A mixed integer programming solution for market clearing and reliability analysis

Streiffert, D.; Philbrick, R.; Ott, A.

doi:10.1109/pes.2005.1489108

Cited by 70 publications

(46 citation statements)

References 8 publications

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“…The equations were slightly adjusted to the assumption described in this section but the basic structure was not changed at all. For similar approaches where MILP structures are used to solve the unit commitment problem even under consideration of security constraints and simplified transmission line capacities see Streiffert et al (2005), Delarue et al (2007) and Frangioni et al (2009).…”

Section: Constantsmentioning

confidence: 99%

Technical Framework Conditions to Integrate High Intermittent Renewable Energy Feed-in in Germany

Weber¹,

Ziems²,

Meinke³

2011

Wind Energy Management

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Section: Constantsmentioning

confidence: 99%

Technical Framework Conditions to Integrate High Intermittent Renewable Energy Feed-in in Germany

Weber¹,

Ziems²,

Meinke³

2011

Wind Energy Management

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“…Previous studies have focused on the reserve level to mitigate variations and uncertainties associated with renewable power generation [4][5][6][7][8][9][10][11][12][13]. References [9,10] managed uncertainty in net loads by imposing operating reserve requirements in deterministic models and [11][12][13] proposed stochastic programming which attempts to minimize expected costs over net load scenarios. However, procuring more regulation services to maintain power balance in the case of sudden changes in net load may result in high energy prices due to insufficient resource in energy market.…”

Section: Introductionmentioning

confidence: 99%

A Flexible Ramping Capacity Model for Generation Scheduling with High Levels of Wind Energy Penetration

et al. 2016

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Abstract:The penetration level of renewable generation has increased significantly in recent years, which has led to operational concerns associated with the system ramping capability. Here, we propose the flexible ramping capacity (FRC) model, which considers the practical ramping capability of generation resources as well as the uncertainty in net load. The FRC model also incorporates the demand curve of the ramping capacity, which represents the hourly economic value of the ramping capacity. The model is formulated mathematically using ramp constraints, which are incorporated into unit commitment (UC) and economic dispatch (ED) processes. Simulations are carried out using a 10-unit system to compare the FRC model with conventional methods. We show that the FRC method can improve reliability and reduce expected operating costs. The simulation results also show that, by using the FRC model, system reliability can be satisfied at high wind power generation levels while achieving economic efficiency.

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“…Furthermore, a MIP solution for solving the PJM unit commitment problem is described in [10]. The paper explains many of the inherent problems associated with MIP solutions and illustrates how these issues were dealt with to provide a fast, accurate, and robust MIP solution.…”

Section: Introductionmentioning

confidence: 99%

Short-Term Scheduling of Combined Cycle Units Using Mixed Integer Linear Programming Solution

Alemany¹,

Moitre²,

Pinto³

et al. 2013

EPE

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Combined cycle plants (CCs) are broadly used all over the world. The inclusion of CCs into the optimal resource scheduling causes difficulties because they can be operated in different operating configuration modes based on the number of combustion and steam turbines. In this paper a model CCs based on a mixed integer linear programming approach to be included into an optimal short term resource optimization problem is presented. The proposed method allows modeling of CCs in different modes of operation taking into account the non convex operating costs for the different combined cycle mode of operation.

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A mixed integer programming solution for market clearing and reliability analysis

Cited by 70 publications

References 8 publications

Technical Framework Conditions to Integrate High Intermittent Renewable Energy Feed-in in Germany

Technical Framework Conditions to Integrate High Intermittent Renewable Energy Feed-in in Germany

A Flexible Ramping Capacity Model for Generation Scheduling with High Levels of Wind Energy Penetration

Short-Term Scheduling of Combined Cycle Units Using Mixed Integer Linear Programming Solution

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