Papers for

power system planners

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Winter weather worsens gas-fired power outages in New York state

A multi-stage probabilistic framework to estimate gas-fired generator performance during extreme winter weather

Abstract: Extreme winter weather has repeatedly disrupted gas-fired power generation in the United States, yet the plant-level data needed to systematically quantify outage risk remain proprietary. Using publicly available weather and electricity demand data together with anonymized generator contingency records from the North American Electric Reliability Corporation (NERC), we develop a three-stage Bayesian probabilistic framework for estimating winter-driven generator performance. Applied to New York State (2013--2022), the framework sequentially estimates: the hourly probability of a generator contingency event, the expected net available capacity conditioned on an event occurring, and the event duration. Colder conditions and higher electricity demand are associated with higher failure probability, lower retained capacity, and longer event duration. Under the most severe observed stress conditions, estimated mean hourly event probability reaches 24\% , while expected mean net available capacity falls to 13\% of nameplate rating. Full outage events have a median duration of 12.7 hours, while partial derating event duration increases from 2.4 to 7.1 hours with capacity loss severity. The proposed framework establishes a transferable baseline that utilities with access to plant-level records can directly extend to obtain more precise reliability estimates for operational planning and resource adequacy assessment.

Sat 3 OctMachine Learning
The gist
Winter storms often cause gas power plants to stop working well, but detailed data on outages is hard to get. To fix this, the authors created a three-step method using public weather and power use data to guess how likely a plant is to have trouble, how much power it can still produce, and how long the problem might last. They tested this method on New York from 2013 to 2022 and found that very cold weather and high electricity use make outages more likely, with outages sometimes lasting over half a day. Their approach can be used by utilities to improve planning and predict power problems better.
Open → 2610.04368v1

Polynomial time method improves planning of power grid expansions

Polynomial-time algorithms for setting tight big-M coefficients in transmission expansion planning with disconnected buses

Abstract: The increasing penetration of renewable energy and rising electricity demand are driving the need to integrate new buses and transmission lines into transmission grids. These trends are reshaping transmission expansion planning (TEP), motivating the development of effective methodologies to manage the resulting complexity. This paper introduces the longest shortest-path connection (LSPC) algorithm, a graph-based method to enhance the mixed-integer linear programming disjunctive formulation of TEP using valid inequalities (VIs). Traditional approaches for determining big-M coefficients in disconnected TEP networks typically rely on solving the computationally intensive longest path problem (LPP). In contrast, LSPC circumvents these limitations by efficiently identifying relevant power-flow paths between disconnected buses within the expansion network. We demonstrate that the VIs generated from these identified paths dominate those derived from LPP-based methods and other existing approaches.

Tue 8 SeptDiscrete Mathematics
The gist
Electricity grids need new lines and connection points to handle more renewable energy and higher demand. Planning these expansions is complicated, especially when parts of the grid are disconnected. The authors developed a faster way to set important parameters called big-M coefficients by finding key paths in the grid more efficiently than before. This method helps improve the math models used to plan grid expansions, making them more accurate and easier to solve.
Open → 2609.09474v1