Papers
Topics
Authors
Recent
Search
2000 character limit reached

A Stochastic-Robust Approach to Hierarchical Generation-Transmission Expansion Planning

Published 3 Oct 2019 in math.OC | (1910.01616v2)

Abstract: In this paper, the differences between an integrated and hierarchical generation and transmission expansion planning approaches are first described. Then, the hierarchical approach is described in detail. In general terms, in this scheme the investment decisions are made in steps, instead of an overall optimization scheme. This paper proposes a stochastic hierarchical generation-transmission expansion planning methodology based on a three-step procedure, as follows: 1. In this step, an integrated expansion planning problem of generation and interregional interconnections is solved; 2. Taking the optimal expansion plan of (generation and interconnections) into account, a production costing simulation with the detailed network representation is performed without monitoring circuit flow limits (except the ones in the interconnections, which are monitored); this simulation produces a set of optimal dispatch scenarios (vectors of bus loads and generation); 3. A Transmission Expansion Planning (TEP) model is then applied to determine the least-cost transmission expansion plan that is robust with respect to all operation scenarios of step 2, using an enhanced Benders decomposition scheme that: (a) incorporates a subset of the operation scenarios in the investment module; and (b) presents a "warm-up" step with a "greedy" algorithm that produces a (good) feasible solution and an initial set of feasibility cuts. The application of the hierarchical planning scheme is illustrated with a realistic multi-country generation and transmission planning case study of the Central America's electricity market.

Summary

Paper to Video (Beta)

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.