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Main Authors: Hu, Manling, Xu, Manqi, Liu, Dunnan
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2411.07069
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author Hu, Manling
Xu, Manqi
Liu, Dunnan
author_facet Hu, Manling
Xu, Manqi
Liu, Dunnan
contents While wind and solar power contribute to sustainability, their intermittent nature poses challenges when integrated into the grid. To mitigate these issues, renewable energy can be combined with coal fired power and hydropower sources to stabilize the energy system, with battery storage serving as a backup source to smooth the total output. This study develops a low carbon dispatch model for a combined energy system using a two stage stochastic optimization approach. The model incorporates a carbon trading mechanism to regulate emissions and addresses the uncertainty in wind and solar outputs by clustering output curves into typical scenarios to derive a joint distribution. In the initial stage of scheduling, decisions are made regarding the unit commitment for coal fired power plants. The second stage optimizes the expected operation cost of other energy generation sources. The feasibility of the model is demonstrated by comparing the results of stochastic and deterministic scenarios through simulation. Analysis of different carbon prices further explores the impact of the carbon trading mechanism on the system's operation cost.
format Preprint
id arxiv_https___arxiv_org_abs_2411_07069
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Two-Stage Stochastic Optimization for Low-Carbon Dispatch in a Combined Energy System
Hu, Manling
Xu, Manqi
Liu, Dunnan
Systems and Control
While wind and solar power contribute to sustainability, their intermittent nature poses challenges when integrated into the grid. To mitigate these issues, renewable energy can be combined with coal fired power and hydropower sources to stabilize the energy system, with battery storage serving as a backup source to smooth the total output. This study develops a low carbon dispatch model for a combined energy system using a two stage stochastic optimization approach. The model incorporates a carbon trading mechanism to regulate emissions and addresses the uncertainty in wind and solar outputs by clustering output curves into typical scenarios to derive a joint distribution. In the initial stage of scheduling, decisions are made regarding the unit commitment for coal fired power plants. The second stage optimizes the expected operation cost of other energy generation sources. The feasibility of the model is demonstrated by comparing the results of stochastic and deterministic scenarios through simulation. Analysis of different carbon prices further explores the impact of the carbon trading mechanism on the system's operation cost.
title Two-Stage Stochastic Optimization for Low-Carbon Dispatch in a Combined Energy System
topic Systems and Control
url https://arxiv.org/abs/2411.07069