Adjustable Robust OPF With Renewable Energy Sources

Jabr, Rabih A.

doi:10.1109/tpwrs.2013.2275013

Cited by 339 publications

(216 citation statements)

References 23 publications

Supporting

Mentioning

213

Contrasting

Unclassified

Order By: Relevance

“…This model consists of 107 buses, 191 transmission lines, and 30 generators. These generators include 16 thermal electric power plants, 8 hydraulic power plants, 5 nuclear power plants, and 1 renewable plant. The renewable plant is described by the symbol "W" in Fig.…”

Section: A Numerical Examplementioning

confidence: 99%

See 1 more Smart Citation

A Randomized Algorithm for Chance Constrained Optimal Power Flow with Renewables

Wada

Morita

Asai

et al. 2017

SICE Journal of Control, Measurement, and System Integration

View full text Add to dashboard Cite

: A chance constrained AC optimal power flow is to find the optimal economic operation plan whose probability satisfying AC power flow equations and various inequality constraints on operating limits of the power system is greater than a specified probability level. Even if a constraint condition for each uncertain power supply value is convex with respect to decision variables, the chance constrained problem is not convex in general. Thus, it is difficult to solve the problem within reasonable computational time. Employment of randomization techniques for this issue is proposed in this paper. A main advantage of the framework leads to a solution with a theoretical guarantee. Its sample complexities are of polynomial order for parameters of a given accuracy. The efficiency of this algorithm is demonstrated by applying it to the Japanese power system models.

show abstract

Section: A Numerical Examplementioning

confidence: 99%

“…In [8], an adjustable robust direct current optimal power flow (DC-OPF) whose operation plan is affinely adjustable with respect to renewable power generation, is formulated. A similar strategy is also employed for security-constrained OPF [9].…”

Section: Introductionmentioning

confidence: 99%

A Randomized Algorithm for Chance Constrained Optimal Power Flow with Renewables

Wada

Morita

Asai

et al. 2017

SICE Journal of Control, Measurement, and System Integration

View full text Add to dashboard Cite

show abstract

“…-Scenario based modeling [7], [8] • Fuzzy approach [9] • Robust optimization [10] Each technique has its own "pros and cons". For example, stochastic techniques require knowledge of the probability density function of uncertain parameter.…”

Section: B Literature Reviewmentioning

confidence: 99%

Information Gap Decision Theory Based OPF With HVDC Connected Wind Farms

Rabiee

Soroudi

Keane

2015

IEEE Trans. Power Syst.

104

View full text Add to dashboard Cite

“…The first-stage decision x stands for the operating point for the nominal load level, then the secondstage decision is the AGC dispatch signal responding to the uncertain load realization, see [72]. An alternative approach using affine decision policy for the AGC dispatch signal is discussed in [73]. A multiperiod adaptive robust model is proposed for look-ahead ED under significant wind [74], where the first-stage decision is the dispatch decision in the current time period, and the dispatch decisions for future look-ahead periods are the second-stage decision.…”

Section: Robust Optimizationmentioning

confidence: 99%

Advanced optimization methods for power systems

Panciatici¹,

Campi

Garatti

et al. 2014

2014 Power Systems Computation Conference

View full text Add to dashboard Cite

Abstract-Power system planning and operation offers multitudinous opportunities for optimization methods. In practice, these problems are generally large-scale, non-linear, subject to uncertainties, and combine both continuous and discrete variables. In the recent years, a number of complementary theoretical advances in addressing such problems have been obtained in the field of applied mathematics. The paper introduces a selection of these advances in the fields of non-convex optimization, in mixedinteger programming, and in optimization under uncertainty. The practical relevance of these developments for power systems planning and operation are discussed, and the opportunities for combining them, together with high-performance computing and big data infrastructures, as well as novel machine learning and randomized algorithms, are highlighted.

show abstract

Adjustable Robust OPF With Renewable Energy Sources

Cited by 339 publications

References 23 publications

A Randomized Algorithm for Chance Constrained Optimal Power Flow with Renewables

A Randomized Algorithm for Chance Constrained Optimal Power Flow with Renewables

Information Gap Decision Theory Based OPF With HVDC Connected Wind Farms

Advanced optimization methods for power systems

Contact Info

Product

Resources

About