-
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.
-
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.
-
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.
-
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.
-
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.
-
Patent Agency Ranking
16.发明授权Method for efficiency-driven operation of dispatchable sources and storage units in energy systems 有权能源系统中调度源和存储单元的效率驱动运行方法公开(公告)号：US09450417B2
公开(公告)日：2016-09-20
申请号：US14093511
申请日：2013-12-01
Applicant: NEC Laboratories America, Inc.
Inventor： Babak Asghari , Ratnesh K. Sharma , Ali Hooshmand
CPC classification number: H02J3/46 , G06Q10/06315 , G06Q50/06 , H02J3/32 , H02J2003/146
Abstract: The invention is directed to a method or management system which 1) dispatches high efficiency generators first, 2) charges/discharges energy storage units in a way to enhance efficiency of generators in the system or avoid the necessity of dispatching generators during their low efficiency operations at all. In this way the method or management system utilizes its knowledge about the efficiency characteristics of generators in the system and its ability to change the net demand seen by the generators through charge and discharge of energy storage units to increase the overall efficiency of the energy system.
Abstract translation: 本发明涉及一种方法或管理系统，该方法或管理系统首先分派高效率发电机，2）以提高系统中发电机效率的方式对能量存储单元进行充电/放电，或避免在其低效率运行期间调度发电机的必要性 在所有 以这种方式，方法或管理系统利用其关于系统中发电机的效率特性的知识，以及通过能量存储单元的充放电来改变发电机所看到的净需求的能力，以提高能量系统的整体效率。
-
公开(公告)号：US20140058571A1
公开(公告)日：2014-02-27
申请号：US13858033
申请日：2013-04-06
Applicant: NEC LABORATORIES AMERICA, INC.
Inventor： Ali Hooshmand , Ratnesh Sharma , Babak Asghari
IPC: G05B15/02
CPC classification number: G05B15/02 , H02J3/00 , H02J2003/003 , Y04S10/54
Abstract: Systems and methods are disclosed for multi-objective energy management of micro-grids. A two-layer control method is used. In the first layer which is the advisory layer, a Model Predictive Control (MPC) method is used as a long term scheduler. The result of this layer will be used as optimality constraints in the second layer. In the second layer, a real-time controller guarantees a second-by-second balance between supply and demand subject to the constraints provided by the advisory layer.
Abstract translation: 公开了用于微网格的多目标能量管理的系统和方法。 使用两层控制方法。 在作为建议层的第一层中，使用模型预测控制（MPC）作为长期调度器。 该层的结果将被用作第二层中的最优约束。 在第二层中，实时控制器保证在咨询层提供的约束条件下，供应和需求之间的二阶平衡。
-
公开(公告)号：US10673241B2
公开(公告)日：2020-06-02
申请号：US16185300
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.
-
公开(公告)号：US20190257886A1
公开(公告)日：2019-08-22
申请号：US16273505
申请日：2019-02-12
Applicant: NEC Laboratories America, Inc.
Inventor： Ali Hooshmand , Mehdi Assefi , Ratnesh Sharma
IPC: G01R31/367 , G06N3/08 , G06N3/04 , G06F17/18 , G06N20/20 , G01R31/382 , H01M10/42
Abstract: A computer-implemented method predicting a life span of a battery storage unit by employing a deep neural network is presented. The method includes collecting energy consumption data from one or more electricity meters installed in a structure, analyzing, via a data processing component, the energy consumption data, removing one or more features extracted from the energy consumption data via a feature engineering component, partitioning the energy consumption data via a data partitioning component, and predicting battery capacity of the battery storage unit via a neural network component sequentially executing three machine learning techniques.
-
公开(公告)号：US10333306B2
公开(公告)日：2019-06-25
申请号：US15833301
申请日：2017-12-06
Applicant: NEC Laboratories America, Inc.
Inventor： Ali Hooshmand , Ratnesh Sharma , Ramin Moslemi
Abstract: A computer-implemented method, system, and computer program product are provided for demand charge management. The method includes receiving an active power demand for a facility, a current load demand charge threshold (DCT) profile for the facility, and a plurality of previously observed load DCT profiles. The method also includes generating a data set of DCT values based on the current load DCT profile for the facility and the plurality of previously observed load DCT profiles. The method additionally includes forecasting a next month DCT value for the facility using the data set of DCT values. The method further includes preventing actual power used from a utility from exceeding the next month DCT value by discharging a battery storage system into a behind the meter power infrastructure for the facility.
-
-
-
-
-
-
-
-
-
Search Results
31
records
(took 0.022 seconds)
