Abstract: A near-optimal scheduling system for considering processing-time variations and real-time data streaming includes a data parser module, a publish subscribe mechanism module, a processing time prediction module and a scheduling optimization module. In the processing time prediction module, an orthogonal greedy algorithm and a recurrent neural network are used to extract key features and then predict varying operation processing time. By formulating the scheduling problem in an integer programming form, an ordinal-optimization (OO) embedded decomposition and coordination method is established in the scheduling optimization module to provide dynamic and near-optimal schedules in a computationally efficient manner. Moreover, a publish subscribe mechanism is developed in the publish subscribe mechanism module by using subscribe and publish methods to realize real-time needs.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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 (24) in which the objective is to improve performance for customers. To solve the snapshot problem (24), the objective function is transformed into a form to facilitate the decomposition of the problem into individual car subproblems (26). The subproblems (26) are independently solved using a two-level formulation, with passenger to car assignment (28) at the higher level, and the dispatching of individual cars (30) at the lower level. Near-optimal passenger selection and individual car routing (38) are obtained. The individual cars are then coordinated through an iterative process (40, 42) to arrive at a group control solution that achieves a near-optimal result for passengers.

Abstract: 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 (24) in which the objective is to improve performance for customers. To solve the snapshot problem (24), the objective function is transformed into a form to facilitate the decomposition of the problem into individual car subproblems (26). The subproblems (26) are independently solved using a two-level formulation, with passenger to car assignment (28) at the higher level, and the dispatching of individual cars (30) at the lower level. Near-optimal passenger selection and individual car routing (38) are obtained. The individual cars are then coordinated through an iterative process (40, 42) to arrive at a group control solution that achieves a near-optimal result for passengers.

Abstract: 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 (24) in which the objective is to improve performance for customers. To solve the snapshot problem (24), the objective function is transformed into a form to facilitate the decomposition of the problem into individual car subproblems (26). The subproblems (26) are independently solved using a two-level formulation, with passenger to car assignment (28) at the higher level, and the dispatching of individual cars (30) at the lower level. Near-optimal passenger selection and individual car routing (38) are obtained. The individual cars are then coordinated through an iterative process (40, 42) to arrive at a group control solution that achieves a near-optimal result for passengers.

Abstract: 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.

Abstract: A near-optimal scheduling method for a group of elevators uses advanced traffic information. More particularly, advanced 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.

Abstract: 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.