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THE ENERGY ECONOMIZER EE - SCHEME. Robert LeBlanc Electrical and Computer Engineering Supervised by: Professor Dr. Adel M. Sharaf. Introduction. Why EE – Scheme? Save Electrical Energy Lower Power Billing Costs Enhance Power Quality (PQ) Increase Reliability and Security

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the energy economizer ee scheme


Robert LeBlanc

Electrical and Computer Engineering

Supervised by: Professor Dr. Adel M. Sharaf


Why EE – Scheme?

  • Save Electrical Energy
  • Lower Power Billing Costs
  • Enhance Power Quality (PQ)
  • Increase Reliability and Security
  • Demand – Side Management
  • Feeder Capacity Release
major components
Major Components:
  • Predictive Interface Capacitor Compensation Hardware that will:
    • Monitor power (P,Q,S,P.F) usage in 15 minutes intervals.
    • Log current historical data for predictive software
  • Predictive Intelligent Software that will:
    • Learn power consumption and demand patterns
    • Adjust the corrective capacitive compensation hardware for optimal utilization.
  • The Corrective Capacitive Switching will:
    • Adjust power usage for optimal energy utilization, efficiency, power factor enhancement as well as voltage stabilization.
what is electrical power
What is Electrical Power?
  • P = Real Power
    • Real Power may be defined as the conversion of electricity into other useful forms of power (Light, heat, mechanical uses)
  • Q = Reactive Power
    • Power that does no real work but is necessary for magnetization (Used in motors, transformers, high intensity lighting)
  • S = Apparent Power
    • The Vector sum of Real and Reactive Power S2=P2+Q2
benefits of correcting power factor
Benefits of Correcting Power Factor

Capacitive Power (QC)

  • Most electrical loads are Inductive in nature
  • These loads may be corrected by adding a capacitive current that are can reduce reactive load
  • When Inductive and Capacitive loads are equal, they cancel leaving only real power. QL=QC=Unity Power

Real Power (PL)

Inductive Power (QL)

problems with power factor correction
Problems with Power Factor Correction
  • Loads are not constant but dynamic and are continually changing.
  • Existing technology generally uses fixed compensation capacitors or switched type which leads to either:
    • Undercompensation conditions
    • Overcompensation conditions
  • This requires an intelligent novel switching routine that will follow closely the varying load dynamics (Dr. A.M. Sharaf).
digital metering
Digital Metering
  • It is necessary to obtain data for predictive software using digital demand meters
    • Measurements every 15 minutes (PL,QL,SL,P.F.)
    • 96 measurements every 24 hours.
    • 35,040 measurements every year.
  • It is also necessary to additionally collect for power quality issues:
    • Voltage
    • Current
predictive intelligent software
Predictive Intelligent Software
  • Learns the characteristics of any inrush cyclical, converter, nonlinear, or arc type loads and load consumption patterns
  • Using statistical interpolation & extrapolation, these key patterns are then turned into usable control switching signals. (Other techniques developed by Dr. Sharaf use ANN – Neural Network based switching)
  • Control signals turn on or off various levels of capacitive compensation based on dynamic intelligent load varying patterns.
  • Software adapts and learns any new load patterns using additional built-in statistical multiple regression MR-tools.
predictive capacitor compensation hardware
Predictive Capacitor Compensation Hardware
  • Adjusts capacitive compensation level Qc(k) for current conditions at a given time sample(k).
  • ½ of the compensation is selected as a fixed capacitor bank.
  • Remaining capacitor compensation is selected as one or more switched capacitor bank required in four levels.
  • Power Factor can be enhanced to acceptable levels
  • Load utilization and Power Quality are also enhanced.
intelligent switching software implementation rules developed by prof dr adel sharaf
Intelligent Switching Software Implementation Rules(Developed by Prof. Dr. Adel Sharaf)
  • Select fixed and variable capacitor sizes to be of equal size to compensate for approximately 90% of reactive power.
  • The Variable capacitor bank is a time switched bank that switches according to historical Load Patterns.
  • Historical load patterns are based on 15 minute metering intervals (P,Q,S,P.F.)
  • Data pattern equations based on historical data are:
    • P*(k) = α1P(k-1) + α2P(k-2) + α3P(k-3)+…
    • Q*(k) = β1P(k-1) + β2P(k-2) + β3P(k-3)+…
    • S*(k) = sqrt( P*(k) + Q*(k) )
    • PF*(k) = P*(k)/S*(k)
  • The interval (k) prediction magnitude only errors are defined as:
    • eS(k) = [S*(k)- S(k)]
    • ePF(k) = sqrt( eS2(k)+ePF2(k) )
  • The Total error eT(k) in the (eS(k), ePF(k)) phase plane is defined as
    • |eT(k)| = sqrt(eS2(k) + ePF2 (k) )
four zonal switching rules for capacitor bank switching developed by prof dr adel sharaf







Zone(0) is dead zone (no action)

Four Zonal Switching Rules for Capacitor Bank Switching(Developed by Prof. Dr. Adel Sharaf)

αD = ΔT/T0 = Duty Cycle


Phase –Plane Portrait of the Target Practice Zonal Switching Patterns

sample test model
Sample Test Model

In order to verify proposed capacitor switching algorithm, a sample test system was employed using Matlab/Simulink. This system was run for various loads and load excursions in order to verify the suspected results.

variable capacitor compensator
Variable Capacitor Compensator

The capacitor bank αD switching is accomplished in four steps. The capacitors are switched in as required by the predictive corrective software. This scheme will achieve near unity power factor operation resulting in power efficient utilization.

3Φ - 4wire switched Capacitor bank

case 1 zone 4 correction
Case 1 – Zone 4 Correction

100% Load With Full Correction,

Power factor = 0.96 (Minimum)

100% Load With No Correction,

Power factor = 0.84 (Minimum)

case 2 zone 2 correction
Case 2 – Zone 2 Correction

Zone 2 With No Correction,

Power factor = 0.87 (Minimum)

Zone 2 With 40% Correction,

Power factor = 0.955 (Minimum)