Patents by Inventor Srinarayana NAGARATHINAM

Srinarayana NAGARATHINAM has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240167713
    Abstract: Use of Physics Informed Neural networks (PINNs) to control building systems is non-trivial, as basic formalism of PINNs is not readily amenable to control problems. Specifically, exogenous inputs (e.g., ambient temperature) and control decisions (e.g., mass flow rates) need to be specified as functional inputs to the neural network, which may not be known a priori. The input feature space could be very high dimensional depending upon the duration (monthly, yearly, etc.) and the (min-max) range of the inputs. The disclosure herein generally relates to Heating, Ventilation, and Air-Conditioning (HVAC) equipment, and, more particularly, to method and system for physics aware control of HVAC equipment. The system generates a neural network model based on a plurality of exogeneous variables from the HVAC. The generated neural network model is then used to generate the one or more control signal recommendations, which are further used to control operation of the HVAC.
    Type: Application
    Filed: October 31, 2023
    Publication date: May 23, 2024
    Applicant: Tata Consultancy Services Limited
    Inventors: SRINARAYANA NAGARATHINAM, YASHOVARDHAN SUSHIL CHATI, ARUNCHANDAR VASAN, MALINI POONI VENKAT
  • Patent number: 11781773
    Abstract: This disclosure relates generally to method and system for maximizing space utilization in a building. Due to current pandemic scenario many organizations eventually need to plan for the return of employees to office space ensuring biosafety. The challenge of maximizing the office space utilization ensuring occupants biosafety and comfort thereby minimizing HVAC energy consumption is necessary. The method utilizes two heuristic approaches for determining maximum allowable occupants placement in the open plan space using an optimal occupant placement technique. This minimizes the HVAC energy if the actual count is lesser than the possible maximum occupants can be placed which further optimizes energy using a joint actuator control technique. Additionally, the proposed two heuristic approaches improve space utilization for the infection rate ensuring bio safety.
    Type: Grant
    Filed: March 9, 2021
    Date of Patent: October 10, 2023
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Praveen Manoharan, Srinarayana Nagarathinam, Arunchandar Vasan, Venkata Ramakrishna Padullaparthi
  • Publication number: 20230125620
    Abstract: HVAC control system's supervisory control is crucial for energy-efficient thermal comfort in buildings. The control logic is usually specified as ‘if-then-that-else’ rules that capture the domain expertise of HVAC operators, but they often have conflict that may lead to sub-optimal HVAC performance. Embodiments of the present disclosure provide a method and system for optimized Heating, ventilation, and air-conditioning (HVAC) control using domain knowledge combined with Deep Reinforcement Learning (DRL). The system disclosed utilizes Deep Reinforcement Learning (DRL) for conflict resolution in a HVAC control in combination with domain knowledge in form of control logic. The domain knowledge is predefined in an Expressive Decision Tables (EDT) engine via a formal requirement specifier consumable by the EDT engine to capture domain knowledge of a building for the HVAC control.
    Type: Application
    Filed: September 26, 2022
    Publication date: April 27, 2023
    Applicant: Tata Consultancy Services Limited
    Inventors: SAGAR KUMAR VERMA, SUPRIYA AGRAWAL, VENKATESH RAMANATHAN, ULKA SHROTRI, SRINARAYANA NAGARATHINAM, RAJESH JAYAPRAKASH, AABRITI DUTTA
  • Patent number: 11609156
    Abstract: Traditionally, benchmarking of asset performance involves comparing actual performance with ideal values that correspond to test conditions which may not be realized in practice leading to inappropriate ranking of the assets. Systems and methods of the present disclosure use condition-aware reference curves for estimating the maximum possible operating efficiencies (under specific operating conditions) instead of the theoretical maximum efficiencies. The reference curves are received from the manufacturer or obtained from on-site test results. Benchmarking is then performed based on two dimensions, viz., an inter-asset metric and an intra-asset metric that are analogous to the first law and second law of thermodynamics respectively. The two-dimensional benchmarking then helps in identifying inefficient assets that may be analyzed further for finding the root cause.
    Type: Grant
    Filed: September 20, 2019
    Date of Patent: March 21, 2023
    Assignee: TATA CONSULTANCY SERVICES LIMITED
    Inventors: Srinarayana Nagarathinam, Venkata Ramakrishna P, Arunchandar Vasan, Venkatesh Sarangan, Anand Sivasubramaniam
  • Patent number: 11579576
    Abstract: Sub-systems of air handling units in infrastructures face unresolved problem of conflict in the rules that activate in a contradictory manner at the same time resulting in sub-optimal performance of the subsystems. The present disclosure provides a system and method for optimizing performance parameters of air handling units in infrastructures. Rule sets having conflicting conditions are identified after verification of rules which are specific to air handling units. Further, frequency of the rule sets having conflicting conditions is determined to generate a ranked list of the rule sets having conflicting conditions. Another ranking procedure is implemented for the rules comprised in the ranked list of the rule sets having conflicting conditions. The system dynamically optimizes one or more parameters specific to the performance criteria based on the ranking of rules.
    Type: Grant
    Filed: January 28, 2020
    Date of Patent: February 14, 2023
    Assignee: Tata Consultancy Services Limited
    Inventors: Supriya Agrawal, Sagar Verma, Ramasubramanian Suriyanarayanan, Srinarayana Nagarathinam, Rajesh Jayaprakash, Venkatesh Ramanathan, Anand Sivasubramaniam
  • Publication number: 20220154958
    Abstract: This disclosure relates generally to method and system for maximizing space utilization in a building. Due to current pandemic scenario many organizations eventually need to plan for the return of employees to office space ensuring biosafety. The challenge of maximizing the office space utilization ensuring occupants biosafety and comfort thereby minimizing HVAC energy consumption is necessary. The method utilizes two heuristic approaches for determining maximum allowable occupants placement in the open plan space using an optimal occupant placement technique. This minimizes the HVAC energy if the actual count is lesser than the possible maximum occupants can be placed which further optimizes energy using a joint actuator control technique. Additionally, the proposed two heuristic approaches improve space utilization for the infection rate ensuring bio safety.
    Type: Application
    Filed: March 9, 2021
    Publication date: May 19, 2022
    Applicant: Tata Consultancy Services Limited
    Inventors: Praveen MANOHARAN, Srinarayana NAGARATHINAM, Arunchandar VASAN, Venkata Ramakrishna PADULLAPARTHI
  • Patent number: 11301941
    Abstract: Electrical utilities offer incentives to customers to reduce consumption during periods of demand-supply mismatch. A building's participation in demand response (DR) depends both on its ability (due to building constraints), and its willingness (a function of incentive) to reduce electricity. Customers prefer a large incentive whereas a utility would want to minimize the revenue outflow to achieve a target reduction. Systems and methods of the present disclosure identify optimal incentive from the utility's perspective reflecting this trade-off. A model is built to estimate the demand response potential (DRP) of a building for a given incentive offered by the utility. The models for individual buildings are used to characterize the behavior of an ensemble of buildings. The utility may then decide optimum incentives that should be offered to achieve a target DR, using the associated DRP.
    Type: Grant
    Filed: November 6, 2017
    Date of Patent: April 12, 2022
    Assignee: Tata Consultancy Services Limited
    Inventors: Kundan Kandhway, Arunchandar Vasan, Srinarayana Nagarathinam, Venkatesh Sarangan, Anand Sivasubramaniam
  • Patent number: 11268723
    Abstract: The present disclosure provides system and method for determining optimal decision parameters for a demand response (DR) event involving a District Cooling Plant (DCP). Most of conventional DR event techniques address control of building-level energy consumption loads alone while in presence of District Cooling (DC) has not received much attention when a plurality of buildings are served by a District Cooling Plant (DCP). The disclosed system and method determine set points of optimal decision parameters of the plurality of buildings and the DCP, by conditioning and un-conditioning on the DCP parameters such that a thermal discomfort of occupants residing in the plurality of buildings is minimum and achieves a maximum target energy demand reduction during the DR event. The disclosed system and method work for hundreds of buildings and able to determine the optimal decision parameters for each building and the DCP efficiently.
    Type: Grant
    Filed: February 18, 2020
    Date of Patent: March 8, 2022
    Assignee: Tata Consultancy Services Limited
    Inventors: Srinarayana Nagarathinam, Harihara Subramaniam Muralidharan, Arunchandar Vasan, Venkatesh Sarangan, Anand Sivasubramaniam
  • Publication number: 20210303998
    Abstract: Conventionally, chiller power consumption has been optimized by using Cooling Load based Control (CLC) approach which does not consider impact of a control strategy on other. Embodiments of the present disclosure provide reinforcement learning based control strategy to perform both chiller ON/OFF sequencing as well as setpoint leaving chilled water temperature (LCWT) scheduling. A RL agent is trained using a re-trained transfer learning (TL) model and LCWT, return chilled water temperature of target chillers and ambient temperature of building are read for determining required cooling load to be provided by target chiller(s) based on which target chillers are scheduled for turning ON/OFF. Transfer learning-based approach is implemented by present disclosure to predict power consumed by a chiller at some setpoint by using a model trained on similar chillers which were operated at that setpoint since chillers are usually run at a single setpoint.
    Type: Application
    Filed: December 29, 2020
    Publication date: September 30, 2021
    Applicant: Tata Consultancy Services Limited
    Inventors: Praveen MANOHARAN, Malini POONI VENKAT, Srinarayana NAGARATHINAM, Arunchandar VASAN
  • Patent number: 11102250
    Abstract: Identifying policy violations for controlling behavior of an Internet of Things (IoT) automation system is provided. Traditional systems and methods provide for controlling IoT based automation system based upon a static analysis of a system model and rules. The embodiments of the proposed disclosure provide for controlling behavior of the IoT automation system by identifying one or more policy violations, wherein the one or more policy violations are identified by generating a plurality of models representing behavior, relationships and functions of one or more sub-systems corresponding to the IoT automation system; extracting a set of modelled rules; constructing, using each of the plurality of models and the set of modelled rules, an integrated model; and identifying, from the integrated model, the one or more policy violations via a Model Verifier Component for controlling behavior of the IoT automation system.
    Type: Grant
    Filed: February 26, 2019
    Date of Patent: August 24, 2021
    Assignee: Tata Consultancy Services Limited
    Inventors: Rajesh Jayaprakash, Srinarayana Nagarathinam, Venkatesh Ramanathan, Ramasubramanian Suriyanarayanan, Anand Sivasubramaniam
  • Publication number: 20210200163
    Abstract: Reinforcement Learning agent interacting with a real-world building to determine optimal policy may not be viable due to comfort constraints. Embodiments of the present disclosure provide multi-deep agent RL for dynamically controlling electrical equipment in buildings, wherein a simulation model is generated using design specification of (i) controllable electrical equipment (or subsystem) and (ii) building. Each RL agent is trained using simulation model and deployed in the subsystem. Reward function for each subsystem includes some portion of reward from other subsystem(s). Based on reward function of each RL agent, each RL agent learns an optimal control parameter during execution of RL agent in subsystem. Further, a global optimal control parameter list is generated using the optimal control parameter. The control parameters in the global optimal control parameters list are fine-tuned to improve subsystem's performance.
    Type: Application
    Filed: September 23, 2020
    Publication date: July 1, 2021
    Applicant: Tata Consultancy Services Limited
    Inventors: Srinarayana NAGARATHINAM, Avinash ACHAR, Arunchandar VASAN
  • Patent number: 11016464
    Abstract: This disclosure relates generally to a system and method to identify at least one conflict and for controlling both static and dynamic variables in one or more operations of at least one subsystem of a plurality of building automation sub-systems. It includes a supervisory control layer that orchestrates multiple underlying sub-systems like heating, ventilation, and air-conditioning (HVAC) sub-systems and at least one access control sub-system. A test case generation framework is used to verify static and dynamic variables of operations of the sub-systems. It identifies conflicts in the static and dynamic variables. Therefore, the system provides controls to the sub-systems using the identified and adjusted conflict of static and dynamic variables on operations.
    Type: Grant
    Filed: July 9, 2019
    Date of Patent: May 25, 2021
    Assignee: Tata Consultancy Limited Services
    Inventors: Rajesh Jayaprakash, Srinarayana Nagarathinam, Supriya Agrawal, Ramasubramanian Suriyanarayanan, Anand Sivasubramaniam
  • Publication number: 20200263893
    Abstract: The present disclosure provides system and method for determining optimal decision parameters for a demand response (DR) event involving a District Cooling Plant (DCP). Most of conventional DR event techniques address control of building-level energy consumption loads alone while in presence of District Cooling (DC) has not received much attention when a plurality of buildings are served by a District Cooling Plant (DCP). The disclosed system and method determine set points of optimal decision parameters of the plurality of buildings and the DCP, by conditioning and un-conditioning on the DCP parameters such that a thermal discomfort of occupants residing in the plurality of buildings is minimum and achieves a maximum target energy demand reduction during the DR event. The disclosed system and method work for hundreds of buildings and able to determine the optimal decision parameters for each building and the DCP efficiently.
    Type: Application
    Filed: February 18, 2020
    Publication date: August 20, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Srinarayana NAGARATHINAM, Harihara Subramaniam MURALIDHARAN, Arunchandar VASAN, Venkatesh SARANGAN, Anand SIVASUBRAMANIAM
  • Publication number: 20200249645
    Abstract: Sub-systems of air handling units in infrastructures face unresolved problem of conflict in the rules that activate in a contradictory manner at the same time resulting in sub-optimal performance of the subsystems. The present disclosure provides a system and method for optimizing performance parameters of air handling units in infrastructures. Rule sets having conflicting conditions are identified after verification of rules which are specific to air handling units. Further, frequency of the rule sets having conflicting conditions is determined to generate a ranked list of the rule sets having conflicting conditions. Another ranking procedure is implemented for the rules comprised in the ranked list of the rule sets having conflicting conditions. The system dynamically optimizes one or more parameters specific to the performance criteria based on the ranking of rules.
    Type: Application
    Filed: January 28, 2020
    Publication date: August 6, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Supriya AGRAWAL, Sagar VERMA, Ramasubramanian SURIYANARAYANAN, Srinarayana NAGARATHINAM, Rajesh JAYAPRAKASH, Venkatesh RAMANATHAN, Anand SIVASUBRAMANIAM
  • Publication number: 20200112588
    Abstract: Identifying policy violations for controlling behavior of an Internet of Things (IoT) automation system is provided. Traditional systems and methods provide for controlling IoT based automation system based upon a static analysis of a system model and rules. The embodiments of the proposed disclosure provide for controlling behavior of the IoT automation system by identifying one or more policy violations, wherein the one or more policy violations are identified by generating a plurality of models representing behavior, relationships and functions of one or more sub-systems corresponding to the IoT automation system; extracting a set of modelled rules; constructing, using each of the plurality of models and the set of modelled rules, an integrated model; and identifying, from the integrated model, the one or more policy violations via a Model Verifier Component for controlling behavior of the IoT automation system.
    Type: Application
    Filed: February 26, 2019
    Publication date: April 9, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Rajesh JAYAPRAKASH, Srinarayana NAGARATHINAM, Venkatesh RAMANATHAN, Ramasubramanian SURIYANARAYANAN, Anand SIVASUBRAMANIAM
  • Publication number: 20200096421
    Abstract: Traditionally, benchmarking of asset performance involves comparing actual performance with ideal values that correspond to test conditions which may not be realized in practice leading to inappropriate ranking of the assets. Systems and methods of the present disclosure use condition-aware reference curves for estimating the maximum possible operating efficiencies (under specific operating conditions) instead of the theoretical maximum efficiencies. The reference curves are received from the manufacturer or obtained from on-site test results. Benchmarking is then performed based on two dimensions, viz., an inter-asset metric and an intra-asset metric that are analogous to the first law and second law of thermodynamics respectively. The two-dimensional benchmarking then helps in identifying inefficient assets that may be analyzed further for finding the root cause.
    Type: Application
    Filed: September 20, 2019
    Publication date: March 26, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: SRINARAYANA NAGARATHINAM, VENKATA RAMAKRISHNA P, ARUNCHANDAR VASAN, VENKATESH SARANGAN, ANAND SIVASUBRAMANIAM
  • Publication number: 20200064800
    Abstract: This disclosure relates generally to a system and method to identify at least one conflict and for controlling both static and dynamic variables in one or more operations of at least one subsystem of a plurality of building automation sub-systems. It includes a supervisory control layer that orchestrates multiple underlying sub-systems like heating, ventilation, and air-conditioning (HVAC) sub-systems and at least one access control sub-system. A test case generation framework is used to verify static and dynamic variables of operations of the sub-systems. It identifies conflicts in the static and dynamic variables. Therefore, the system provides controls to the sub-systems using the identified and adjusted conflict of static and dynamic variables on operations.
    Type: Application
    Filed: July 9, 2019
    Publication date: February 27, 2020
    Applicant: Tata Consultancy Services Limited
    Inventors: Rajesh JAYAPRAKASH, Srinarayana NAGARATHINAM, Supriya AGRAWAL, Ramasubramanian SURIYANARAYANAN, Anand SIVASUBRAMANIAM
  • Patent number: 10444712
    Abstract: A system and method for optimizing energy consumption in a plurality of air handling units (AHUs) in a zone is provided. The system comprising a zone thermal unit that is configured to obtain a first set of input parameters including an internal heat gains, a surface convective loads, an intra-zone mixing, a supply air temperature, a second set of input parameters including internal moisture gains, a supply humidity ratio, and a third set of input parameters including an air contaminant concentration and an ambient contaminant concentration of the AHUs and generates a first set of output parameters including a zone temperature, a humidity ratio and an air concentration. The system further includes an optimizer that is configured to generate a second set of output parameters including an optimum combination of AHU flow rates for the AHUs based on at least one of the first set of output parameters.
    Type: Grant
    Filed: July 12, 2016
    Date of Patent: October 15, 2019
    Assignee: Tata Consultancy Services Limited
    Inventors: Srinarayana Nagarathinam, Shiva R Iyer, Venkata Ramakrishna P, Arunchandar Vasan, Venkatesh Sarangan, Anand Sivasubramaniam
  • Publication number: 20180357730
    Abstract: Electrical utilities offer incentives to customers to reduce consumption during periods of demand-supply mismatch. A building's participation in demand response (DR) depends both on its ability (due to building constraints), and its willingness (a function of incentive) to reduce electricity. Customers prefer a large incentive whereas a utility would want to minimize the revenue outflow to achieve a target reduction. Systems and methods of the present disclosure identify optimal incentive from the utility's perspective reflecting this trade-off. A model is built to estimate the demand response potential (DRP) of a building for a given incentive offered by the utility. The models for individual buildings are used to characterize the behavior of an ensemble of buildings. The utility may then decide optimum incentives that should be offered to achieve a target DR, using the associated DRP.
    Type: Application
    Filed: November 6, 2017
    Publication date: December 13, 2018
    Applicant: Tata Consultancy Services Limited
    Inventors: Kundan KANDHWAY, Arunchandar VASAN, Srinarayana NAGARATHINAM, Venkatesh SARANGAN, Anand SIVASUBRAMANIAM
  • Publication number: 20170016644
    Abstract: A system and method for optimizing energy consumption in a plurality of air handling units (AHUs) in a zone is provided. The system comprising a zone thermal unit that is configured to obtain a first set of input parameters including an internal heat gains, a surface convective loads, an intra-zone mixing, a supply air temperature, a second set of input parameters including internal moisture gains, a supply humidity ratio, and a third set of input parameters including an air contaminant concentration and an ambient contaminant concentration of the AHUs and generates a first set of output parameters including a zone temperature, a humidity ratio and an air concentration. The system further includes an optimizer that is configured to generate a second set of output parameters including an optimum combination of AHU flow rates for the AHUs based on at least one of the first set of output parameters.
    Type: Application
    Filed: July 12, 2016
    Publication date: January 19, 2017
    Inventors: Srinarayana NAGARATHINAM, Shiva R. Iyer, Venkata Ramakrishna P, Arunchandar Vasan, Venkatesh Sarangan, Anand Sivasubramaniam