Leakage Control and Energy Consumption Optimization (Research Paper)

Leakage Control and Energy Consumption Optimization (Research Paper)

Leakage Control and Energy Consumption Optimization in the Water Distribution Network Based on Joint Scheduling of Pumps and Valves

Yu Shao, Yanxi Yu, Tingchao Yu, Shipeng Chu, Xiaowei Liu


Apart from water quality, leakage control and energy consumption management are the most concerning challenges for water treatment plants (WTPs). The joint scheduling of pumps and pressure reducing valves (PRVs) in the water distribution network can reduce excessive pressure and distribute pressure more evenly, which achieves comprehensive reduction of leakages and energy consumption.

Taking into account the main shortcomings of the commonly used methods, such as scheduling pumps or PRVs separately, or optimizing PRV settings when their position is given, etc., this paper has taken the PRV (position and setting) and the working status of variable speed pumps (VSPs) as decision variables and the cost savings contributed by leakage reduction and energy consumption savings as the objective function, which maximized the economic benefits brought by PRV and/or VSP scheduling. A genetic algorithm (GA) was used to optimize the solution under multiple working conditions. T

The performance of three control strategies (PRV-only scheduling, VSP-only scheduling, and joint scheduling of PRVs and VSPs) are compared to each other based on a small network. Joint scheduling has achieved the best economic benefits in reducing the gross cost (contributed by leakage and energy consumption) of the three control strategies, which results in a leakage reduction of 33.4%, an energy consumption reduction of 25.4%, and a total cost reduction of 33.1%, when compared to the original network, and saving about 1148 m3 water (7% of the original consumption) and 722 kWh electric energy (25.4% of the original consumption) per day.

Keyword : water distribution network; leakage; energy consumption; pump; valve; joint scheduling

Energies 2019, 12(15), 2969; DOI: 10.3390/en12152969

Source: MDPI