Abstract: Accurate real-time monitoring of distribution networks becomes increasingly pivotal to ensure reliable and optimal operation of grid. Existing joint parameter-state estimation techniques predominantly focus on transmission systems, making their applicability to distribution systems challenging due to variations in available input data. Furthermore, the joint estimation techniques significantly suffer from computational complexity. Present disclosure provides a method and a system for personalized multi-subject text to image generation. The system first uses lossy Distflow equations and an inverse Physics-Informed Neural Network (iPINN) architecture for learning network voltage dynamics, drift matrix and network bus voltages from real-time bus power injection data and historical voltage data. Thereafter, the system determines a plurality of line parameters from the learnt drift matrix using a least-square optimization technique.

Abstract: Power systems mainly focuses on uncertainties such as load variations, renewable energy sources, electricity price variability etc., but a gap exists in formulating and solving Portfolio Optimization (PO) problem considering inter multi-energy market price vulnerabilities. The present disclosure receives an energy volume generated by a plurality of energy generation systems. Further, a current market price value is predicted and an expected revenue for each of the plurality of energy generation systems is computed. Simultaneously, an energy generation cost, an energy conversion cost is computed, and an energy storage cost are computed. Further, a market price variation risk associated with each of the plurality of multi-energy day-ahead markets is computed. Further, a market price risk forecast is computed.

Abstract: This disclosure relates generally to method and system of generating optimal portfolio for seller bidding strategy in decoupled multi-energy markets. Energy sellers generate multiple forms of energy and can trade in specific energy markets by maximizing returns and minimizing risk of price fluctuations. Portfolio optimization across multi-energy markets lacks proper consideration of inter energy conversion efficiencies, market price risks, and asset constraints. The present disclosure provides to multi-energy markets prior to bidding day at least one energy type available with a seller, a bidding price of corresponding energy type, and at least one energy type required by a market participant to generate an optimal portfolio. The seller determines a risk factor for energy type in the multi-energy markets and then computes a total risk for each energy type. The optimal portfolio splits the generated volume of each energy type to bid at every timeslot of the multi-energy markets.

Abstract: This disclosure relates generally to performing user segmentation, and more particularly to predicting attribute values for user segmentation. In one embodiment, the method includes segregating a user with an incomplete attribute value and a user with complete attribute values for an attribute into a first group and a second group respectively, computing prior probability for each suggestive attribute value, identified for the incomplete attribute value, based on number of users in second group having the suggestive attribute value as attribute value for the attribute. Computing likelihood for each suggestive attribute value based on similarity of the attribute values of the user of the first group with users of the second group, computing a posterior probability for each suggestive attribute value based on the prior probability and the likelihood, selecting a suggestive attribute value with the highest posterior probability as the attribute value for the incomplete attribute value of the user.

Abstract: Described herein, is a method for user segmentation for cost-based deployment of enterprise infrastructure. According to an implementation, for each of the users, a user fingerprint (UFP) score set comprising rating scores that quantify levels of enterprise-level needs of the each user is determined. For each of deployment solutions of the enterprise, a deployment fingerprint (DFP) score set comprising rating scores that quantify levels of capabilities of the each deployment solution enabled to meet enterprise-level needs of the users is determined. The users are grouped into user segments based on the UFP score sets of the users. A definition of each of the user segments is determined. The definition is indicative of a user whose enterprise-level needs define characteristics of the corresponding user segment. A number of user segments is found based on a cost associated with the deployment solutions for the user segments.

Abstract: The present invention relates to a configurable parameter driven system and method for providing an appropriate target operating environment based on user specific needs and enterprise objectives. The configuration parameters can be changed to account for newer computing environment solutions that could appear and could also be tailored for enterprise specific needs. The method fingerprint the end users' based on characteristics and requirements to derive user needs and enterprise criteria's. The method is systematic and flexible amenable to change in varying enterprise environment.

Abstract: Methods and systems for Assurance-enabled Linde Buzo Gray (ALBG) data clustering is described herein. In an implementation, a user model data from a database available to the processor is obtained. The user model data comprises data elements or users, each of which corresponds to features and feature values associated with the users. These data elements of the user model data are segmented into clusters using our segmentation approach with an initial accuracy criterion parametric value and the output is captured as segment data. The segment data output is checked for initial pareto validity. If successful, iterative segmentation run with incremental accuracy criterion using parameterized value is performed till the segmented clusters are determined valid against pareto validity check. The last successful pareto valid segmented cluster data is considered as the finalized segment output data.

Abstract: This disclosure relates generally to performing user segmentation, and more particularly to predicting attribute values for user segmentation. In one embodiment, the method includes segregating a user with an incomplete attribute value and a user with complete attribute values for an attribute into a first group and a second group respectively, computing prior probability for each suggestive attribute value, identified for the incomplete attribute value, based on number of users in second group having the suggestive attribute value as attribute value for the attribute. Computing likelihood for each suggestive attribute value based on similarity of the attribute values of the user of the first group with users of the second group, computing a posterior probability for each suggestive attribute value based on the prior probability and the likelihood, selecting a suggestive attribute value with the highest posterior probability as the attribute value for the incomplete attribute value of the user.

Abstract: Methods and systems for Assurance-enabled Linde Buzo Gray (ALBG) data clustering is described herein. In an implementation, a user model data from a database available to the processor is obtained. The user model data comprises data elements or users, each of which corresponds to features and feature values associated with the users. These data elements of the user model data are segmented into clusters using our segmentation approach with an initial accuracy criterion parametric value and the output is captured as segment data. The segment data output is checked for initial pareto validity. If successful, iterative segmentation run with incremental accuracy criterion using parameterized value is performed till the segmented clusters are determined valid against pareto validity check. The last successful pareto valid segmented cluster data is considered as the finalized segment output data.

Abstract: Described herein, is a method for user segmentation for cost-based deployment of enterprise infrastructure. According to an implementation, for each of the users, a user fingerprint (UFP) score set comprising rating scores that quantify levels of enterprise-level needs of the each user is determined. For each of deployment solutions of the enterprise, a deployment fingerprint (DFP) score set comprising rating scores that quantify levels of capabilities of the each deployment solution enabled to meet enterprise-level needs of the users is determined. The users are grouped into user segments based on the UFP score sets of the users. A definition of each of the user segments is determined. The definition is indicative of a user whose enterprise-level needs define characteristics of the corresponding user segment. A number of user segments is found based on a cost associated with the deployment solutions for the user segments.

Abstract: The present invention relates to a configurable parameter driven system and method for providing an appropriate target operating environment based on user specific needs and enterprise objectives. The configuration parameters can be changed to account for newer computing environment solutions that could appear and could also be tailored for enterprise specific needs. The method fingerprint the end users' based on characteristics and requirements to derive user needs and enterprise criteria's. The method is systematic and flexible amenable to change in varying enterprise environment.

Abstract: The present invention relates to a simple, economical, and efficient cyclic process for producing rhombic dodecahedron shaped glycine enriched, free flowing common salt from brine, said process comprising steps of adding glycine of concentration ranging between 10 to 25% to the saturated bnne, evaporating the saturated brine containing glycine to obtain crystals having high content of glycine, with mother liquor, washing the crystals with saturated brine to obtain rhombic dodecahedron shaped glycine enriched common salt having glycine content ranging between 0.5 to 1.0% and a washed brine, combining the mother liquor and the washed brine to obtain resulting brine, subjecting the resultant brine to solar evaporation, and repeating the steps of (iii) to (v) to obtain rhombic dodecahedron shaped glycine enriched common salt from brine with glycine concentration ranging between 0.5 to 1.0%.