Agent Based Modeling , Simulation and Forecasting of Household Electricity Demand Profiles
Background
Electricity usage planning is a main concern for electricity stakeholders in a country. To meet the compelling demand for electricity and to deal with different uncertainties involved in this process, development of sustainable policies through proper planning is becoming increasingly challenging.
As per Pakistan National Transmission and Dispatch Company; Pakistan will be able to meet the projected demand of peak hours in 2018. During the last five years, the % mean electricity consumption of different consumer classes is shown in figure below. It is quite evident; the major consumer class is domestic which constitute the 47% of the total electricity consumption.
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Modeling and Simulation of Household energy consumption is necessary for formulation of demand response strategies for domestic consumers, designing of domestic Time Of Use (TOU) tariffs, distribution grid planning, transformer sizing and many other electricity related activities. Therefore, a modular bottom-up approach is required to gain deeper insights and maximum flexibility.
Methodology
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Agent based Modeling & Simulation
Agent based modeling focuses on the individual active components of a system. In agent based simulation, active entities, known as agents, must be identified and their behavior is defined. They may be people, households, vehicles, equipment, products, or companies, whatever is relevant to the system. Connections between them are established, environmental variables set, and simulations run. The global dynamics of the system then emerge from the interactions of the many individual behaviors.
Model Development
Agents : Households , Electricity Appliances (AC, Computer , Fridge , Lights , TV , Oven etc )
Events : Switch_ On (Electricity Appliance) , calculate Energy Consumption
Table Functions: representing 24 hrs usage probability of electricity appliances
Collections: Representing the no. of electricity appliances in evert house
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Proposed Approach and Architecture
We propose the use of the Agent based modeling and simulation approach to simulate the operations and interactions of domestic consumers and electricity appliances at a single household level with a view to assessing their effects on the system as a whole. The key point is that simple household electricity usage rules and patters will generate a complex behavior that cannot be modeled easily by using the other methods.
Equations
Energy_Consumption_Per_Appliance =
∑_(i=1)^(24 hrs)▒〖Energy _ Consumption_Per_Appliance〗+Watts
(if Device On Prob > Random Prob)
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Energy_Consumption_Per_Household =
∑_(i=1)^n▒〖Energy _ Consumption_Per_Appliance〗
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Total_Energy_Consumption =
∑_(i=1)^n▒〖Energy _ Consumption_per_Household〗
Simulation Result
Simulation Result
The proposed framework was simulated for 10 houses which shows the appliance wise electricity consumption trend during 2hrs in a day.
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For validation and verification of the simulated result was compared with one feeder actual electricity consumption data for July, 2016 to June, 2017 that connects only the domestic consumers.
Conclusions and Recommendations
Conclusion
The Agent based simulation will provide as a framework and a tool for conceptual modeling, simulation and visualization of the future demand of domestic electricity consumers. It will further allow the modelers to conceptualize and abstract main entities, influencing factors, key parameters and system variables and the dynamic phenomena that have an impact on the demand in any form and investigate their causes and effects using different initial configurations and experimental settings.
Impact
Our Agent based simulation framework for electricity demand will be useful in forecasting future energy demand and therefore will play a very significant role in electric energy planning. Once the model is configured and calibrated with the national infrastructure, the results generated from the model will be used by analysts to answer different research questions, which further will lead the decision makers to adopt optimal choices for future electricity energy planning in the country.
Project Funding: 3.0 Million PKR Project Duration: June 2016 – December 2017
Related Industry: Power Sector (Tarbela Power Plant, IESCO), Planning Commission