subjectivity and can't answer whether it is reasonable or not. The risk of load shedding is regarded as cost integrated into the generation cost objective function [5][6], and the optimal reserve can be determined automatically by the minimum operating cost and load shedding cost as target. The problem of the optimal reserve requirement of system has been investigated in these research works mentioned above.…”

Section: Introductionmentioning

confidence: 99%

A novel day-ahead generation scheduling and spinning reserve determination model for power grid containing wind power

Zhao

Tang

Luo³

et al. 2013

2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA)

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A novel day-ahead generation scheduling and spinning reserve determination model was proposed for power grid with large-scale wind power. The load shedding losses and the wind curtailment losses were estimated by using the probability density function. And they are taken as two operation risk costs integrated into the generation cost objective function. While fully meeting the unit ramp rate constraints and the network security constraints, the dayahead generation schedule of conventional units and the up/down spinning reserve capacities were solved simultaneously. The priority list method and the minimum marginal cost based economic dispatch algorithm are used to solve the proposed model. Numerical results of modified IEEE reliability test system show that the proposed model and method are effective.

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“…In some practical operating cases, BAs determine the spinning reserve by some deterministic evaluation such as the largest online in-feed or system risk probability [8,9]. Regulating reserve is then quantified by specific percentage of the allocated spinning reserve or load demands [10,11].…”

Section: Introductionmentioning

confidence: 99%

Adaptive regulating reserve scheduling for the isolated power system

Chang-Chien

Chien

2011

Int Trans Elec Energy Syst

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SUMMARY Regulating reserve is generally deployed to support system frequency. Because the moment‐to‐moment load fluctuations require continuous frequency control, allocating the reserve for this kind should be flexible to support the function of automatic generation control. Because fast response units not only are assigned to support automatic generation control but also are utilized to deal with credible frequency events, the regulating reserve may be planned as a portion of contingency reserve for security concern, especially for an isolated power system. Without inter‐tie to mutually support system frequency, frequency of an isolated system is much more sensitive to the disturbances than that in the interconnection. Therefore, the scheduling of regulating reserve for an isolated system should be more cautious to take both security and economy into account. This paper describes a methodology that adaptively schedules the regulating reserve based on the dynamic security margin as well as the ongoing demand of the system. Compared with the conventional way of using the historical data, the proposed scheduling method is proven to be more capable of dealing with the change of system condition and furthermore potentially reducing the extraneous reserve. More operational cases will be presented to show the merits of the proposed method that is applied to the ancillary service market. Copyright © 2011 John Wiley & Sons, Ltd.

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Optimum simultaneous clearing of energy and spinning reserve markets using cost/benefit analysis

Cited by 13 publications

References 28 publications

Optimal scheduling of wind-thermal power system using clustered adaptive teaching learning based optimization

Optimal scheduling of wind-thermal power system using clustered adaptive teaching learning based optimization

A novel day-ahead generation scheduling and spinning reserve determination model for power grid containing wind power

Adaptive regulating reserve scheduling for the isolated power system

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