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Progress Report - A Smart Home Model Using JaCaMo Framework

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Rodrigo Martins

on 18 February 2014

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Transcript of Progress Report - A Smart Home Model Using JaCaMo Framework

Progress Report
A Smart Home Model Using JaCaMo Framework

Motivation
How to improve the efficiency of energy use within a single household and at the same time prepare the household to attend the needs of the Smart Grid?
Electric Power Industry
Smart Grid
Smart Grid focuses on improving efficiency, reliability, economy and sustainability of the production and distribution of electricity
An electrical grid that uses information and communications technology to gather and act on information, such as information about the behaviors of suppliers and consumers.
Green thoughts
The global CO2 emissions are 50% above the 1990 level
(1990 is the base year used in the Kyoto Protocol)*.

Fossil fuels that we are familiar with today is almost entirely eliminated

Electricity demand across the world is predicted to increase by 76% by 2030 (compared to 2007 levels)
Thank you!!!!
* Font: German Renewable Energy Institute - IWR
Green thoughts
The global CO2 emissions are 50% above the 1990 level
(1990 is the base year used in the Kyoto Protocol)*.
* Font: German Renewable Energy Institute - IWR
Smart Grid
Smart Grid focuses on improving efficiency, reliability, economy and sustainability of the production and distribution of electricity
An electrical grid that uses information and communications technology to gather and act on information, such as information about the behaviors of suppliers and consumers.
What is a Smart appliance?
Interconnected
Intelligent
Instrumented
Domestic Appliances
Domestic appliances are characterized under specific categories
Cold
Wet
Temperature
Control
Cooking
Periodic Load
Entertainment
Lighting
What is a Smart appliance?
Interconnected
Intelligent
Instrumented
Domestic Appliances
Domestic appliances are characterized under specific categories
Cold
Wet
Temperature
Control
Cooking
Periodic Load
Entertainment
Lighting
Demand Side Management
Allow the end users to manage their electricity usage

Help the customer to use electricity more efficiently
Smart Home
Rodrigo Castro Martins
rodrigo.castro@ceee.com.br
felipe.meneguzzi@pucrs.br
Felipe Meneguzzi
Energy consumption across the world is predicted to increase by 60% by 2030 (compared to 2010 levels)
Energy Consumption
What did we plan?
How to discover and communicate with the entities on the grid in order to increase control of the power grid, reducing the occurrence of peak demand and assisting users to better manage their households by optimizing energy usage?
Research Question
Hypothesis:
It is possible to strike a balance in optimizing
comfort
, electrical
efficiency
and increasing the
resilience
of a household, by
modeling the appliances and the elements of the grid as a multiagent system
.

In this system, the appliances, the meter and the elements of generation system are modeled as agents within an agent organization that work to improve the collaboration of the household with the grid.
General Objective
Our main objective is to develop a Smart Home model inserting individual agents deployed in each household entities. This model will allow the Smart Home to become more collaborative with the electric grid by balancing demand of energy, increasing the resilience of the household as well as optimizing users well-being.
What did we do so far?
Demand2Consume Allocation Protocol
Experiments, Evaluation and Runs
Next Steps
We are currently refining the household communication protocol introducing an auction approach for energy trading between the smart meter and the appliances;
The User Profile in Brazil
The Smart Home Model
Methodology
In 2012 Brazil had > 60,000,000
They consumed 117,567,173 MWh
An average of 1,933 KWh of consumption
per year, 161KWh per month.
Residential Electricity Consumption from 1995 to 2012
Residential Consuming Units from 2004 to 2012 (x1000)
Projection of the population, 2011-2021
An agent-based smart home model whereby individual autonomous agents are deployed to control each household energy consuming device, as well as an agent coordinating them all through the energy meter.
The model
This model should allow a smart home to become more
collaborative
with the electric grid by balancing energy demand, increasing the
resilience
of the household as well as optimizing user
comfort.
appliance(Pow; Cycles; Categ; Window[Start;End] )
Appliance
washing_machine(600; 4; Wet; Window[14;22])
MAS JaCaMo
Load
Allocation Protocol
The Smart Meter has the responsibility of:

monitoring the set of appliances so they do not operate out of their operating window;

controlling the peak of demand per cycle and control the limit of load per day

releasing load for each appliance;
The appliances have to:

monitor their operating window;

request the necessary load to the Smart Meter;

negotiate with the Smart Meter if can operate or should wait until next cycle;
Runs
We considered three different scenarios
Comfort

Energy Saving

Average consumption
Paper Publication
“A Smart Home model
to Demand Side Management"
Extended Version of our paper was submitted to:
Journal of Advanced Computational Intelligence and Intelligent Informatics
60% of the daily load

3.33% of daily load

10% of the daily load
Scenario
Cycle Limit
In Workshop on Collaborative Online Organizations
(COOS’13) @AAMAS, 2013
Each day is divided in 48 cycles

Household consumption: 186 kWh month (6.2 kwh day)
Appliances used in the simulation
Runs
Activities and Timeline
We developed a MAS to demonstrate the household model. After refining the model we will create a new multi agent system to validate the extended model;
Validate the extended model;
Write the dissertation;
Dissertation defense.
Full transcript