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PowNet: A Network-Constrained Unit Commitment/Economic Dispatch Model for Large-Scale Power Systems Analysis Cover

PowNet: A Network-Constrained Unit Commitment/Economic Dispatch Model for Large-Scale Power Systems Analysis

Open Access
|Mar 2020

Abstract

PowNet is a free modelling tool for simulating the Unit Commitment/Economic Dispatch of large-scale power systems. PowNet is specifically conceived for systems characterized by the presence of variable renewable resources (e.g., hydropower, solar, and wind), whose penetration on the grid is strongly influenced by climatic variability and constrained by the availability of transmission capacity. To help users effectively capture the nuances of power system dynamics, PowNet is equipped with features that enable accuracy, transferability, and computational efficiency over large spatial and temporal domains. Specifically, the model (i) accounts for the techno-economic constraints of both generating units and transmission networks, (ii) can be easily coupled with models that estimate the status of generating units as a function of the climatic conditions, and (iii) explicitly includes import/export nodes, which are useful in representing cross-border systems. PowNet is implemented in Python and is compatible with any standard optimization solver (e.g., Gurobi, CPLEX). Its functionality is demonstrated on the Cambodian power system.

 

Funding statement: This research is supported by Singapore’s Ministry of Education (MoE) through the Tier 2 project ‘Linking water availability to hydropower supply—an engineering systems approach’ (Award No. MOE2017-T2-1-143).

DOI: https://doi.org/10.5334/jors.302 | Journal eISSN: 2049-9647
Language: English
Submitted on: Sep 27, 2019
Accepted on: Feb 18, 2020
Published on: Mar 12, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 A. F. M. Kamal Chowdhury, Jordan Kern, Thanh Duc Dang, Stefano Galelli, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.