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11.发明申请公开(公告)号：US20150095000A1
公开(公告)日：2015-04-02
申请号：US14504166
申请日：2014-10-01
Applicant: NEC Laboratories America, Inc.
Inventor： Rakesh Patil , Huazhen Fang , Ratnesh Sharma
CPC classification number: G06F17/5004 , G06F2217/80
Abstract: A method of determining the location of actuators and sensors for climate control that includes providing a model of temperature and airflow within a room. A matrix for the placement of sensors is calculated using a Lyapunov equation. A Lyapunov equation includes a matrix for the transition state from the model of temperature and airflow. A trace of the matrix for the placement of sensors is maximized to provide optimum placement of the sensors. A matrix for the placement of actuators within the model is calculated using the Lyapunov equation. A variable for the Lyapunov equation includes the matrix for the transition state obtained from the model of temperature and airflow. A trace of the matrix for the placement of actuators is maximized to provide optimum placement of the actuators within the room.
Abstract translation: 确定用于气候控制的致动器和传感器的位置的方法，其包括在室内提供温度和气流的模型。 使用Lyapunov方程计算用于放置传感器的矩阵。 Lyapunov方程包括从温度和气流模型的过渡状态的矩阵。 用于放置传感器的矩阵的轨迹最大化，以提供传感器的最佳布置。 使用Lyapunov方程计算用于在模型内放置致动器的矩阵。 Lyapunov方程的变量包括从温度和气流模型获得的过渡态的矩阵。 用于放置致动器的矩阵的轨迹被最大化以提供致动器在房间内的最佳布置。
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12.发明申请Computer Implemented Method for Diagnositc Analytics for Battery Life Management 审中-公开电池寿命管理诊断分析计算机实现方法公开(公告)号：US20140088897A1
公开(公告)日：2014-03-27
申请号：US14038530
申请日：2013-09-26
Applicant: NEC LABORATORIES AMERICA, INC.
Inventor： Ratnesh Sharma , Krishnamurthy Dvijotham
CPC classification number: G01R31/382 , G01R31/367 , G01R31/3842 , G01R31/392 , G06F17/5018
Abstract: A computer implemented method combines a simplified equivalent circuit model with a model capturing the variation of the circuit parameters. The components of the equivalent circuit model depend on the internal battery state, and the parameters of the model encode this dependence. The invention then uses actual operational data capturing various modes of operation of the battery and different discharge rates to fit the model parameters (rather than controlled laboratory tests used in previous work). Once this analysis is done (offline), the model can be used in an online phase to adjust estimates of the internal battery state as the battery is operating.
Abstract translation: 计算机实现的方法将简化的等效电路模型与捕获电路参数的变化的模型相结合。 等效电路模型的组件取决于内部电池状态，并且模型的参数对该依赖性进行编码。 然后，本发明使用捕获电池的各种操作模式的实际操作数据和不同的放电速率来适应模型参数（而不是以前的工作中使用的受控实验室测试）。 一旦分析完成（离线），该模型可以在在线阶段用于调整电池运行时内部电池状态的估计。
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公开(公告)号：US10673242B2
公开(公告)日：2020-06-02
申请号：US16185373
申请日：2018-11-09
Applicant: NEC Laboratories America, Inc.
Inventor： Kiyoshi Nakayama , Ratnesh Sharma , Ali Hooshmand
IPC: H02J3/32 , G06Q10/06 , G06Q50/06 , G05B13/04 , H02J13/00 , G06Q30/04 , H02J3/38 , H02J7/00 , H02J3/00 , G05B13/02
Abstract: Systems and methods for controlling battery charge levels to maximize savings in a behind the meter energy management system include predicting a demand charge threshold with a power demand management controller based on historical load. A net energy demand is predicted for a current day with a short-term forecaster. A demand threshold maximizes financial savings using the net energy demand using a rolling time horizon optimizer by concurrently optimizing the demand charge savings and demand response rewards. A load reduction capability factor of batteries is determined with a real-time controller corresponding to an amount of energy to fulfill the demand response rewards. The net energy demand is compared with the demand threshold to determine a demand difference. Battery charge levels of the one or more batteries are controlled with the real time controller according to the demand difference and the load reduction capability factor.
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公开(公告)号：US20190288513A1
公开(公告)日：2019-09-19
申请号：US16257399
申请日：2019-01-25
Applicant: NEC Laboratories America, Inc.
Inventor： Kiyoshi Nakayama , Ratnesh Sharma
Abstract: A system and methods are provided for a decentralized transactive energy management. The method includes calculating, by a processor-device, power balancing at one of a plurality of nodes responsive to current statistics at the one of a plurality of nodes. The method also includes estimating, by the processor-device, a present energy demand for the one of a plurality of nodes responsive to the current statistics. The method additionally includes obtaining, by the processor-device, an amount of excess energy available another of the plurality of nodes. The method further includes optimizing, by the processor-device, a power flow between the one of the plurality of nodes and the another of the plurality of nodes to satisfy the present energy demand for the one of the plurality of nodes. The method also includes transferring the excess energy from the another of the plurality of nodes to the one of the plurality of nodes.
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公开(公告)号：US20190148945A1
公开(公告)日：2019-05-16
申请号：US16185300
申请日：2018-11-09
Applicant: NEC Laboratories America, Inc.
Inventor： Kiyoshi Nakayama , Ratnesh Sharma , Ali Hooshmand
Abstract: Systems and methods for controlling battery charge levels to maximize savings in a behind the meter energy management system include predicting a demand charge threshold with a power demand management controller based on historical load. A net energy demand is predicted for a current day with a short-term forecaster. A demand threshold maximizes financial savings using the net energy demand using a rolling time horizon optimizer by concurrently optimizing the demand charge savings and demand response rewards. A load reduction capability factor of batteries is determined with a real-time controller corresponding to an amount of energy to fulfill the demand response rewards. The net energy demand is compared with the demand threshold to determine a demand difference. Battery charge levels of the one or more batteries are controlled with the real time controller according to the demand difference and the load reduction capability factor.
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Patent Agency Ranking
公开(公告)号：US20190147552A1
公开(公告)日：2019-05-16
申请号：US16185373
申请日：2018-11-09
Applicant: NEC Laboratories America, Inc.
Inventor： Kiyoshi Nakayama , Ratnesh Sharma , Ali Hooshmand
Abstract: Systems and methods for controlling battery charge levels to maximize savings in a behind the meter energy management system include predicting a demand charge threshold with a power demand management controller based on historical load. A net energy demand is predicted for a current day with a short-term forecaster. A demand threshold maximizes financial savings using the net energy demand using a rolling time horizon optimizer by concurrently optimizing the demand charge savings and demand response rewards. A load reduction capability factor of batteries is determined with a real-time controller corresponding to an amount of energy to fulfill the demand response rewards. The net energy demand is compared with the demand threshold to determine a demand difference. Battery charge levels of the one or more batteries are controlled with the real time controller according to the demand difference and the load reduction capability factor.
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公开(公告)号：US20190137956A1
公开(公告)日：2019-05-09
申请号：US16180493
申请日：2018-11-05
Applicant: NEC Laboratories America, Inc.
Inventor： Ali Hooshmand , Ratnesh Sharma , Korosh Vatanparver
Abstract: Systems and methods for controlling behind-the meter energy storage/management systems (EMSs) to maximize battery lifetime, including determining optimal monthly demand charge thresholds based on a received customer load profile, battery manufacturer specifications, and battery operating conditions and parameters. The determining of the monthly demand charge threshold includes iteratively performing daily optimizations to determine battery utilization, and minimize demand charge for each day for the load profile. A battery lifetime is predicted based on manufacturer specifications and utilization determined by the daily optimizations. A battery capacity retention value and battery capacity loss are determined based on an annual discharged energy (AADE) and an average battery state-of-charge (SoC). An optimal monthly demand threshold is selected based on the predicted battery lifetime and demand charge utilization. EMS operations are controlled by tuning the battery parameters to provide maximum demand charge and battery lifetime for the customer load profile using a real-time controller.
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公开(公告)号：US20190131923A1
公开(公告)日：2019-05-02
申请号：US16173265
申请日：2018-10-29
Applicant: NEC Laboratories America, Inc.
Inventor： Ali Hooshmand , Ratnesh Sharma , Mohammad Ehsan Raoufat , Ramin Moslemi
Abstract: A computer-implemented method is provided for controlling a Battery Energy Storage System (BESS) having a battery set and connected to a Photovoltaic (PV) panel set. The method includes enforcing, by a processor device, a multi-objective Model Predictive Control (MPC) optimization on the BESS. The multi-objective MPC optimization includes a first objective of reducing a possibility of Demand Charge Threshold violations by minimal DCT increments which provide a higher demand charge savings, a second objective of improving a robustness of the BESS against energy forecast errors by increasing a State Of Charge (SOC) of the battery set, and a third objective of maximizing PV-utilization. The method further includes controlling, by the processor device, charging and discharging of the BESS in accordance with the multi-objective MPC optimization to meet the first, second, and third objectives.
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公开(公告)号：US10234886B2
公开(公告)日：2019-03-19
申请号：US15228670
申请日：2016-08-04
Applicant: NEC Laboratories America, Inc.
Inventor： Babak Asghari , Ratnesh Sharma , Amirsaman Arabali
Abstract: A system and method for management of one or more grid-scale Energy Storage Systems (GSSs), including generating an optimal GSS schedule in the presence of frequency regulation uncertainties. The GSS scheduling includes determining optimal capacity deployment factors to minimize penalties for failing to provide scheduled energy and frequency regulation up/down services subject to risk constraints; generating a schedule for a GSS unit by performing co-optimization using the optimal capacity deployment factors, the co-optimization including tracking upper and/or lower bounds on a state of charge (SoC) and including the bounds as a hard constraints; and calculating risk indices based on the optimal scheduling for the GSS unit, and outputting an optimal GSS schedule if risk constraints are satisfied. A controller charges and/or discharges energy from GSS units based on the generated optimal GSS schedule.
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公开(公告)号：US20190056451A1
公开(公告)日：2019-02-21
申请号：US16103970
申请日：2018-08-16
Applicant: NEC Laboratories America, Inc.
Inventor： Babak Asghari , Ratnesh Sharma , Mohammad Ehsan Raoufat
Abstract: Systems and methods for controlling Battery Energy Storage Systems (BESSs), including determining historical minimum state of charge (SOC) for peak shaving of a previous day based on historical photovoltaic (PV)/load profiles, historical demand charge thresholds (DCT), and battery capacity of the BESSs. A minimum SOC for successful peak shaving of a next day is estimated by generating a weighted average based on the historical minimum SOC, and optimal charging/discharging profiles for predetermined intervals are generated based on estimated PV/load profiles for a next selected time period and grid feed-in limitations. Continuous optimal charging/discharging functions are provided for the one or more BESSs using a real-time controller configured for overriding the optimal charging/discharging profiles when at least one of a high excess PV generation, a peak shaving event, or a feed-in limit violation is detected.
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