Market-Based Generation and Transmission Planning With Uncertainties

TLDR

The study proposes a stochastic coordination model for generation and transmission expansion planning in a competitive electricity market. The model uses Monte Carlo simulation with scenario reduction to capture random outages and load forecast errors, assumes a capacity payment mechanism and joint energy‑transmission market, and iteratively simulates the decision‑making of GENCOs, TRANSCOs, and the ISO until a stopping criterion is met. Case studies demonstrate the effectiveness of the stochastic method for coordinated generation and transmission planning under uncertainty.

Abstract

This paper presents a stochastic coordination of generation and transmission expansion planning model in a competitive electricity market. The Monte Carlo simulation method is applied to consider random outages of generating units and transmission lines as well as inaccuracies in the long-term load forecasting. The scenario reduction technique is introduced for reducing the computational burden of a large number of planning scenarios. The proposed model assumes a capacity payment mechanism and a joint energy and transmission market for investors' costs recovery. The proposed approach simulates the decision making behavior of individual market participants and the ISO. It is an iterative process for simulating the interactions among GENCOs, TRANSCOs and ISO. The iterative process might be terminated by the ISO based on a pre-specified stopping criterion. The case studies illustrate the applications of proposed stochastic method in a coordinated generation and transmission planning problem when considering uncertainties.