Year: 2026
Type: article
Abstract: Meeting the ever-growing needs of the power grid requires constant infrastructure enhancement. There are two important aspects for a grid’s ability to ensure continuous and reliable electricity delivery to consumers: capacity, the maximum amount the system can handle, and transmission, the infrastructure necessary to deliver electricity across the network. The capacity and transmission costs are allocated to the end-users according to the cost causation principle. These charges are computed based on the customer’s demand on coincident peak (CP) events, time intervals when the system-wide electric load is highest. We tackle the problem of predicting CP events based on publicly available data of actual and forecast loads in different jurisdictions. We propose two different algorithms depending upon the availability of forecasts. In both cases, we generate Monte Carlo scenarios from the models, and derive estimators for predicting CP-day and exact CP-hour events. We back-test the prediction performance of our algorithms on two case studies. Our analysis has crucial practical implications for load curtailment through Battery Energy Storage System (BESS) solutions.
Source: Energy Systems
Authors: René Carmona, Xinshuo Yang, Claire Zeng
Institution: Princeton University
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,490
Awards: G455799479, NEW COOPERATIVE AGREEMENT TO PRINCETON UNIVERSITY IN ACCORDANCE WITH ARPA-E FOA NUMBER DE-FOA-0002171 (PERFORM)AND APPLICATION CONTROL NUMBER 2171-1603.
PROJECT TITLE: ''STOCHASTIC MODELS, INDICES & OPTIMIZATION ALGORITHMS FOR PRICING & HEDGING RELIABILITY RISKS IN MODERN POWER GRIDS''
THE APPLICANT PROPOSES TO ADAPT THE SCIENCE OF RISK MEASURES,CREDIT RATINGS AND ACTUARIAL PRODUCTS TO QUANTIFY THE IMPACT OF UNCERTAINTIES OF RENEWABLES
PRODUCTION, LOAD AND DERS ON ELECTRICITY MARKET OPERATIONS., ----------
TRUSTEES OF PRINCETON UNIVERSITY: NEW DNFA AWARD.
TITLE: “STOCHASTIC MODELS, INDICES & OPTIMIZATION ALGORITHMS FOR PRICING & HEDGING RELIABILITY RISKS IN
MODERN POWER GRIDS”
THE TRUSTEES OF PRINCETON UNIVERSITY WILL DEVELOP A JOINT STOCHASTIC MODEL FOR SOLAR, WIND AND LOADS FOR THE REGIONS OF INTEREST TO SEVERAL PERFORM TEAMS, AND A SIMULATION ENGINE PROVIDING RESPECTIVE MONTE CARLO SCENARIOS CAPTURING THE TEMPORAL AND GEOGRAPHICAL CORRELATIONS.
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OpenAlex ID: W7140172986