Energy and Reserve Scheduling Under a Joint Generation and Transmission Security Criterion: An Adjustable Robust Optimization Approach

Street, Alexandre; Moreira, Alexandre; Arroyo, José M.

doi:10.1109/tpwrs.2013.2278700

Cited by 110 publications

(109 citation statements)

References 26 publications

Supporting

Mentioning

105

Contrasting

Unclassified

Order By: Relevance

“…Specifically, [26] and [29] consider the case of security-constrained unit commitment under the more general N-k reliability criterion. Similarly, [26,27] and [29] use robust optimization methods for identifying worst-case N-k contingencies.…”

mentioning

confidence: 99%

“…-We ensure the existence of a feasible post-contingency corrective recourse, taking into consideration generator ramping constraints and the no-contingency (nominal) state economic dispatch; -We consider the loss of both generation units and transmission lines; -We propose novel decomposition methods to solve the contingency-constrained CCUC efficiently, and show that models and methods proposed by [12], [19], [26], [27], and [29] are all special cases of our general approach.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Contingency-constrained unit commitment with post-contingency corrective recourse

et al. 2014

View full text Add to dashboard Cite

We consider the problem of minimizing costs in the generation unit commitment problem, a cornerstone in electric power system operations, while enforcing an N-k-ε reliability criterion. This reliability criterion is a generalization of the wellknown N-k criterion, and dictates that at least (1 − ε j ) fraction of the total system demand must be met following the failures of k or fewer system components. We refer to this problem as the Contingency-Constrained Unit Commitment problem, or CCUC. We present a mixed-integer programming formulation of the CCUC that accounts for both transmission and generation element failures. We propose novel cutting plane algorithms that avoid the need to explicitly consider an exponential number of contingencies. Computational studies are performed on several IEEE test systems and a simplified model of the Western US interconnection network, which demonstrate the effectiveness of our proposed methods relative to current state-of-the-art.

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

Contingency-constrained unit commitment with post-contingency corrective recourse

et al. 2014

View full text Add to dashboard Cite

show abstract

“…As discussed in [30] and [31], trilevel models are the most efficient manner to represent scheduling under security criteria. Following the findings of [31], the inner problem shown in (3) that schedules generation power outputs and reserves can be written as:…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Following the findings of [31], the inner problem shown in (3) that schedules generation power outputs and reserves can be written as:…”

Section: Mathematical Formulationmentioning

confidence: 99%

A Five-Level MILP Model for Flexible Transmission Network Planning Under Uncertainty: A Min–Max Regret Approach

Moreira

Štrbac

Moreno

et al. 2018

IEEE Trans. Power Syst.

Self Cite

View full text Add to dashboard Cite

Abstract-The benefits of new transmission investment significantly depend on deployment patterns of renewable electricity generation that are characterized by severe uncertainty. In this context, this paper presents a novel methodology to solve the transmission expansion planning (TEP) problem under generation expansion uncertainty in a min-max regret fashion, when considering flexible network options and n − 1 security criterion. To do so, we propose a five-level mixed integer linear programming (MILP) based model that comprises: (i) the optimal network investment plan (including phase shifters), (ii) the realization of generation expansion, (iii) the co-optimization of energy and reserves given transmission and generation expansions, (iv) the realization of system outages, and (v) the decision on optimal post-contingency corrective control. In order to solve the fivelevel model, we present a cutting plane algorithm that ultimately identifies the optimal min-max regret flexible transmission plan in a finite number of steps. The numerical studies carried out demonstrate: (a) the significant benefits associated with flexible network investment options to hedge transmission expansion plans against generation expansion uncertainty and system outages, (b) strategic planning-under-uncertainty uncovers the full benefit of flexible options which may remain undetected under deterministic, perfect information, methods and (c) the computational scalability of the proposed approach.Index Terms-transmission expansion planing under uncertainty, multi-level optimization, network security, power systems economics.

show abstract

“…A lot of effort has been put to solve many specific thermal operation problems. Some of these very interesting problem arise from the combination of an extremely simple problem with the most varied characteristics of real life power systems such as the Unit-Commitment problem [52], its contigency constrained counterpart [53], the optimal power flow [17], thermal expansion [], network expansion [].…”

Section: A Thermal Operationmentioning

confidence: 99%

Modelling Power Markets With Multi-Stage Stochastic Nash Equilibria

Garcia¹,

Chabar²

View full text Add to dashboard Cite

ThanksTo all my family, specially my mother and father who stood by my side and gave me all the support one could ever dream with during this long way. Also to my brother João Pedro and my step-father Ricardo for the company.To PUC-Rio for providing an excellent environment.To my great friends that were present during all these long years.To my friends from PUC-Rio for the endless discussions, specially Gustavo Amaral, Mario Souto, Alexandre Moreira and Bruno Fanzeres.To my professors Carlos Tomei and Carlos Kubrusly for helping me to discover my interests and find my way in mathematics.To my advisor Alexandre Street who guided during most of my electrical engineering course and introduced me to optimization applied to power systems.To my good friends in UC Santa Barbara, specially my advisor over there João Pedro Hespanha.To all my friends at PSR, specially Julio Alberto Dias, Luiz Carlos da Costa Junior and Camila Metello who helped me day and night, also to Sergio Granville and Luiz Augusto Barroso for the many conversations and insights that made this work possible.To my co-advisor Mario Veiga for introducing me to the topic of this work and giving me all the support without which it would not have been possible. AbstractThe modelling of modern power markets requires the representation of the following main features: (i) a stochastic dynamic decision process, with uncertainties related to renewable production and fuel costs, among others; and (ii) a game-theoretic framework that represents the strategic behaviour of multiple agents, for example in daily price bids.These features can be in theory represented as a stochastic dynamic programming recursion, where we have a Nash equilibrium for multiple agents. However, the resulting problem is very challenging to solve. This work presents an iterative process to solve the above problem for realistic power systems. The proposed algorithm is consist of a fixed point algorithm, in which, each step is solved via stochastic dual dynamic programming method.The application of the proposed algorithm are illustrated in case studies with the real power systems. MODELAGEM DE MERCADOS DE ENERGIA COM EQUILIBRIO DE NASH STOCÁSTICO MULTI-ESTÁGIO ResumoA modelagem dos mercados de energia modernos exige a representação das seguintes características principais: (i) um processo de decisão dinâmico estocástico , com incertezas relacionadas aos os custos de produção e dos combustíveis renováveis, entre outros; e (ii) teoria dos jogos que representa o comportamento estratégico de múltiplos agentes , por exemplo, em propostas de preços diárias.Esses recursos podem ser , em teoria, representados como uma recursão de programação dinâmica estocástica, onde temos um equilíbrio de Nash para múltiplos agentes. No entanto, o problema resultante é muito difícil de resolver.Este trabalho apresenta um processo iterativo para resolver o problema acima para sistemas de energia realistas. O algoritmo proposto é composto de um algoritmo de ponto fixo, no qual, cada passo é resolvido através do mét...

show abstract

Energy and Reserve Scheduling Under a Joint Generation and Transmission Security Criterion: An Adjustable Robust Optimization Approach

Cited by 110 publications

References 26 publications

Contingency-constrained unit commitment with post-contingency corrective recourse

Contingency-constrained unit commitment with post-contingency corrective recourse

A Five-Level MILP Model for Flexible Transmission Network Planning Under Uncertainty: A Min–Max Regret Approach

Modelling Power Markets With Multi-Stage Stochastic Nash Equilibria

Contact Info

Product

Resources

About