A New Affinely Adjustable Robust Model for Security Constrained Unit Commitment under Uncertainty

Sierra-Aguilar, Juan Esteban; Marín-Cano, Cristian Camilo; López-Lezama, Jesús M.; Jaramillo-Duque, Álvaro; Villegas, Juan G.

doi:10.3390/app11093987

Cited by 3 publications

(1 citation statement)

References 65 publications

(98 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ORPD is part of the daily operation of power systems; it consists of finding the right settings of transformer taps, reactor banks and voltage set points in generation buses, generally with the aim of minimizing active power losses [1]. The ORPD is usually solved after the unit commitment, which is the process of programming the active power generation as a function of their biding prices and limits [2,3]. The first attempts to solve the ORPD problem resorted to classical optimization techniques such as linear programming [4], quadratic programming [5] and interior point methods [6].…”

Section: Introductionmentioning

confidence: 99%

Solving the Optimal Reactive Power Dispatch Problem through a Python-DIgSILENT Interface

et al. 2022

Self Cite

View full text Add to dashboard Cite

The Optimal Reactive Power Dispatch (ORPD) problem consists of finding the optimal settings of reactive power resources within a network, usually with the aim of minimizing active power losses. The ORPD is a nonlinear and nonconvex optimization problem that involves both discrete and continuous variables; the former include transformer tap positions and settings of reactor banks, while the latter include voltage magnitude settings in generation buses. In this paper, the ORPD problem is modeled as a mixed integer nonlinear programming problem and solved through two different metaheuristic techniques, namely the Mean Variance Mapping Optimization and the genetic algorithm. As a novelty, the solution of the ORPD problem is implemented through a Python-DIgSILENT interface that combines the strengths of both software. Several tests were performed on the IEEE 6-, 14-, and 39-bus test systems evidencing the applicability of the proposed approach. The results were contrasted with those previously reported in the specialized literature, matching, and in some cases improving, the reported solutions with lower computational times.

show abstract

Section: Introductionmentioning

confidence: 99%

Solving the Optimal Reactive Power Dispatch Problem through a Python-DIgSILENT Interface

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

Renewable Energy Systems: Optimal Planning and Design

Choi

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

Multi-Period Optimal Reactive Power Dispatch Using a Mean-Variance Mapping Optimization Algorithm

2022

View full text Add to dashboard Cite

Optimal reactive power dispatch plays a key role in the safe operation of electric power systems. It consists of the optimal management of the reactive power sources within the system, usually with the aim of reducing system power losses. This paper presents both a new model and a solution approach for the multi-period version of the optimal reactive power dispatch. The main feature of a multi-period approach lies on the incorporation of inter-temporal constraints that allow the number of switching operations in transformer taps and capacitor banks to be limited in order to preserve their lifetime and avoid maintenance cost overruns. The main contribution of the paper is the constraint handling approach which consists of a multiplication of sub-functions which act as penalization and allow simultaneous consideration of both the feasibility and optimality of a given candidate solution. The multi-period optimal reactive power dispatch is an inherently nonconvex and nonlinear problem; therefore, it was solved using the metaheuristic mean-variance mapping optimization algorithm. The IEEE 30-bus and IEEE 57-bus test systems were used to validate the model and solution approach. The results allow concluding that the proposed model guarantees an adequate reactive power management that meets the objective of minimizing power losses and keeping the transformer taps and capacitor bank movements within limits that allow guaranteeing their useful life.

show abstract

A New Affinely Adjustable Robust Model for Security Constrained Unit Commitment under Uncertainty

Cited by 3 publications

References 65 publications

Solving the Optimal Reactive Power Dispatch Problem through a Python-DIgSILENT Interface

Solving the Optimal Reactive Power Dispatch Problem through a Python-DIgSILENT Interface

Renewable Energy Systems: Optimal Planning and Design

Multi-Period Optimal Reactive Power Dispatch Using a Mean-Variance Mapping Optimization Algorithm

Contact Info

Product

Resources

About