Visible to the public A generalized stochastic N-m security-constrained generation expansion planning methodology using partial transmission distribution factors

TitleA generalized stochastic N-m security-constrained generation expansion planning methodology using partial transmission distribution factors
Publication TypeConference Paper
Year of Publication2017
AuthorsHinojosa, V.
Conference Name2017 IEEE Power Energy Society General Meeting
Keywordsgeneralized generation distribution factors, generalized stochastic N-m security-constrained generation expansion planning methodology, Generators, line outage distribution factors, Linear distribution factors, Load flow, Load modeling, load scenarios, multiple-line outages, optimisation, Optimization, optimization problem, partial transmission distribution factors, Planning, post-contingency constraints, power generation dispatch, power generation planning, power generation scheduling, power markets, power system reliability, power system security, power transmission economics, pubcrawl, resilience, Resiliency, Scalability, security, security criteria, security-constrained, security-constrained analyses, Stochastic computing, Stochastic Computing Security, stochastic problem, Stochastic processes, stochastic programming, stochastic security-constrained generation capacity expansion planning problem, Transmission line matrix methods, two-stage problem, Uncertainty
Abstract

This study proposes to apply an efficient formulation to solve the stochastic security-constrained generation capacity expansion planning (GCEP) problem using an improved method to directly compute the generalized generation distribution factors (GGDF) and the line outage distribution factors (LODF) in order to model the pre- and the post-contingency constraints based on the only application of the partial transmission distribution factors (PTDF). The classical DC-based formulation has been reformulated in order to include the security criteria solving both pre- and post-contingency constraints simultaneously. The methodology also takes into account the load uncertainty in the optimization problem using a two-stage multi-period model, and a clustering technique is used as well to reduce load scenarios (stochastic problem). The main advantage of this methodology is the feasibility to quickly compute the LODF especially with multiple-line outages (N-m). This idea could speed up contingency analyses and improve significantly the security-constrained analyses applied to GCEP problems. It is worth to mentioning that this approach is carried out without sacrificing optimality.

URLhttps://ieeexplore.ieee.org/document/8274428/
DOI10.1109/PESGM.2017.8274428
Citation Keyhinojosa_generalized_2017