Application of Progressive Hedging to Var Expansion Planning Under Uncertainty

04/17/2020
by   Igor Carvalho, et al.
0

This paper describes the application of a Progressive Hedging (PH) algorithm to the least-cost var planning under uncertainty. The method PH is a scenario-based decomposition technique for solving stochastic programs, i.e., it decomposes a large scale stochastic problem into s deterministic subproblems and couples the decision from the s subproblems to form a solution for the original stochastic problem. The effectiveness and computational performance of the proposed methodology will be illustrated with var planning studies for the IEEE 24-bus system (5 operating scenarios), the 200-bus Bolivian system (1,152 operating scenarios) and the 1,600-bus Colombian system (180 scenarios).

READ FULL TEXT

page 2

page 3

research
11/16/2020

Fuzzy C-means-based scenario bundling for stochastic service network design

Stochastic service network designs with uncertain demand represented by ...
research
04/26/2013

Non Deterministic Logic Programs

Non deterministic applications arise in many domains, including, stochas...
research
09/25/2020

Randomized Progressive Hedging methods for Multi-stage Stochastic Programming

Progressive Hedging is a popular decomposition algorithm for solving mul...
research
04/05/2019

Combining Offline Models and Online Monte-Carlo Tree Search for Planning from Scratch

Planning in stochastic and partially observable environments is a centra...
research
06/17/2013

An Algorithm to Find Optimal Attack Paths in Nondeterministic Scenarios

As penetration testing frameworks have evolved and have become more comp...
research
07/03/2009

Computational Scenario-based Capability Planning

Scenarios are pen-pictures of plausible futures, used for strategic plan...
research
07/17/2023

Towards Accelerating Benders Decomposition via Reinforcement Learning Surrogate Models

Stochastic optimization (SO) attempts to offer optimal decisions in the ...

Please sign up or login with your details

Forgot password? Click here to reset