University of Connecticut

Otis Elevator Company

Southern California Edison Company

Peter B Luh

Arthur Hsu

Yanyuan Qin

Bing Wang

Mauro Jorge Atalla

Lingyu Ren

Gregory G Luther

Peng Zhang

Bo Xiong

Robert N Tomastik

Gary A Stern

William E Blankson

Ernan Ni

Joseph H Yan

Ying Chen

Feng Zhao

Yaming Ma

Systems and methods for integrating ultra-fast programmable networks in microgrid are disclosed to provide flexible and easy-to-manage communication solutions, thus enabling resilient microgrid operations in face of various cyber and physical disturbances. The system is configured to establish a novel software-defined networking (SDN) based communication architecture which abstracts the network infrastructure from the upper-level applications to significantly expedite the development of microgrid applications, develop three functions of the SDN controller for microgrid emergency operations, including time delay guarantee, failover reconfiguration and rate limit and create a hardware-in-the-loop cyber-physical platform for evaluating and validating the performance of the presented architecture and control techniques.

Enabling resilient microgrid through ultra-fast programmable network

A near-optimal scheduling method for a group of elevators uses advance traffic information. More particularly, advance traffic information is used to define a snapshot problem () in which the objective is to improve performance for customers. To solve the snapshot problem (), the objective function is transformed into a form to facilitate the decomposition of the problem into individual car subproblems (). The subproblems () are independently solved using a two-level formulation, with passenger to car assignment () at the higher level, and the dispatching of individual cars () at the lower level. Near-optimal passenger selection and individual car routing () are obtained. The individual cars are then coordinated through an iterative process () to arrive at a group control solution that achieves a near-optimal result for passengers.

Group elevator scheduling with advance traffic information

A method for determining a market clearing price ('MCP') in an electricity market, in which an objective function relates the MCP and constraints in terms of a nonlinear programming expression, and the MCP is found by resolving an augmented Lagrangian dual function using a surrogate optimization framework. A system is also provided.

Simultaneous optimal auctions using augmented lagrangian and surrogate optimization

A method and system for scheduling using a facet ascending algorithm or a reduced complexity bundle method for solving an integer programming problem is presented. A Lagrangian dual function of an integer scheduling problem is maximized (for a primal minimization problem) to obtain a good near-feasible solution, and to provide a lower bound to the optimal value of the original problem. The dual function is a polyhedral concave function made up of many facets. The facet ascending algorithm of the present invention exploits the polyhedral concave nature of the dual function by ascending facets along intersections of facets. At each iteration, the algorithm finds the facets that intersect at the current dual point, calculates a direction of ascent along these facets, and then performs a specialized line search which optimizes a scaler polyhedral concave function in a finite number of steps. An improved version of the facet ascending algorithm, the reduced complexity bundle method, maximizes a nonsmooth concave function of variables. This is accomplished by finding a hyperplane separating the origin and the affine manifold of a polyhedron. The hyperplane also separates the origin and the polyhedron since the polyhedron is a subset of its affine manifold. Then an element of the bundle is projected onto the subspace normal to the affine manifold to produce a trial direction normal. If the projection is zero (i.e., indicating the affine manifold contains the origin), a re-projection onto the subspace normal to the affine manifold of an appropriate face of the polyhedron gives a trial direction. This reduced complexity bundle method always finds an .epsilon.-ascent trial direction or detects an .epsilon.-optimal point, thus maintaining global convergence. The method can be used to maximize the dual function of a mixed-integer scheduling problem.

Method and system for scheduling using a facet ascending algorithm or a

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Storrs, CT, United States of America

Peter B Luh