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.
Original language | English (US) |
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Article number | 123573 |
Journal | Journal of Cleaner Production |
Volume | 279 |
DOIs | |
State | Published - Jan 10 2021 |
Keywords
- Energy efficiency
- Load transfer
- Modeling
- Optimization
- Water intake-supply pump stations
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- General Environmental Science
- Strategy and Management
- Industrial and Manufacturing Engineering