System and method for minimizing storage demand charges by weight assignments to different demand categories
Systems and methods for minimizing demand charges includes generating historical demand profiles having a plurality of demand charge threshold (DCT) values over a period of time, filtering the DCT values using weighting factors to provide filtered DCT values such that DCT underestimations and overestimations are removed from optimization, determining an optimal DCT output value from the filtered DCT values such that the optimal DCT output value is based on the historical demand profiles and the weighting factors, and distributing energy in one or more batteries in accordance with the optimal DCT output value and current energy demand to minimize energy and demand charges.
1. A method for minimizing demand charges, comprising:
generating historical demand profiles having a plurality of demand charge threshold (DCT) values over a period of time;
filtering the DCT values using weighting factors to provide filtered DCT values such that DCT underestimations and overestimations are removed from optimization;
determining an optimal DCT output value from the filtered DCT values such that the optimal DCT output value is based on the historical demand profiles and the weighting factors; and
distributing energy in one or more batteries in accordance with the optimal DCT output value and current energy demand to minimize energy and demand charges;
wherein filtering the DCT values includes:
classifying the plurality of DCT values into a plurality of sub-categories based on threshold values; and
assigning a weighting factor to each of the plurality of DCT values, wherein the weighting factor for each of the plurality of DCT values is different than each other; and
wherein classifying the plurality of DCT values includes sub-dividing the plurality of DCT values into one of a low-demand category, mid-demand category, and high demand category;
and assigning a weighting factor includes assigning a first weight value for DCT values in the low-demand category, assigning a second weight value for DCT values in the mid-demand category, and assigning a third weight value for DCT values in the high-demand category, wherein the third weight value is greater than the first weight value and less than the second weight value.
2. A system for minimizing demand charges, comprising:
a processor coupled to a memory, the processor being configured to:
generate historical demand profiles having a plurality of demand charge threshold (DCT) values over a period of time;
filter the DCT values using weighting factors to provide filtered DCT values such that DCT underestimations and overestimations are removed from optimization;
determine an optimal DCT output value from the filtered DCT values such that the optimal DCT output value is based on the historical demand profiles and the weighting factors; and
distribute energy in one or more batteries in accordance with the optimal DCT output value and current energy demand to minimize energy and demand charges;
wherein the processor is further configured to:
classify the plurality of DCT values into a plurality of sub-categories based on threshold values; and
assign a weighting factor to each of the plurality of DCT values, wherein the weighting factor for each of the plurality of DCT values is different than each other; and
wherein the processor is further configured to:
sub-divide the plurality of DCT values into one of a low-demand category, mid-demand category, and high demand category; and
assign a first weight value for DCT values in the low-demand category, assign a second weight value for DCT values in the mid-demand category, and assign a third weight value for DCT values in the high-demand category, wherein the third weight value is greater than the first weight value and less than the second weight value.
3. A non-transitory computer readable storage medium comprising a computer readable program for minimizing demand charges, wherein the computer readable program when executed on a computer causes the computer to perform a method for minimizing demand charges, the method comprising:
generating historical demand profiles having a plurality of demand charge threshold (DCT) values over a period of time;
filtering the DCT values using weighting factors to provide filtered DCT values such that DCT underestimations and overestimations are removed from optimization;
determining an optimal DCT output value from the filtered DCT values such that the optimal DCT output value is based on the historical demand profiles and the weighting factors; and
distributing energy in one or more batteries in accordance with the optimal DCT output value and current energy demand to minimize energy and demand charges;
wherein filtering the DCT values includes:
classifying the plurality of DCT values into a plurality of sub-categories based on threshold values; and
assigning a weighting factor to each of the plurality of DCT values, wherein the weighting factor for each of the plurality of DCT values is different than each other; and
wherein classifying the plurality of DCT values includes sub-dividing the plurality of DCT values into one of a low-demand category, mid-demand category, and high demand category; and
assigning a weighting factor includes assigning a first weight value for DCT values in the low-demand category, assigning a second weight value for DCT values in the mid-demand category, and assigning a third weight value for DCT values in the high-demand category, wherein the third weight value is greater than the first weight value and less than the second weight value.