Optimized Operation of Pump Stations of Water Delivery System Using Bees Algorithm

Background and Objectives: The optimization algorithms inspired by honey bee’s social behavior are among the most recent optimization techniques. Artificial bee colony algorithm (ABC) is one of these algorithms. Today, considering the dramatic increase in pumping energy prices in water conveyance systems, problem of optimal operation of pumping stations is one of the very hottest research areas. In many pumping stations there are no specific guidelines for the operation of the existing pumps and station ope rator acts to turn on and turn of the pumps based on experience and need will be announced him. This traditional method impose a lot of extra cost to sys tem. Therefore, in addition to proper design of pumping stations, operation of these stations is also extremely important. The most important factor affecting the pu mping station performance is the per formance of the pumps, thus pumps should be used as much as possible in their maximum efficiency.
Materials and methods: In this research a pump operation schedule is represented as a string of binary values with each bit representing pump on and off status during a particular time interval and pump optimal scheduling problem is coded as a problem of finding the best binary string which results in the least energy price. In this study a Binary Arti ficial Bee C olony Optimiz ation algorithm based simulation- optimization model has been developed for optimal scheduling of serial pumping stations. The model integrates ABC optimizer and EPA NET hydraulic network solver in MAT LAB software. The proposed model is applied to find the optima l pump operation schedule of Shiraz water conveyance system from Dor oudzan Dam in an ordinary day of the year. Then, the optimal operation mode on this special day was compared with a non-optimal utilization scenarios. The average cost of electrical energy was considered equal to 275 Rials in this study.
Results: The results showed that having regard to all the constraints of the problem, the energy cost in the optimal operation was 32% less than average one in an ordinary day. Bit ABC algorithm also caused about 8 percent improvement in optimal algorithm of - PSO with the general neighborhood, but the cost of response obtained in this study was about 2 percent higher than the - PSO algorithm with local neighborhood.
Conclusion: The comparison between the optimal operation program and the previous researches results showed the model’s abilities.