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A Complex Event Processing Architecture for Energy and Operation Management Jimi Wen July 14 2011 New York 1.

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Presentation on theme: "A Complex Event Processing Architecture for Energy and Operation Management Jimi Wen July 14 2011 New York 1."— Presentation transcript:

1 A Complex Event Processing Architecture for Energy and Operation Management
Jimi Wen July New York 1

2 Outline Introduction Application Objectives Architecture Overview
Energy Management System Maximum Contracted Demand Store Operation Architecture Overview Raw Events Preprocessed Events Rule-based Events Discussions In this report, we share our experience in developing a complex event processing architecture that bridges sensors networks to an energy management system used in the context of chain convenient stores. We analyze event data in real-time to generate immediate and predictive appliance/ operation insights and enable instant response dened by simple business rules. For intuitive rule management, preprocessed events should be used in many cases instead of raw events collected from sensor network. We illustrate practical energy and operation management rules based on preprocessed events such as forecasted and classied events in addition to raw events. 2

3 Application Context Maximum Contracted Demand Contract Store operation
Knowledge of these MCD contracts advantageous to utilities. Better estimate on demand, better planning for generation and transmission infrastructure. Users save on a cheaper plan, if they restrict (Time and Volume) somewhat their consumption. Total cost = Usage*Rate + Max Usage * Penalty + Adjustment Store operation Minimization of electricity => decrease cost However electricity less than 10% of total operation cost, cannot sacrifice operation . But most store main objective is maximize revenue => electricity demand is not really elastic. Constraint Optimization (Rules!!) 3

4 Energy Management System
Data Collection Meters, Sensors, Utilities, Web etc. Reporting and Monitoring Emission auditing, data visualization, detection, analysis etc. Engagement Connect users’ energy consumption, advising, feedback etc. Consumption Interaction Scheduling, Bidding, Trading etc. AlertMe Energy eMeter Control4 SeriousEnergy 4

5 Web-Based EMS Deployment iMeter iGateway Server & Database Interface
6 Stores, 2 Offices, 1 Lab iMeter Data transmitted via ModBus/Zigbee iGateway Convert Protocol Stack Server & Database Intel Xeon 3400 Processor Interface Google Map API Data Visualization 5

6 Architecture Different level languages for different type of users
CEP Engine Rule Engine ECA Rule Meter Data Weather Event Handler EMS System Console Output Logger Data Adaptor Forecasting Classifier Windowing Filter Plug-in 6

7 Raw Events Meter Data Smart Grid Data Environment Sensor Data Web Data
Zigbee communication->gateway->Data server Each Appliance: voltage, current, power factor, real power, apparent power etc. Smart Grid Data Price (For the end-user everything is represent as price?) Environment Sensor Data Measurement of site for possible application development? Web Data Forecast weather for solar power? 7

8 Preprocessed Events-Forecasted
a kind of plugin written in a more suitable language that can natively express such computation Forecasted Events Similar time of day approach 15 minutes model Monte Carlo Method Forecasted probabilities 8

9 Preprocessed Events-Classified
Classified Events Different State of Each Appliance monitored Simple threshold Inference from parametric or stochastic models Non-intrusive Appliance monitoring Preprocessed Events Raw, Forecasted and Classified Events are used to together in the rule manager For energy and/or operation management SOP can be easily implemented by non-developers 9

10 Rule-based Events Raw event only: Preprocessed event-classified only:
if sensor data dropout, message for system maintenance appointment. Preprocessed event-classified only: if billboard is not on anytime from 5pm to 5am, alert store manager to switch the billboard on. Preprocessed event-forecasted only: If overload probability is high, alert store manager 10

11 Rule-based Events Mixture of event types
If overload probability is high and oden3 cooker is on and outdoor temperature is above 30C, then alert to switch o the oden cooker. "Event:OdenOff" (?Ev, ?T) :- Exists ?Ev ?O ( And ( "Event:ReadBuffer"( ?Ev "Event:OverLoad" ) "Electricity:ODenCooker"( ?O ) "Electricity:PowerOn"( ?O, ?OOn ) "Environment:Temperature"( ?TM) "op:greater-than"( ?TM "30" ) "op:text_match"( ?OOn "0n" ) "op:time-now" ( ?T ) ) ) Forall ?Ev ?O ( If And ( "Event:OdenOff"( ?Ev ?T ) "op:time-now" ( ?TN ) "Electricity:PowerOn"( ?O, ?OOn ) "op:time-after" ( ?TN "5m" ?T) Then Do( Action(?O "op:power-off") ) ) 11

12 Discussion CEP that is specific and embedded How to benchmark?
Performance (JSR223+ JSON), not a problem at our scale… Function (JSR Java) Enablingness Creating value added solutions Create good applications with lesser engine first Better interface: Evaluation? Update? Promising results in 6 store locations 12

13 Interface Which one? 13

14 CEP as a platform? Engine- core by big IT provider, IBM, TIBCO etc.
Plugins- from niche specialty solutions, Rules- users for rapid development Operation- operation, monitoring, reporting, feedback etc. 14

15 Thank you for your attention!! Questions?

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