Research On Hierarchical And Distributed Cooperative Scheduling Optimization Method For Smart Pumping Station Group In Small Watershed

Drainage and irrigation pumping stations are widely used in China as important hydraulic infrastructure for drainage,irrigation,flood control and ecological protection.With the vigorous development of pumping station energy-saving renovation project and the increasing demand for irrigation and drainage,the number of smart pumping stations in small watersheds is increasing.A large number of decentralized smart pumping stations in small watersheds need group cooperative dispatching operation to take into account the requirements of irrigation and drainage tasks and operation economy.The lack of effective group cooperative operation in flood season emergencies may cause hidden dangers of river dam collapse.The cooperative dispatching of large-scale smart pumping stations is a complex problem involving multiple pumping stations,multiple units and multiple energy systems,which contains multiple constraints.Under this background,this paper studies the hierarchical distributed collaborative scheduling optimization method of small watershed intelligent pumping station group.The main research work is as follows:(1)A multi-unit coordinated scheduling model and stochastic optimization method for smart pumping station with photovoltaic power generation are proposed.By optimizing the pumping flow of each pump unit in different periods,the daily power consumption cost of the pumping station is reduced.Firstly,the unit model of irrigation and drainage pumping station is established.In the model,the influence of the speed change of the pump unit on the performance parameters of the pump such as flow,shaft power,efficiency and head is considered,and the uncertainty of photovoltaic power generation is simulated by multi-scenario analysis technology.On this basis,the proposed stochastic optimization method considers the time-of-use electricity price,takes the minimum daily electricity cost of pumping station as the objective function,and takes the safe operation conditions of pumping station and the requirements of drainage and irrigation tasks as the constraints for scheduling optimization.The example shows that the method can reasonably allocate the pumping flow of each pump unit in different periods and reduce the daily power consumption cost of the pumping station.(2)A hierarchical collaborative scheduling optimization architecture and method of smart pumping station group considering the layout characteristics of small watershed pumping stations are proposed.The complexity of the cooperative scheduling problem is reduced by the interactive optimization of the pumping station control layer and the pumping station group system layer.The control layer of pumping station considers the constraint of river water flow during irrigation period,and the information of power surplus and vacancy after independent dispatching optimization is transmitted to the management layer of pumping station group system through inter-layer interaction mechanism.The system layer considers the power balance constraint of pumping station group,and optimizes the power trading between pumping stations and power grid with the lowest daily operation cost of pumping station group.The simulation example shows that this method can effectively solve the collaborative scheduling problem of large-scale pumping stations and avoid the problem of insufficient water supply in the downstream of the river during the irrigation period.(3)A distributed collaborative scheduling optimization method of smart pumping station group based on Lagrange relaxation is proposed.The data communication burden of pumping station group is reduced by transforming the centralized collaborative scheduling optimization problem of pumping station group into the distributed optimization problem of regional autonomy.The proposed method considers the constraint of river water flow in flood season,decomposes the global constraint in the problem by Lagrangian relaxation method,and obtains the sub-problem of pump station scheduling with local and low complexity.Each pump station optimizes the pumping flow of each pump unit independently,and the key information is shared only by the central control system of the pump station group.The simulation example shows that this method can realize the distribution autonomy of pumping station group,reduce the data communication burden of pumping station group,and avoid the hidden danger of dam break in flood season.In summary,this paper studies the hierarchical distributed collaborative scheduling optimization method of large-scale smart pumping stations in small watersheds.On the basis of meeting the requirements of pumping station drainage and irrigation tasks,it reduces the operation cost of pumping station groups,alleviates the communication pressure,and avoids the hidden danger of dam failure in flood season.