Genetic optimization toward operation of water intake-supply pump stations system. (10th January 2021)
- Record Type:
- Journal Article
- Title:
- Genetic optimization toward operation of water intake-supply pump stations system. (10th January 2021)
- Main Title:
- Genetic optimization toward operation of water intake-supply pump stations system
- Authors:
- Chen, Wanpeng
Tao, Tao
Zhou, Aijiao
Zhang, Lu
Liao, Lei
Wu, Xumeng
Yang, Kai
Li, Chenxiu
Zhang, Tian C.
Li, Zhi - Abstract:
- Abstract: The water intake and water supply pump stations consume a large amount of energy every year, and their energy efficiency improvement has a significant impact on the operations of the water industry. In this study, a general model for simplifying a simulated two-stage system (i.e., water intake and water supply pumping stations) was established. Optimization strategies were developed based on a dynamic-level-feedback-control approach. Non-dominated sorted genetic algorithm-II (NSGA-II) was used to solve the multi-objective optimization problem. Both cost-driven and energy-driven optimizations were proposed from the perspective of reliability, economy, and durability of pumping station operation. Results show that, compared to the extant strategy currently used, the cost- and energy-driven optimization strategies developed in this study can reduce operating energy costs of the system by 7.0% and 6.2%, and have satisfactory stability under the condition of uncertain water demand. Cost-driven optimization improves the power demand response of the two-stage system by increasing the load transfer in peak periods. Energy-driven optimization reduces carbon dioxide emissions by reducing the total operational energy consumption of the system. Highlights: A general model of the water intake-supply pump stations is constructed. Pump switching on/off number and time interval are synthetically considered for the operational durability. Dynamic-level-feedback-control approachAbstract: The water intake and water supply pump stations consume a large amount of energy every year, and their energy efficiency improvement has a significant impact on the operations of the water industry. In this study, a general model for simplifying a simulated two-stage system (i.e., water intake and water supply pumping stations) was established. Optimization strategies were developed based on a dynamic-level-feedback-control approach. Non-dominated sorted genetic algorithm-II (NSGA-II) was used to solve the multi-objective optimization problem. Both cost-driven and energy-driven optimizations were proposed from the perspective of reliability, economy, and durability of pumping station operation. Results show that, compared to the extant strategy currently used, the cost- and energy-driven optimization strategies developed in this study can reduce operating energy costs of the system by 7.0% and 6.2%, and have satisfactory stability under the condition of uncertain water demand. Cost-driven optimization improves the power demand response of the two-stage system by increasing the load transfer in peak periods. Energy-driven optimization reduces carbon dioxide emissions by reducing the total operational energy consumption of the system. Highlights: A general model of the water intake-supply pump stations is constructed. Pump switching on/off number and time interval are synthetically considered for the operational durability. Dynamic-level-feedback-control approach helps to ensure the operational reliability of the two-stage system. Load transfer and energy consumption are conducive to enhancing system operational energy efficiency. … (more)
- Is Part Of:
- Journal of cleaner production. Volume 279(2021)
- Journal:
- Journal of cleaner production
- Issue:
- Volume 279(2021)
- Issue Display:
- Volume 279, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 279
- Issue:
- 2021
- Issue Sort Value:
- 2021-0279-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-01-10
- Subjects:
- Water intake-supply pump stations -- Optimization -- Modeling -- Energy efficiency -- Load transfer
Factory and trade waste -- Management -- Periodicals
Manufactures -- Environmental aspects -- Periodicals
Déchets industriels -- Gestion -- Périodiques
Usines -- Aspect de l'environnement -- Périodiques
628.5 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09596526 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jclepro.2020.123573 ↗
- Languages:
- English
- ISSNs:
- 0959-6526
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4958.369720
British Library DSC - BLDSS-3PM
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