# Soumyadip Ghosh, Peekskill US

## Soumyadip Ghosh, Peekskill, NY US

Patent application number | Description | Published |
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20110258087 | ANALYTICS FOR SETTING UP STRATEGIC INVENTORY SYSTEMS TO HANDLE SMALL LOT ORDERS IN THE STEEL INDUSTRY - A method of managing manufacturing production includes determining a plurality of products for manufacture using a production line is disclosed. Each product is specified by composition and production line steps and criteria. Production orders for products are analyzed to determine whether products should be grouped into product-types, and whether product (type) should be made-to-stock or made to order. Queuing theory based analytic methods and optimization based heuristics are used to determine the priority for each product in the production line, taking product substitution opportunities in batch-production into account. Preselected points along the production line are determined for gathering an amount of inventory for each product. This decision is made considering product-differentiation down the line. An established inventory policy for each product at preselected points along the production line requires that inventory is reviewed and an order is placed for additional inventory when on hand inventory reaches a predetermined reorder point. | 10-20-2011 |

20110282475 | EFFECTIVE CYCLE TIME MANAGEMENT EMPLOYING A MULTI-HORIZON MODEL - Cycle time and throughput of a manufacturing facility is effectively manages by a control system that employs a combination of a long-term horizon model and at least one short-term horizon model to generate control signals for a set of machines in a manufacturing facility. The long-term horizon model determines long-term average time allocation percentage for each machine for a given set of throughput targets and cycle time targets for products to be manufactured. Each of the at least one short-term horizon model determines queues for immediate use at processing tools, while the queues are subjected to a secondary adjustment based on the time allocation constraints generated by the long-term horizon model. The combination of the long-term and the at least one short-term horizon models provides a stable long-term proactive WIP bubble-management as well as short-term WIP bubble management. | 11-17-2011 |

20120078687 | SYSTEM AND METHOD FOR LOWEST COST AGGREGATE ENERGY DEMAND REDUCTION - A method, apparatus and computer program product for determining lowest cost aggregate energy demand reduction at multiple network levels such as distribution and feeder networks. An algorithm for an optimal incentive mechanism offered to energy customers (e.g. of a utility power entity) that accounts for heterogeneous customer flexibility in load reduction, with the demand response realized via the utility's rebate signal and, accounts for temporal aspects of demand shift in response for rebates. A mathematical formulation of a cost minimization problem is solved to provide incentives for customers to reduce their demand. A gradient descent algorithm is used to solve for the optimal incentives customized for individual end users. | 03-29-2012 |

20120185106 | INTEGRATION OF DEMAND RESPONSE AND RENEWABLE RESOURCES FOR POWER GENERATION MANAGEMENT - System and method of solving, in a single-period, an optimal dispatching problem for a network of energy generators connected via multiple transmission lines, where it is sought to find the lowest operational cost of dispatching of various energy sources to satisfy demand. The model includes traditional thermal resources and renewable energy resources available generation capabilities within the grid. The method considers demand reduction as a virtual generation source that can be dispatched quickly to hedge against the risk of unforeseen shortfall in supply. Demand reduction is dispatched in response to incentive signals sent to consumers. The control options of the optimization model consist of the dispatching order and dispatching amount energy units at generators together with the rebate signals sent to end-users at each node of the network under a demand response policy. Numerical experiments based on an analysis of representative data illustrate the effectiveness of demand response as a hedging option. | 07-19-2012 |

20120185406 | FAST AND ACCURATE METHOD FOR ESTIMATING PORTFOLIO CVaR RISK - A method, system and computer program product for measuring a risk of an asset portfolio. The system estimates a β-level CVaR (Conditional Value-at-Risk) of the asset portfolio by modeling interdependencies between assets in the asset portfolio. The modeling is based on Gaussian copula model. | 07-19-2012 |

20130018700 | OPTIMIZING PRODUCT PORTFOLIOS UNDER CUSTOMER CHOICEAANM Ervolina; Thomas R.AACI PoughquagAAST NYAACO USAAGP Ervolina; Thomas R. Poughquag NY USAANM Ettl; Markus R.AACI OssiningAAST NYAACO USAAGP Ettl; Markus R. Ossining NY USAANM Ghosh; SoumyadipAACI PeekSkillAAST NYAACO USAAGP Ghosh; Soumyadip PeekSkill NY USAANM Gresh; Donna LeighAACI Cortlandt ManorAAST NYAACO USAAGP Gresh; Donna Leigh Cortlandt Manor NY USAANM Oh; SechanAACI StanfordAAST CTAACO USAAGP Oh; Sechan Stanford CT US - A method and system are disclosed for managing configurable products via solving an optimization problem. In one embodiment, the method comprises collecting data from a software application and a user; formulating a set of constraints based on the collected data; defining the optimization problem by the set of constraints and an optimization objective; solving the optimization problem using the collected data, the set of constraints, the optimization objective and the objective function via mixed integer programming; and outputting a solution of the optimization problem. | 01-17-2013 |

20130018829 | MANAGING CAPACITIES AND STRUCTURES IN STOCHASTIC NETWORKSAANM Dieker; Antonius B.AACI AtlantaAAST GAAACO USAAGP Dieker; Antonius B. Atlanta GA USAANM Ghosh; SoumyadipAACI PeekskillAAST NYAACO USAAGP Ghosh; Soumyadip Peekskill NY USAANM Squillante; Mark S.AACI Pound RidgeAAST NYAACO USAAGP Squillante; Mark S. Pound Ridge NY US - A system, method and computer program product for managing capacities and structures in a stochastic network. The method includes mapping the stochastic network to a general analytic model, e.g., a Brownian model, decomposing the general analytic model of the stochastic network into a set of smaller general analytic models, determining the capacities/structures for the set of analytic models as an intermediate solution for the capacities/structures of the stochastic network; and, determining the capacities/structures for the stochastic network starting at the intermediate solution for the capacities/structures using simulation-based methods. | 01-17-2013 |

20130173493 | OPTIMIZING PROCUREMENT SPEND COMPLIANCE - Managing spend compliance may include receiving a set of spend transaction records containing one or more spend attributes, one or more compliance business rules and one or more investment scenarios that increase spend compliance. The compliance business rules may be applied to the transaction records and segments of transactions with predetermined high savings opportunities may be determined. A prioritized investment plan over one or more time periods that yield optimized return on investment may be generated based on applying the segments of transactions and the investment scenarios. | 07-04-2013 |

20130238530 | SYSTEMS AND METHODS FOR GENERATING WIND POWER SCENARIOS FOR WIND-POWER-INTEGRATED STOCHASTIC UNIT COMMITMENT PROBLEMS - The present disclosure relates generally to systematic algorithms (and associated systems and methods) that take a forecast model as input and produce a discrete probability distribution as output, using scenario reduction ideas from stochastic programming. In one example, an algorithm (and associated system and method) creates scenarios sequentially for each time period, leading to a scenario tree. | 09-12-2013 |

20140025351 | PLANNING ECONOMIC ENERGY DISPATCH IN ELECTRICAL GRID UNDER UNCERTAINTY - A method for solving a two-stage non-linear stochastic formulation for the economic dispatch problem under renewable-generation uncertainty. Certain generation decisions are made only in the first stage and fixed for the subsequent (second) stage, where the actual renewable generation is realized. The uncertainty in renewable output is captured by a finite number of scenarios. Any resulting supply-demand mis-match must then be alleviated using high marginal-cost power sources that can be tapped in short time frames. The solution implements two outer approximation algorithms to solve this nonconvex optimization problem to optimality. Under certain conditions the sequence of optimal solutions obtained under both alternatives has a limit point that is a globally-optimal solution to the original two-stage nonconvex program. A further decomposition approach derived from the Alternating Direction Method of Multipliers algorithm is implemented. | 01-23-2014 |

20140025352 | PLANNING ECONOMIC ENERGY DISPATCH IN ELECTRICAL GRID UNDER UNCERTAINTY - A method for solving a two-stage non-linear stochastic formulation for the economic dispatch problem under renewable-generation uncertainty. Certain generation decisions are made only in the first stage and fixed for the subsequent (second) stage, where the actual renewable generation is realized. The uncertainty in renewable output is captured by a finite number of scenarios. Any resulting supply-demand mis-match must then be alleviated using high marginal-cost power sources that can be tapped in short time frames. The solution implements two outer approximation algorithms to solve this nonconvex optimization problem to optimality. Under certain conditions the sequence of optimal solutions obtained under both alternatives has a limit point that is a globally-optimal solution to the original two-stage nonconvex program. A further decomposition approach derived from the Alternating Direction Method of Multipliers algorithm is implemented. | 01-23-2014 |

20140266041 | DISTRIBUTED CHARGING OF ELECTRICAL ASSETS - The present disclosure relates generally to the field of distributed charging of electrical assets. In various examples, distributed charging of electrical assets may be implemented in the form of systems, methods and/or algorithms. | 09-18-2014 |

20140324532 | SYSTEM AND METHOD FOR MODELING AND FORECASTING CYCLICAL DEMAND SYSTEMS WITH DYNAMIC CONTROLS AND DYNAMIC INCENTIVES - Systems and methods for modeling and forecasting cyclical demand systems in the presence of dynamic control or dynamic incentives. A method for modeling a cyclical demand system comprises obtaining historical data on one or more demand measurements over a plurality of demand cycles, obtaining historical data on incentive signals over the plurality of demand cycles, constructing a model using the obtained historical data on the one or more demand measurements and the incentive signals, wherein constructing the model comprises specifying a state-space model, specifying variance parameters in the model, and estimating unknown variance parameters. | 10-30-2014 |

20140365022 | Managing Time-Substitutable Electricity Usage using Dynamic Controls - A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives. | 12-11-2014 |

20140365024 | Managing Time-Substitutable Electricity Usage using Dynamic Controls - A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives. | 12-11-2014 |