Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market

Abstract In recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. I...

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Main Authors: Xinhong Zhou, Shipeng Chu, Tuqiao Zhang, Tingchao Yu, Yu Shao
Format: Article
Language:English
Published: Wiley 2024-04-01
Series:Water Resources Research
Subjects:
Online Access:https://doi.org/10.1029/2023WR035630
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author Xinhong Zhou
Shipeng Chu
Tuqiao Zhang
Tingchao Yu
Yu Shao
author_facet Xinhong Zhou
Shipeng Chu
Tuqiao Zhang
Tingchao Yu
Yu Shao
author_sort Xinhong Zhou
collection DOAJ
description Abstract In recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. In a RTP market, both positive and negative electricity prices are possible. These negative prices create economically attractive opportunities for Water Distribution System (WDS) to dispatch their energy consumption. On the other hand, excessively high prices may put WDS at risk of supply disruptions and reduced service levels. However, the continuous development of wind power and photovoltaics results in more volatile and unpredictable fluctuations in the price of renewable energy. The risk arising from uncertainty in electricity prices can lead to a significant increase in actual costs. To address this issue, this paper develops an a posteriori random forest (AP‐RF) approach to forecast the probability density function of electricity prices for the next day and provide a risk‐constrained pump scheduling method toward RTP electricity market. The experimental results demonstrate that the developed method effectively addresses the issue of increased costs caused by inaccurate electricity price forecasting.
format Article
id doaj-art-eaf27529596f48979f766a09775cf6a1
institution OA Journals
issn 0043-1397
1944-7973
language English
publishDate 2024-04-01
publisher Wiley
record_format Article
series Water Resources Research
spelling doaj-art-eaf27529596f48979f766a09775cf6a12025-08-20T02:09:29ZengWileyWater Resources Research0043-13971944-79732024-04-01604n/an/a10.1029/2023WR035630Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity MarketXinhong Zhou0Shipeng Chu1Tuqiao Zhang2Tingchao Yu3Yu Shao4College of Civil Engineering and Architecture Zhejiang University Hangzhou ChinaCollege of Civil Engineering and Architecture Zhejiang University Hangzhou ChinaCollege of Civil Engineering and Architecture Zhejiang University Hangzhou ChinaCollege of Civil Engineering and Architecture Zhejiang University Hangzhou ChinaCollege of Civil Engineering and Architecture Zhejiang University Hangzhou ChinaAbstract In recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. In a RTP market, both positive and negative electricity prices are possible. These negative prices create economically attractive opportunities for Water Distribution System (WDS) to dispatch their energy consumption. On the other hand, excessively high prices may put WDS at risk of supply disruptions and reduced service levels. However, the continuous development of wind power and photovoltaics results in more volatile and unpredictable fluctuations in the price of renewable energy. The risk arising from uncertainty in electricity prices can lead to a significant increase in actual costs. To address this issue, this paper develops an a posteriori random forest (AP‐RF) approach to forecast the probability density function of electricity prices for the next day and provide a risk‐constrained pump scheduling method toward RTP electricity market. The experimental results demonstrate that the developed method effectively addresses the issue of increased costs caused by inaccurate electricity price forecasting.https://doi.org/10.1029/2023WR035630real‐time electricity pricerisk constraintoptimal schedulingwater distribution system
spellingShingle Xinhong Zhou
Shipeng Chu
Tuqiao Zhang
Tingchao Yu
Yu Shao
Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market
Water Resources Research
real‐time electricity price
risk constraint
optimal scheduling
water distribution system
title Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market
title_full Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market
title_fullStr Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market
title_full_unstemmed Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market
title_short Risk‐Constrained Optimal Scheduling in Water Distribution Systems Toward Real‐Time Pricing Electricity Market
title_sort risk constrained optimal scheduling in water distribution systems toward real time pricing electricity market
topic real‐time electricity price
risk constraint
optimal scheduling
water distribution system
url https://doi.org/10.1029/2023WR035630
work_keys_str_mv AT xinhongzhou riskconstrainedoptimalschedulinginwaterdistributionsystemstowardrealtimepricingelectricitymarket
AT shipengchu riskconstrainedoptimalschedulinginwaterdistributionsystemstowardrealtimepricingelectricitymarket
AT tuqiaozhang riskconstrainedoptimalschedulinginwaterdistributionsystemstowardrealtimepricingelectricitymarket
AT tingchaoyu riskconstrainedoptimalschedulinginwaterdistributionsystemstowardrealtimepricingelectricitymarket
AT yushao riskconstrainedoptimalschedulinginwaterdistributionsystemstowardrealtimepricingelectricitymarket