Multi-Area Unit Scheduling and Reserve Allocation Under Wind Power Uncertainty

Ahmadi-Khatir, Ali; Conejo, Antonio J.; Cherkaoui, Rachid

doi:10.1109/tpwrs.2013.2293542

Cited by 159 publications

(58 citation statements)

References 18 publications

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“…To address these challenges, an extensive academic and industrial literature has developed addressing both technical and economic aspects of variable energy resource (VER) integration [1]- [3]. The main conclusion of such integration studies is that renewable energy integration requires the procurement of additional generation reserves [4]- [9]; although they often disagree on their exact quantity.…”

Section: Introductionmentioning

confidence: 99%

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances—Part II: Methodology

Muzhikyan

Farid

2015

IEEE Trans. Ind. Electron.

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Abstract-In recent years, an extensive academic and industrial literature has developed to determine how much such variable energy resources (VER) may be integrated and how to best mitigate their impacts. While certainly insightful within the context of their application, many integration studies have methodological limitations in that they are case specific, address a single control function of power grid balancing operations, and are often not validated by simulation. This paper presents a holistic method for the assessment of power grid imbalances induced by variable energy resources based upon the concept of enterprise control. It consists within a single package a three layer enterprise control simulator which includes most of the balancing operation functionality found in traditional power systems. The control layers include a resource scheduling layer composed of a security-constrained unit commitment, a balancing layer composed of a security-constrained economic dispatch, and a regulation layer. The proposed method is validated by a set of numerical simulations. The sequel to this paper submitted to the same issue provides a set of extensive results that demonstrate how power grid balancing operations systematically address variable energy resource integration.

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Section: Introductionmentioning

confidence: 99%

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances—Part II: Methodology

Muzhikyan

Farid

2015

IEEE Trans. Ind. Electron.

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“…• To use a supercomputer, • To implement parallelization techniques [29], • To apply appropriate techniques to simplify the network [30] and/or to reduce the number of scenarios [31], • To decompose the UC problem by area [32].…”

Section: Computational Optimality and Implementation Issuesmentioning

confidence: 99%

Network-Constrained AC Unit Commitment Under Uncertainty: A Benders’ Decomposition Approach

Nasri

Kazempour

Conejo

et al. 2016

IEEE Trans. Power Syst.

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121

109

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Abstract-This paper proposes an efficient solution approach based on Benders' decomposition to solve a network-constrained ac unit commitment problem under uncertainty. The wind power production is the only source of uncertainty considered in this paper, which is modeled through a suitable set of scenarios. The proposed model is formulated as a two-stage stochastic programming problem, whose first-stage refers to the day-ahead market, and whose second-stage represents real-time operation. The proposed Benders' approach allows decomposing the original problem, which is mixed-integer nonlinear and generally intractable, into a mixed-integer linear master problem and a set of nonlinear, but continuous subproblems, one per scenario. In addition, to temporally decompose the proposed ac unit commitment problem, a heuristic technique is used to relax the inter-temporal ramping constraints of the generating units. Numerical results from a case study based on the IEEE one-area reliability test system (RTS) demonstrate the usefulness of the proposed approach.

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“…The auxiliary problem principle (APP) [9] is applied with ALD to implement distributed OPF [10], and decentralized multiarea stochastic generation unit commitment (UC) [11]. The alternating direction multiplier method (ADMM) is also used to solve ALD-based OPF in a distributed manner [12], [13].…”

Section: Introductionmentioning

confidence: 99%

“…In [17], the multiarea dynamic economic dispatch (DED) problem was solved with a modified generalized Benders' decomposition technique in a decentralize-and-coordinate manner. Nevertheless, in addressing the decentralized OPF method, few (except [11]) considers ON/OFF states of generating units, which are the core decision in the multiarea generation unit scheduling.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Multiarea Robust Generation Unit and Tie-Line Scheduling Under Wind Power Uncertainty

Shahidehpour

et al. 2015

IEEE Trans. Sustain. Energy

145

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The growing interconnections of regional power systems and the large-scale integration of wind energy bring about the critical need to coordinate multiarea generation unit and tieline scheduling (MAUTS). It is recognized that because of the limitations on private data exchange and model management, it is suitable to address the multiarea power scheduling problem in a decentralized way. In this paper, the MAUTS problem is formulated using the adaptive robust optimization (RO) scheme to account for uncertain wind energy. Our model is decomposed into regional subproblems by augmented Lagrangian decomposition (ALD), which enables a fully distributed computation within an alternating direction multiplier method framework. To address the nonconvexity issue, a tractable alternating optimization procedure (AOP) is developed to obtain high-quality solutions with finite convergence for the nonconvex mixed-integer problem. Simulations on different test systems are conducted to show the computational performance, the solution quality, and scalability of the proposed method.Index Terms-Multiarea power systems, network-constrained generation unit commitment, robust optimization (RO), tie-line scheduling, wind energy uncertainty. 1949-3029

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Multi-Area Unit Scheduling and Reserve Allocation Under Wind Power Uncertainty

Cited by 159 publications

References 18 publications

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances—Part II: Methodology

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances—Part II: Methodology

Network-Constrained AC Unit Commitment Under Uncertainty: A Benders’ Decomposition Approach

Decentralized Multiarea Robust Generation Unit and Tie-Line Scheduling Under Wind Power Uncertainty

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