Sewage flow optimization algorithm for large-scale urban sewer networks based on network community division

By considering the flow control of urban sewer networks to minimize the electricity consumption of pumping stations, a decomposition-coordination strategy for energy savings based on network community division is developed in this paper. A mathematical model characterizing the steady-state flow of urban sewer networks is first constructed, consisting of a set of algebraic equations with the structure transportation capacities captured as constraints. Since the sewer networks have no apparent natural hierarchical structure in general, it is very difficult to identify the clustered groups. A fast network division approach through calculating the betweenness of each edge is successfully applied to identify the groups and a sewer network with arbitrary configuration could be then decomposed into subnetworks. By integrating the coupling constraints of the subnetworks, the original problem is separated into N optimization subproblems in accordance with the network decomposition. Each subproblem is solved locally and the solutions to the subproblems are coordinated to form an appropriate global solution. Finally, an application to a specified large-scale sewer network is also investigated to demonstrate the validity of the proposed algorithm.

Multi-boiler System Optimization in Integrated Steelworks Based on Decomposition and Coordination Method

As for the existing problems of boilers in integrated steelworks, the multi-boiler system could be quantitatively optimized with the decomposition and coordination method. Then, case studies were carried out based on the data of an integrated steelworks. Two groups of actual production records were contrastively analyzed, and the calculation results from the optimized program of these two groups indicated that for groups 1 and 2, the costs fall by 5.06% and 3.79%and the fuel consumptions decrease by 2.72% and 1.45%, respectively, compared with the actual data. To analyze the cost and fuel consumption change under the same condition of total load demand, assigned fuel consumption and water temperature, five sets of data were selected for further analysis. It was shown that the total cost and fuel consumption of the optimized program could fall by 3.5% and 1.6% respectively, compared with the actual production records. The optimal allocation significantly contributed to energy conservation and cost reduction. The effects of the system energy conservation cannot be realized by single equipment energy conservation. They were complementary to each other, and should be put on the same stage.

FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION:THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturing scheduling and supply chain coordination are critical to quickly respond to changing market conditions. These problems, however, are difficult in view of inherent complexity and various uncertainties involved. Based on a series of results by the authors, decomposition and coordination by using Lagrangian relaxation is identified in this paper as an effective way to control complexity and uncertainty. A manufacturing scheduling problem is first formulated within the job shop context with uncertain order arrivals, processing times, due dates, and part priorities as a separable optimization problem. A solution methodology that combines Lagrangian relaxation, stochastic dynamic programming, and heuristics is developed. Method improvements to effectively solve large problems are also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomic members across chains of suppliers, a decentralized supply chain model is established in the second half of this paper. By relaxing cross-member constraints, the model is decomposed into member-wise subproblems, and a nested optimization structure is developed based on the job shop scheduling results. Coordination is performed through the iterative updating of cross-member prices without accessing other members' private information or intruding their decision-making authorities, either with or without a coordinator. Two examples are presented to demonstrate the effectiveness of the method. Future prospects to overcome problem inseparability and improve computing efficiency are then discussed.

Multi-area Generation-reserve Joint Dispatch Approach Considering Wind Power Cross-regional Accommodation

This paper presents a study on how to accommodate wind power into multiple regions,while simultaneously implementing economic and reliable dispatch for multi-area power system operation.The focus is on quantifying the operational risk brought by wind power uncertainty and at the same time accommodating wind power by coordinating multi-area generation and reserve resources.The reserve requirement of each area is calculated based on two indexes,namely,loss of load probability and wind spillage probability.Then,a generation-reserve cooptimization dispatch model that factors cross-regional wind power accommodation is proposed.The transmission margin and network security constraints of tie-lines are considered to systematically allocate reserve resources for all areas.Finally,optimality condition decomposition is used to decompose the dispatching model to achieve relatively independent regional scheduling,and to get the global optimization result.The reasonableness and effectiveness of the proposed approach is validated by a 6-bus 2-area test system and a 236-bus interconnected system.