AC connected modules with line frequency or voltage variation pattern for energy control
A control strategy for distributed power generation modules in a power system that varies the line frequency or voltage according to a predetermined pattern to cause a PV inverter to modify its power output and thereby avoid overcharging a battery. When the power system operates in islanded mode, the AC load demand can be lower than the available energy from the PV array, causing the battery to become overcharged. To avoid this scenario, a hybrid inverter executes a pattern generator algorithm that varies the line frequency or voltage linearly, exponentially or any mathematical function or look-up tables. The PV inverter executes a pattern detection algorithm that detects the linear, exponential, or any mathematical function or look-up table change in the line frequency. In response, the PV inverter modifies its power output until an overcharging condition of the battery is removed. The line frequency/voltage can be varied within the anti-islanding limits.
1. A method of automatically controlling a current or voltage applied to a battery by monitoring a characteristic of an alternating current (AC) line, comprising:
determining, in a first module, whether a monitored current or voltage of the battery satisfies a predetermined criterion;
responsive to the current or voltage of the battery satisfying the criterion, automatically changing via the first module the characteristic of the AC line using a pattern generator algorithm that produces a modified output that varies the characteristic of the AC line according to a first predetermined pattern that is produced by a first function, wherein the first module includes a first controller programmed with machine-readable instructions for carrying out the generator pattern algorithm and is electrically coupled to the battery and to at least one source of AC energy; and
detecting, at a second module remote from the first module via a pattern detection algorithm, the modified output, and, responsive to the detecting, causing the current or voltage applied to the battery for charging the battery to be changed via the first module, wherein the second module includes a second controller programmed with machine-readable instructions for carrying out the pattern detection algorithm and is electrically coupled to the first module.
2. The method of claim 1 , wherein the characteristic is a frequency or a voltage of the AC line.
3. The method of claim 1 , wherein the criterion is whether the current or voltage of the battery exceeds a predetermined current or voltage.
4. The method of claim 1 , wherein the criterion is whether the current or voltage of the battery falls below a predetermined current or voltage.
5. The method of claim 1 , wherein the first module includes a hybrid converter for providing and receiving energy.
6. The method of claim 1 , wherein the second module is coupled to a renewable energy conversion unit that converts a source of renewable energy into electricity.
7. The method of claim 1 , wherein the second module includes a photovoltaic inverter that receives solar energy from a photovoltaic array coupled to the second module and outputs a corresponding AC current.
8. The method of claim 1 , wherein the characteristic is varied within an anti-islanding limit of the AC line, wherein the AC line is rated to oscillate at a fundamental frequency, and wherein the anti-islanding limit does not exceed 2 Hz above or below the fundamental frequency.
9. The method of claim 8 , wherein the anti-islanding limit is within a defined anti-islanding limit in the Underwriters Laboratory (UL) 1741 or the Institute of Electrical and Electronics Engineers (IEEE) 1547.
10. The method of claim 1 , wherein the first function includes an exponential function.
11. The method of claim 1 , wherein the first function includes a linear function.
12. The method of claim 1 , wherein the first function includes a linear-exponential function.
13. The method of claim 1 , wherein the characteristic of the AC line is varied first according to the first predetermined pattern and second according to a second predetermined pattern that is produced by a second function that differs from the first function.
14. The method of claim 1 , wherein the pattern detection algorithm includes a wavelet transform function, a PID, fuzzy logic, or a Fast Fourier Transform.
15. The method of claim 1 , wherein the source of AC energy is a utility grid or a distributed generator system (genset).
16. The method of claim 2 , wherein the criterion is whether the current or voltage of the battery falls outside of a predetermined range of current or voltage, wherein the first module includes a hybrid converter that provides and receives energy, wherein the second module is coupled to a renewable energy conversion unit that converts a source of renewable energy into electricity, wherein the second module includes a photovoltaic inverter or converter that receives solar energy from a photovoltaic array coupled to the second module and outputs a corresponding current, and wherein the first function includes an exponential function, a linear function, or a linear-exponential function.
17. The method of claim 16 , wherein the source of AC energy is a utility grid or a distributed generator system (genset).
18. The method of claim 17 , wherein the characteristic is varied within an anti-islanding limit of the AC line, wherein the AC line oscillates at a fundamental frequency, and wherein the anti-islanding limit does not exceed one hertz above or below the fundamental frequency.
19. The method of claim 18 , wherein the pattern detection algorithm includes a wavelet transform function.