Study of Optimal Operation for Huai’an Parallel Pumping Stations with Adjustable-Blade Units Based on Two Stages Decomposition-Dynamic Programming Aggregation Method

Abstract

Two-stage decomposition-dynamic programming aggregation method has been first proposed and introduced to solve the mathematical model of daily optimal operation for parallel pumping stations with adjustable-blade units. Taking minimal daily electricity cost of single pump station as objective function, the water quantity pumped by each station as coordinated variable, by means of the type of the pump units this model is decomposed into several first-stage sub-model of daily optimal operation with adjustable-blade for single pump station. Then taking minimal daily electricity cost of single pump unit as objective function, the water quantity pumped by each unit as coordinated variable, the first-stage sub-model is decomposed into several second-stage sub-model of daily optimal operation with adjustable-blade for single pump unit which takes the blade angle as decision variable, the discrete values of water quantity pumped by each unit as state variable, and is solved by means of dynamic programming method. The constructed aggregation model takes daily water quantity pumped by each pump unit as decision variable, the discrete values of water quantity pumped by parallel station group as state variable, and is also solved by dynamic programming method. The aggregation process replaces the traditional method of constructing equations. This method has first solved the optimal operation issues for multi-units of parallel stations with various operation modes, time period division and daily average head of each station, and also provided theoretical support for the study on optimal operation of multi-stage pumping stations. Taking Huai'an No.1, No.2, and No.4 parallel pumping stations as a study case, a series of optimization results have been obtained.

Combinatorial Optimization Method for Operation of Pumping Station with Adjustable Blade and Variable Speed Based on Experimental Optimization of Subsystem

“…Referring to literature [11,13], the aggregation model (7)∼ (9) can be solved by one-dimensional dynamic programming method, by which the optimal allocation of water quantity for each unit * 0 , ( = 1, 2, . . .…”

“…In order to reduce energy consumption of the pumping operation, the blade adjustment and variable-speed adjustment are the usual operation modes. By adjusting the blade angle [4,11] or rotational speed [12,13], the pump unit could adapt to the variation of head and flow in a larger scope, which makes the operation of pumping station in a high efficiency area. Optimal operation of single pumping station is mostly conditioned in a certain time period; the change range of the head meets certain requirements, to decrease the total cost of running power consumption to the minimum, thus adjusting the conditions of how to compose reasonably to head, flow, and power combination; therefore, optimal operation can be achieved.…”

“…Taking complex system theory into consideration, based on optimal operation of pumping station with single running condition [11,13], and the feasibility of dynamic programming method in solving complicated nonlinear problem with separable stages [18], and the applicability of experimental optimization theory in solving complicated nonlinear problems containing double decision variables [19], the study on optimal operation for single pumping station with combinatorial adjustment with adjustable blade and variable speed is carried out by means of combining experimental optimization method with decomposition-dynamic programming method.…”

Optimal Operation of a Single Unit with an Adjustable Blade in an Interbasin Water Transfer Pumping Station Based on Successive Approximation Discretization for Blade Angle

“…e reduction percentage of UMOC was 0.027%-0.408%, with an average reduction rate of 0.123%. Although these optimization effects are not significant enough, considering that the comparison reference is the result obtained from the first time of optimization that was already in an optimal operation mode, the optimization benefit can reach more than 7% compared with the working condition with the designed blade angle and rated speed for the single pump unit [24]. e absolute value of energy cost saving will be large if we consider the joint operation of multiple units of a single pumping station or parallel pumping stations and even the long-distance water transfer project with a long operating period.…”

“…Gong and Cheng [23] applied an experimental optimization method for a large-scale system to optimize the operation of a pumping station with adjustable blade and variable speed and obtained the unit power cost under different operation loads and daily average heads. Gong et al [24] proposed a decomposition-dynamic programming aggregation method that can solve the mathematical model of a single pumping station with different types of pump units installed. Makaremi et al [25] proposed a multiobjective optimization method that uses NSGA-II coupled with EPANET to optimize the energy cost and number of pump switches.…”