CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the priority of Indian Non-Provisional Patent Application No. 201621019470, filed on June 07, 2016, and titled, "AUTOMATIC REAL-TIME LOAD SIDE VOLTAGE OPTIMIZATION", whose contents are incorporated herein by the way of reference.

DEFINITION OF TERMS USED IN THIS SPECIFICATION

[0002] The term 'Supply end' refers to a point in an electrical circuit that provides electrical power for consumption.

[0003] The term 'Electrical load' or 'load side' is a point on the electrical circuit that consumes the electrical power supplied by the supply end.

BACKGROUND

Technical field

[0004] The present disclosure is related to systems and methods for measuring electrical power. Particularly, the present disclosure is related to a system that controls and optimizes voltage.

Description of the related art

[0005] Typically, technique of voltage optimization is used at a load side to set a target voltage supplied to an electrical equipment at 220V instead of 230V/240V supplied by a grid. Lowering the value of the target voltage helps reduce energy consumption and also improves operational life of electrical equipments connected in residential, commercial and industrial applications. The aforementioned technique of setting the target voltage at a level lower than the voltage supplied by the grid, suffers from the limitation that a single value of target voltage does not provide efficient performance for a combination of loads applied upon the electrical equipments.

[0006] Typically, optimal voltage is defined as the voltage at which an electrical equipment operates at its highest efficacy and consumes the least amount of electrical energy. The electrical equipment dissipates least amount of heat while operating at an optimal voltage. However, the value of optimal voltage varies based on the type of the electrical equipment, make and manufacturers of the electrical equipment. Further, the optimal voltage varies in accordance with loading patterns of the electrical equipment and also based on equipment degradation. In order to achieve the optimal voltage, it is necessary that an voltage optimizing system is operated at a location closer to the load so that optimal voltage values could be estimated on a continuous basis for varying loads.

[0007] Prior art in this field include a method for performing voltage adjustments at the grid level to improve grid stability and energy efficiency of client loads. Such voltage adjustments at the grid level allow for a maximum of five percent of the electrical energy to be saved. Moreover, grid-side voltage optimization and Conservation Voltage Reduction (CVR) is slow in response as compared to load side real-time voltage optimization.

[0008] Existing prior arts disclose a system for voltage regulation/stabilization. The system accepts an incoming voltage with high variation (for example 230V +/- 15%) and converts it to an output voltage with low variation (for example 230V +/-1%). However, in the aforementioned system, the output voltage is not a function of load behavior. Typically, in such systems voltage is set to a fixed value irrespective of the loading conditions.

[0009] Existing prior arts disclose a system for determining energy usage, and forecasting individualized energy demand. The system optimizes energy usage and cost of service using the predicted individualized energy demand However, existing prior art does not disclose a system for forecasting energy saving in conjunction with voltage optimization. However, it is estimated that load side voltage optimization provides for an increase of up to twenty five percent in energy savings. There does not exist a system that performs real-time voltage optimization at load side for a combination of loads.

[0010] In view of the drawbacks mentioned hitherto, there exists a need for a system that performs real-time voltage optimization at load side for a combination of loads. Further, there exists a need for a system that forecasts energy savings based on optimized voltage.

[001 1] The above mentioned shortcomings, disadvantages and problems are addressed herein, which will be understood by reading and studying the following specification.

OBJECTS

[0012] The primary object of the present disclosure is to provide a system for automatically determining optimal voltages suited for varying loads. [0013] Another object of the present disclosure is to provide a system that integrates a plurality of sensors, microcontroller and voltage regulator into a single housing.

[0014] Another object of the present disclosure is to provide a system that senses at least one component of electrical power delivered to an electrical load, and measures loading patterns corresponding to the sensed component of electrical power.

[0015] Another object of the present disclosure is to provide a system that automatically regulates output voltage based on optimal voltages.

[0001] Yet another object of the present disclosure is to provide a system that stores historical optimal voltage values corresponding to a plurality of loading patterns.

[0016] Yet another object of the present disclosure is to provide a system that independently predicts energy savings based on the loading pattern, sensed component of electrical power and determined optimal voltage values.

[0017] Yet another object of the present disclosure is to provide a system that ensures longer life span of electrical equipment's connected thereto.

[0018] These and other objects and advantages of the present disclosure will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings.

SUMMARY

[0019] The shortcomings discussed in the prior art are addressed by a system for real-time voltage optimization on load side. The various embodiments of the present disclosure disclose a system for determining optimal voltages suited for a combination of loads. The system envisaged by the present disclosure system integrates a plurality of sensors, microcontroller and voltage regulator into a single housing. The system senses at least one component of electrical power delivered to an electrical load, and measures loading patterns corresponding to the sensed component of electrical power. Further, the system automatically sets or regulates output voltage based on determined optimal voltages. The system stores historical optimal voltages determined corresponding to each loading pattern. Further, the system predicts energy savings based on the loading pattern, sensed component of electrical power and determined optimal voltages. Thus, the system ensures longer life span of electrical equipments connected thereto.

[0020] The system envisaged by the present disclosure includes a plurality of sensors, wherein at least some of the sensors are configured to sense a component of electrical power delivered to the electrical load, and remainder of the plurality of sensors are configured to sense a component of electrical power generated at an electrical supply-end. The plurality of sensors are further configured to generate measurement data corresponding to sensed component of electrical power delivered to the electrical load and the electrical supply-end. The system includes a microcontroller configured to analyze the measurement data and generate at least one power loading pattern characterized by a plurality of predetermined electrical parameters. The microcontroller determines an optimal reference value corresponding to the component of electrical power delivered to an electrical load based on the power loading pattern. The microcontroller triggers a voltage regulator to regulate the component of electrical power to the optimal reference value by iteratively adjusting the predetermined electrical parameters. Further, the microcontroller estimates cumulative energy savings achieved at the electrical load based on a comparative analysis of the sensed component of electrical power and regulated component of electrical power.

[0021] In accordance with the present disclosure, the component of electrical power is at least one of an input voltage, output voltage, and output current. The predetermined electrical parameters characterizing the power loading pattern are selected from the group consisting of active power, reactive power, apparent power, Total Harmonic Distortion (THD) and Power Factor (PF). The optimal reference value is a value corresponding to optimal voltage.

[0022] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating the preferred embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The other objects, features and advantages will occur to those skilled in the art from the following description of the preferred embodiment and the accompanying drawings in which: [0024] FIG. 1 is a block diagram of a system for real-time load side voltage optimization, in accordance with an embodiment of the present disclosure.

[0025] FIG. 2 is a flowchart illustrating a method for optimizing load voltage performed by the system, according to an embodiment of the present disclosure.

[0026] FIG. 3 is a flowchart illustrating the predetermined (mathematical) function executed by the microcontroller for determining optimal voltage, in accordance with an embodiment of the present disclosure.

[0027] FIG. 4 is a flowchart illustrating a method for determining fitting parameter, in accordance with an embodiment of the present disclosure.

[0028] FIG. 5 is a flowchart illustrating a method for calculating energy savings, in accordance with an embodiment of the present disclosure.

[0029] Although the specific features of the present disclosure are shown in some drawings and not in others, this is done for convenience only as each feature may be combined with any or all of the other features in accordance with the present disclosure.

DETAILED DESCRIPTION

[0030] In the following detailed description, a reference is made to the accompanying drawings that form a part hereof, and in which the specific embodiments that may be practiced is shown by way of illustration. These embodiments are described in sufficient detail to enable those skilled in the art to practice the embodiments and it is to be understood that other changes may be made without departing from the scope of the embodiments. The following detailed description is therefore not to be taken in a limiting sense.

[0031] The various embodiments of the present disclosure disclose a system that determines voltage operation points that will be most energy efficient within an operating range of an electrical equipment. The system integrates a plurality of sensors, microcontroller and voltage regulator into a single housing. The system measures the component of electrical power generated at the supply- end as well as delivered to an electrical load. The electrical component is selected from the group consisting of input voltage, output voltage and output current. The system generates a loading pattern corresponding to the measured component of electrical power, and subsequently analyses the loading pattern to determine the corresponding optimal voltage. Further, the system envisaged by the present disclosure predicts energy savings based on the loading pattern, measured component of electrical power and the determined optimal voltage.

[0032] FIG. 1 is a block diagram of a system 100 for real-time load side voltage optimization, in accordance with one embodiment of the present disclosure. The system 100 determines optimal voltages for operating an electrical equipment on a combination of loads. The system 100 includes a first set of sensors collectively represented by 102, a second set of sensors collectively represented by 104, a voltage regulator 106, a microcontroller 108, a memory module 110, and a cloud based network 1 12. The first set of sensors 102 are configured to sense a component of electrical power generated at a supply- end. The second set of sensors 104 are configured to sense a component of electrical power delivered to an electrical load from the supply-end. The first set of sensors 102 and the second set of sensors 104 generate measurement data corresponding to sensed component of electrical power generated at the supply- end and the electrical load respectively.

[0033] The measurement data includes input voltage Vj, output voltage V ₀ , and output current I ₀ measured at the supply end and the electrical load respectively. The first set of sensors 102 and the second set of sensors 104 include at least one of a voltage sensor, and a current sensor. At a given instance of time 'k', the values Vj(k), V ₀ (k) and I ₀ (k) are transmitted to the microcontroller 108 via an analog to digital converter (ADC).

[0034] In an exemplary scenario, values of voltage and current are measured for an instance 'k'. In another exemplary scenario, the values of voltage and the current are measured from the data collected by sampling the output voltage and output current multiple times during a particular power cycle. The measured data is analyzed by the microcontroller 108 to determine power loading patterns.

[0035] The power loading pattern is characterized by a plurality of electrical parameters. The electrical parameters characterizing the power loading pattern are selected from a group consisting of active power, reactive power, apparent power, Total Harmonic Distortion (THD) and Power Factor (PF). The microcontroller 108 is further configured to determine an optimal reference value corresponding to the component of electrical power delivered to an electrical load based on specific power loading pattern. In accordance with the present disclosure, the component of electrical power sensed by the first set of sensors 102 and the second set of sensors 104 is voltage, and the optimal reference value is a value corresponding to optimal voltage.

[0036] In accordance with the present disclosure, the microcontroller 108 is further configured to trigger the voltage regulator 106 to regulate the component of electrical power (preferably, voltage) delivered to the electrical load to the optimal reference value by iteratively adjusting predetermined electrical parameters (charactering the power loading pattern indicative of the voltage delivered to the electrical load) which include at least active power, reactive power, apparent power, Total Harmonic Distortion (THD) and Power Factor (PF). The optimal voltage varies with power loading patterns of the electrical equipment as well as based on the electronic equipment degradation. Further, the microcontroller 108 estimates cumulative energy savings achieved at the electrical load by a comparative analysis of the voltage delivered to the electrical load and the optimal voltage.

[0037] In accordance with the present disclosure, the system 100 continuously monitors the electrical parameters at the electrical load for varying loading conditions. For each power loading pattern, corresponding electrical parameters are stored in the memory module 110. Further, the memory module 1 10 stores a plurality of historical power loading patterns and corresponding historical optimal voltage values. The memory module 1 10 also stores historical data related to energy usage and the said historical data is made available to the microcontroller 108 for calculating energy costs and for forecasting energy savings. [0038] In accordance with the present disclosure, the microcontroller 108 accesses the memory module 110 and compares a first power loading pattern corresponding to a first measurement data with the historical power loading patterns stored therein. Further, the microcontroller 108 identifies at least one historical power loading pattern matching the first power loading pattern. If a match is found, the microcontroller 108 extracts a historical optimal voltage value corresponding to the matched power loading pattern. The microcontroller 108 triggers the voltage regulator 106 to regulate the output voltage delivered to the electrical load to the extracted historic optimal voltage value. If no historical loading patterns are found matching the first power loading pattern, then the optimal voltage is determined by the microcontroller 108 by executing a predetermined mathematical function.

[0039] In accordance with the present disclosure, the microcontroller 108 is further configured to forecast a load-side output power based on the measurement data corresponding to the sensed component of electrical power delivered at the supply-end. The microcontroller 108 calculates a load-side output power based on the optimal voltage value. The microcontroller 108 compares the forecasted load-side output power (corresponding to the measurement data) with the calculated load-side output power corresponding to the optimal voltage value. The microcontroller 108 further forecasts the cumulative energy savings by calculating a difference between the forecasted load-side output power and the calculated load-side output power.

[0040] In accordance with the present disclosure, the system includes a cloud based network 1 12 (preferably, a cloud based storage network) communicably coupled (preferably, in a wireless manner) to the microcontroller 108. The microcontroller 108 transfers at least one of the measurement data, the historical power loading patterns, historical optimal voltage values, and values corresponding to cumulative energy savings, to the cloud based network 1 12.

[0041] In accordance with the present disclosure, the system further incorporates wired or wireless communication devices to enable interaction with the cloud based network 112.

[0042] In accordance with the present disclosure, the cloud based network 1 12 stores data corresponding to relevant additional parameters and further uses the stored data for computation of energy savings. The cloud based network 112 performs analysis for determining optimal voltages based on longer term trends considering additional parameters such as time of day, day of week, and rate of Occupancy (O).

[0043] In accordance with the present disclosure, the first set of sensors 102, the second set of sensors 104, the voltage regulator 106, the microcontroller 108, and the memory module 110 and are incorporated in a single housing.

[0044] FIG. 2 is a flowchart illustrating a method for optimizing load- side voltage. The input voltage V,, output voltage V ₀ , and output current I ₀ is measured by a first set of sensors and a second set of sensors positioned at supply end and load side respectively. At a given instance of time 'k', the parameters Vj(k), V ₀ (k) and I ₀ (k) are sensed by the first set of sensors and the second set of sensors respectively (202). The measurement data (preferably numerical values) corresponding to the sensed parameters is transmitted to a microcontroller via an analog to digital converter (ADC). At any instance 'k', a power loading pattern corresponding to the measured data is generated by the microcontroller (204).

[0045] The power loading pattern, hereafter referred to as loading pattern is characterized by electrical parameters including but not limited to active power (P), Reactive Power (Q), Apparent power (S), Power factor, Total Harmonic Distortion (T). Active power (P) is a product of voltage across the electrical load and current flowing through a DC circuit. Reactive Power (Q) is a power merely absorbed and returned in the electrical load due to its reactive properties. Apparent power (S) is the total power in an electronic circuit, which is dissipated and absorbed by the electronic circuit. Further, the apparent power is a combination of reactive power and true power. The power factor is the ratio of the real power flowing to the load to the apparent power in an electronic circuit.

[0046] Further, the loading pattern generated (determined) by the microcontroller is compared with a plurality of historical loading patterns stored in the memory module (206). Every historical loading pattern stored in a look up table of the memory module is mapped to a corresponding optimal voltage value. If the loading pattern (generated by the microcontroller) is found to match at least one historical power loading pattern stored in the memory module, then a historic optimal voltage value corresponding to the matched power loading pattern is extracted from the memory module (210).

[0047] If the determined loading pattern is not found to match any of the historical power loading patterns, then a predetermined (mathematical) function is executed by the microcontroller to determine a new optimal voltage value (208). Further, a voltage regulator is triggered to regulate the output voltage delivered to the electrical load to either the historical optimal voltage value or the new optimal voltage value (210). The historical optimal voltage value or the new optimal voltage value is set as target voltage V _t for the voltage regulator. Further, energy savings achieved at the electrical load is forecasted based on a comparative analysis of the voltage input to the electrical load and the target voltage (212).

. [0048] In accordance with the present disclosure, the method of forecasting energy savings includes forecasting the load-side output power based on the measurement data Vi sensed at the supply-end. Further, a load-side output power based on the optimal voltage value (determined by the microcontroller) is calculated. The forecasted load-side output power corresponding to the measurement data Vj is compared with the calculated load-side output power corresponding to the optimal voltage value. The resultant energy savings is forecasted by calculating a difference between the forecasted load-side output power and the calculated load-side output power.

[0049] FIG. 3 is a flowchart illustrating the predetermined mathematical function executed by the microcontroller for determining an optimal voltage, in accordance with an embodiment of the present disclosure. The flowchart begins at step 300. The output voltage V ₀ , and output current I ₀ are measured by a second set of sensors positioned at the electrical load. At a given instance of time 'k', parameters such as V ₀ (k) and I ₀ (k) are sensed by the second set of sensors, and subsequently the measurement data corresponding to V ₀ (k) and I ₀ (k) is generated (302). The measurement data is transferred to a microcontroller via an analog to digital converter (ADC). At any instance 'k', power loading pattern corresponding to the measurement data is determined by the microcontroller (304). The power loading pattern is characterized by electrical parameters such as active power (P), Reactive Power (Q), Apparent power (S), Power factor, Total Harmonic Distortion (T).

[0050] In accordance with the present disclosure, P(k) is the active power at the instance 'k'. P(k-l) is the active power at an instance 'k- . The power P(k) and P(k-l) are compared to determine if the difference between them is zero (306). If the difference between P(k) and P(k-l) is zero (implying that Output power' at the instance 'k' is equal to the output power at the instance 'k-1 '), then the power loading pattern corresponding to P(k) is stored in a look up table of a memory module (308) for further reference. Further, fit parameters are calculated by the microcontroller based on the power loading patterns (310). Fit parameters are a set of coefficients used in predicting load side power and energy consumption at any instance 'k'. The process of calculating fit parameters is further elaborated in FIG. 4.

[0051] The power P(k) and P(k-l) are compared to check whether the difference between P(k) and P(k-l) is greater than zero (312). If the difference between active power at two instances, 'k' and 'k-Γ is greater than zero, then power utilized by the electrical load has increased due to an increase in output voltage. Further, voltage values V ₀ (k) and V ₀ (k-1) are compared by the microcontroller to determine whether the difference between V ₀ (k) and V ₀ (k-1) is greater than zero. The target voltage V _t is changed based on the variations in V ₀ (k) and V ₀ (k-1) at step 314, and 316. The target voltage V _t is changed to observe the change in output power. Depending on the corresponding change in active power P(k), the target voltage V _t is either increased or decreased. Thus, by comparing the changes in power consumption, decisions are made if the change in target voltage is close to the optimal voltage. The process of increase or decrease in target voltage V _t is repeated until a change in target voltage V _t doesn't cause a significant change in the output power. At a point where there is no variation in the output power, the corresponding target voltage value V _t is determined as the optimal voltage. Once the optimal voltage is determined, it is stored in the look up table along with the corresponding loading pattern.

[0052] FIG. 4 is a flowchart illustrating a method for determining fitting parameters, in accordance with an embodiment of the present disclosure. Fitting parameters are used in calculating energy savings. Fitting parameters are determined by fitting a model (a set of instructions executed by a microcontroller used to calculate energy savings) to a mean and standard deviation of input voltage. The coefficients of fitting parameters are used to estimate the active power.

[0053] The flowchart begins at step 400. A step size is calculated for a period of time based on determined historical optimal voltage values (402). Step size is calculated by the equation: (V _tmax -V _tm jn) /n, wherein V _tma x is a maximum target voltage selected from the historical optimal voltage values, V _tma xis a minimum target voltage selected from the historical optimal voltage values, and 'n' is a total time duration for which fit parameters are calculated. The target voltage V _t is set as V _tm i _n when the value of 'i' is zero, where 'i' is any integer varying from zero to 'n' (404). The value of 'i' is compared with 'n' to determine if value of 'i' is less than 'n' (406). [0054] The steps 412 to 416 are iteratively executed as long as the value of 'i' is less than 'η' (406). The load side output power is calculated based on the measurement data provided by the (412). The load side output power is calculated using the equation:

where V ₀ (k) is an output voltage V ₀ at an instance k, and I ₀ (k) is an output current I ₀ at an instance 'k'.

[0002] Further, a new value of V _t is calculated by adding the (value of) step size to current value of V _t (414). The new value of V _t is stored as optimal voltage (corresponding to the measurement data) in a memory module. Further, the calculated value of Power P is also stored in the memory module (416).

[0055] If the value of 'i' is equal to or greater than 'η', then a predetermined process is executed to determine the fitting parameters (408). In order to calculate the fitting parameters, a minimum of 'η-Γ data points are analyzed from the measurement data. Calculating the fitting parameters involves plotting the 'η- measurements of output Power for a plurality of corresponding output voltages. Further, a mean and standard deviation corresponding to the plot of output power against the output voltage are determined by implementing a predetermined fitting function. Further, the fitting parameters are derived based on the mean and the standard deviation. The fit parameters are stored in the look up table along with the optimal voltages for each of the load conditions.

[0003] The fitting parameters are used in the following equation to compute the load side output power: [0056] where P _k is a forecasted load side output Power at an instance 'k', V'(k) is an input voltage at an instance 'k', 'a' is a coefficient of fitting parameter estimated over a period of time 'n'. For every combination of loading conditions, the coefficient parameters ao, aj, a _n are determined.

[0057] The forecasted load side output Power P _k and the calculated value of load side output Power P is further utilized in estimating energy consumption and energy savings at the electrical load.

[0058] FIG. 5 is a flowchart illustrating a method for calculating energy savings, in accordance with an embodiment of the present disclosure. The energy savings are predicted in real-time based on determined optimal voltage values. The flowchart begins at step 500. A load side output Power P and energy consumption is calculated for the determined optimal voltage value (502). Further, a load side power P _k is estimated considering the voltage generated at a supply end without voltage optimization (504). Subsequently, energy consumption without voltage optimization is determined.

[0059] The load side output power is calculated using the equation:

P = V _o (k) I ₀ (k),

Where V ₀ (k) is an output voltage V ₀ at an instance 'k', and I ₀ (k) is an output current I ₀ at an instance 'k'.

[0060] The input voltage and fitting parameters are utilized to predict the load side output power for measured input voltage. The forecasted load side output Power is calculated using the equation: where P _k is a forecasted load side output Power at an instance 'k', V'(k) is an input voltage at an instance 'k', 'a' is a coefficient of fitting parameter estimated over a period of time 'n'.

[0061] The forecasted load-side output power corresponding to the measurement data is compared with calculated load-side output power corresponding to the optimal voltage value. Further, the resultant energy savings is forecasted by calculating a difference between the forecasted load-side output power corresponding to the measurement data and the calculated load-side output power (508). The flowchart ends at step 510.

[0062] In accordance with an embodiment of the present disclosure, the system 100 stores measurement data (provided by the first set of sensors and second set of sensors) on the cloud based network. Further, a cloud server is triggered to determine the corresponding optimal voltage using certain additional parameters. Examples of additional parameters used in determining the optimal voltage include but are not limited to time of day, day of week, rate of occupancy (O). The additional parameters are preferably used in estimating the fitting parameters.

[0063] In accordance with another embodiment of the present disclosure, the system 100 employs cloud computing to determine minor variations in optimal voltages or energy savings predictions based on data analyzed over longer duration trends and environmental conditions. Examples of techniques used in the cloud based network to forecast energy savings include neural networks, SVD (singular value decomposition), Support Vector Machines (SVM), k-value, Principal Value decomposition (PCA). The cloud based system enables reporting of electrical parameters and energy savings to at least one internet connected device.

[0064] The present disclosure provides a system for real-time voltage optimization on load side. The system ensures energy savings for facility using the system. The system ensures longer life span of electrical equipments connected to the system. The system provides improved productivity using the electrical equipments connected to the system. The system reduces process/production downtime for facility using the voltage optimization system. The system automatically determines optimal voltages, regulate optimal voltages and predict energy savings by executing predetermined functions in a microcontroller. Thus, facility managers need not study or evaluate optimal voltages and adjust them manually. The system reports energy savings in an easily comprehendible format (for example, terms of units saved or percentage savings).

[0065] The foregoing description of the specific embodiments will so -fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such as specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments.

[0066] It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modifications. However, all such modifications are deemed to be within the scope of the claims.