METHODS AND SYSTEMS FOR ENERGY MANAGEMENT AND OPTIMIZATION
A method includes monitoring, by an energy management system, a microgrid using multiple sensors associated with a utility grid, one or more power sources in the microgrid, and one or more load devices in the microgrid, and determining, by the energy management system, one or more load profiles corresponding to the one or more load devices based on measurements from the multiple sensors. The method also includes determining, a priority order of the one or more load devices in the microgrid based on the one or more load profiles corresponding to the one or more power sources, and dynamically connecting and disconnecting the one or more power sources and the one or more load devices based on a utility grid condition, available powers from the one or more power sources, the one or more load profiles, and the priority order of the one or more load devices.
1 . A method comprising:
monitoring, by an energy management system, a microgrid using multiple sensors associated with a utility grid, one or more power sources in the microgrid, and one or more load devices in the microgrid;
determining, by the energy management system, one or more load profiles corresponding to the one or more load devices in the microgrid based on measurements from the multiple sensors;
determining, by the energy management system, a priority order of the one or more load devices in the microgrid based on the one or more load profiles corresponding to the one or more power sources; and
dynamically connecting and disconnecting, by the energy management system, the one or more power sources and the one or more load devices based on a utility grid condition, available powers from the one or more power sources, the one or more load profiles, and the priority order of the one or more load devices.
2 . The method of claim 1 , wherein the one or more power sources comprise a set of solar panels connected to the energy management system via at least one microinverter, wherein the at least one microinverter is connected to at least one relay switch coupled with a current sensor and a voltage sensor, wherein the method further comprises:
determining an available power from the set of solar panels by communicating with the at least one microinverter and the current sensor and the voltage sensor coupled with the at least one relay switch connected to the at least one microinverter.
3 . The method of claim 2 , wherein the one or more power sources further comprises one or more batteries connected with the energy management system via bidirectional supply equipment, wherein the method further comprises:
enabling charging at least one of the one or more batteries in response to determining the available power from the set of solar panels in response to determining the available power from the set of solar panels is more than a total load value of the one or more load devices in the microgrid.
4 . The method of claim 3 , wherein enabling charging at least one of the one or more batteries comprises providing a predetermined current to at least one of the one or more batteries.
5 . The method of claim 3 , further comprising enabling discharging at least one of the one or more batteries to the microgrid in response to determining the available power from the set of solar panels is less than the total load value of the one or more load devices in the microgrid.
6 . The method of claim 5 , wherein enabling discharging at least one of the one or more batteries to the microgrid comprises providing a predetermined current to the microgrid from the at least one of the one or more batteries.
7 . The method of claim 1 , further comprising connecting an additional load device to the microgrid in response to determining a total available power from the one or more power sources is greater than a total load value of the one or more load devices in the microgrid.
8 . The method of claim 1 , further comprising disconnecting a load device to the microgrid based on the priority order of the one or more load devices, in response to determining a total available power from the one or more power sources is less than a total load value of the one or more load devices in the microgrid.
9 . The method of claim 1 , further comprising determining the priority order of the one or more load devices in the microgrid based on a user input.
10 . The method of claim 1 , further comprising:
determining a plurality of power consumption parameters associated with a load device based on the measurements collected during a predetermined time interval; and
determining a load profile for the load device based on the plurality of power consumption parameters using a machine learning model.
11 . The method of claim 1 , further comprising determining a load profile corresponding to a load device in the microgrid based on an identification of a load circuit in the microgrid comprising the load device.
12 . The method of claim 1 , further comprising:
monitoring a relay temperature associated with a relay switch using a temperature sensor;
determining a thermal trend based on the relay temperature over a predetermined period of time;
determining that a temperature increase associated with the relay switch during a predetermined period of time meets or exceeds a predetermined threshold;
based on determining that the temperature increase meets or exceeds the predetermined threshold, transmitting an alert message indicating an abnormal condition of the relay switch to a user device; and
opening the relay switch in response to determining the temperature increase associated with the relay switch during the predetermined period of time meets or exceeds the predetermined threshold.
13 . The method of claim 1 , further comprising calibrating relay switching time for opening or closing a relay switch based on (i) a control signal to open or close the relay switch, (ii) an estimated relay aging condition, and (iii) voltage and current data associated with the relay switch.
14 . The method of claim 1 , further comprising verifying periodically a capacity of a battery powering the energy management system by draining the battery and recharging the battery at a predetermined time interval.
15 . The method of claim 1 , further comprising identifying one or more phases that the one or more load devices are connected to respectively.
16 . A non-transitory computer-readable medium comprising program code that is executable by one or more processors to:
monitor a microgrid using multiple sensors, wherein the multiple sensors are associated with a utility grid, one or more power sources in the microgrid, and one or more load devices in the microgrid;
determine one or more load profiles corresponding to the one or more load devices in the microgrid based on measurements from the multiple sensors;
determine a priority order of the one or more load devices in the microgrid based on the one or more load profiles corresponding to the one or more power sources; and
dynamically connect and disconnect the one or more power sources and the one or more load devices based on a utility grid condition, available powers from the one or more power sources, the one or more load profiles, and the priority order of the one or more load devices.
17 . The non-transitory computer-readable medium of claim 16 , further comprising program code that is executable by the one or more processors to connect an additional load device to the microgrid in response to determining a total available power from the one or more power sources is greater than a total load value of the one or more load devices in the microgrid.
18 . The non-transitory computer-readable medium of claim 16 , further comprising program code that is executable by the one or more processors to disconnect a load device to the microgrid based on the priority order of the one or more load devices, in response to determining a total available power from the one or more power sources is less than a total load value of the one or more load devices in the microgrid.
19 . The non-transitory computer-readable medium of claim 16 , further comprising program code that is executable by the one or more processors to:
determine a plurality of power consumption parameters associated with a load device based on the measurements collected during a predetermined time interval; and
determine a load profile for the load device based on the plurality of power consumption parameters using a machine learning model.
20 . The non-transitory computer-readable medium of claim 16 , further comprising program code that is executable by the one or more processors to:
monitor a relay temperature associated with a relay switch using a temperature sensor;
determine a thermal trend based on the relay temperature over a period of time;
determine that a temperature increase associated with the relay switch during a predetermined period of time meets or exceeds a predetermined threshold;
based on determining that the temperature increase meets or exceeds the predetermined threshold, transmit an alert message indicating an abnormal condition of the relay switch to a user device; and
open the relay switch in response to determining the temperature increase associated with the relay switch during the predetermined period of time meets or exceeds the predetermined threshold.