Management of grid-scale energy storage systems for multiple services

1. A computer implemented method for energy distribution for one or more grid-scale Energy Storage Systems (ESSs), comprising:

controlling, using a tertiary controller:

generating of one or more time series models to provide forecasted pricing data for one or more markets;

determining of battery life and degradation costs for one or more batteries in one or more ESSs to provide battery life and degradation costs, the degradation costs being determined for time step k as:

Cost( k )= C b |P b energy ( k )|+ C b P b reg (k),

where C b represents per unit degradation costs for the one or more ESSs, P b energy (k) represents power of the one or more ESSs for time step k, and P b reg (k) represents capacity of the one or more ESSs in a frequency regulation (FR) market; and

optimizing of bids for the one or more markets to generate optimal bids based on at least one of the forecasted pricing data or the battery life and degradation costs; and

controlling, using a primary controller, distributing of energy to or from the one or more ESSs based on the optimal bids, the primary controller being configured for:

regulating voltage at a point of connection to a power grid from the one or more ESSs, the regulating further comprising maintaining a stable voltage by controlling, using a reactive power controller, reactive power injection at one or more points of common coupling (PCCs) from the one or more ESSs to the power grid; and

controlling, using an active power controller, real-time charge and discharge commands based on the optimizing and regulating for real-time control of the one or more ESSs.

2. The method of claim 1 , wherein the one or more time series models include a Locational Marginal Price (LMP) time series model and a voltage regulation time series model.

3. The method of claim 1 , wherein the determining battery life and degradation costs is performed on an hourly basis for each of the one or more ESSs, wherein the determining further comprises generating an average model based on per unit degradation costs of each ESS multiplied by the energy throughput of the ESS.

4. The method of claim 1 , wherein the optimizing further comprises performing stochastic optimization to evaluate a cost tradeoff of providing energy services vs. battery life costs for a plurality of situations to determine an optimal battery dispatch, wherein the one or more markets include an energy market and a frequency market.

5. The method of claim 1 , wherein the controlling further comprises actively controlling power to dispatch ESSs automatically to maintain a system voltage within a normal range.

6. The method of claim 1 , wherein the regulating controls the one or more ESSs to reduce system loss and save energy using conservation voltage regulation (CVR).

7. The method of claim 1 , wherein the bids are day-ahead energy bids.

8. A system for energy distribution for one or more grid-scale Energy Storage Systems (ESSs), comprising:

a tertiary controller, comprising:

a forecaster, coupled to a bus, for generating one or more time series models to predict pricing data for one or more markets, with the one or more time series models being stored therein;

a determiner for providing battery life and degradation costs for one or more batteries in the one or more ESSs, the degradation costs being determined for time step k as:

Cost( k )= C b |P b energy ( k )|+ C b P b reg (k),

where C b represents per unit degradation costs for the one or more ESSs, p b energy (k) represents power of the one or more ESSs for time step k, and P b reg (k) represents capacity of the one or more ESSs in a frequency regulation (FR) market; and

an optimizer, coupled to the bus, for generating optimal bids for the one or more markets based on the pricing data or the battery life and degradation costs for the one or more ESSs; and

a primary controller for distributing energy to or from the one or more ESSs based on the optimal bids, the primary controller comprising:

a regulator coupled to the bus for voltage regulation at a point of connection to a power grid from the one or more ESSs, the regulator further comprising a reactive power controller configured to maintain a stable voltage by controlling reactive power injection at one or more points of common coupling (PCCs) from the system to the power grid; and

an active power control configured to generate and issue real-time charge and discharge commands based on the optimal bids and the voltage regulation for real-time control of the one or more ESSs.

9. The system of claim 8 , wherein the one or more time series models include a Locational Marginal Price (LMP) time series model and a voltage regulation time series model.

10. The system of claim 8 , wherein the determiner provides battery life and degradation costs on an hourly basis for each of the one or more ESSs, and the battery life and degradation costs are determined by generating an average model based on per unit degradation costs of each ESS multiplied by the energy throughput of the ESS.

11. The system of claim 8 , wherein the optimizer performs stochastic optimization to evaluate a cost tradeoff of providing energy services vs. battery life costs for a plurality of situations to determine an optimal battery dispatch.

12. The system of claim 8 , wherein the primary controller actively controls power to dispatch ESSs automatically to maintain system voltage within a normal range.

13. The system of claim 8 , wherein the regulator controls the one or more ESSs to reduce system loss and save energy using conservation voltage regulation (CVR).

14. The system of claim 8 , wherein the tertiary controller performs real-time system parameter identification to enable millisecond level control of voltage regulation by the primary controller.

15. A non-transitory computer-readable storage medium comprising a computer readable program for energy distribution for one or more grid-scale Energy Storage Systems (ESSs), wherein the computer readable program when executed on a computer causes the computer to perform the steps of:

controlling, using a tertiary controller:

generating of one or more time series models to provide forecasted pricing data for one or more markets;

determining of battery life and degradation costs for one or more batteries in or more ESSs to provide battery life and degradation costs, the degradation costs being determined for time step k as:

Cost( k )= C b |P b energy ( k )|+ C b P b reg (k),

where C b represents per unit degradation costs for the one or more ESSs, P b energy (k) represents power of the one or more ESSs for time step k, and P b reg (k) represents capacity of the one or more ESSs in a frequency regulation (FR) market; and

optimizing of bids for the one or more markets to generate optimal bids based on at least one of the forecasted pricing data or the battery life and degradation costs; and

controlling, using a primary controller, distributing of energy to or from the one or more ESSs based on the optimal bids, the primary controller being configured for:

regulating voltage at a point of connection to a power grid from the one or more ESSs, the regulating further comprising maintaining a stable voltage by controlling, using a reactive power controller, reactive power injection at one or more points of common coupling (PCCs) from the one or more ESSs to the power grid; and

controlling, using an active power controller, real-time charge and discharge commands based on the optimizing and regulating for real-time control of the one or more ESSs.

16. The non-transitory computer-readable storage medium of claim 15 , wherein the determining battery life and degradation costs is performed on an hourly basis for each of the one or more ESSs, and is determined by generating an average model based on per unit degradation costs of each ESS multiplied by the energy throughput of the ESS.