Simulation Modeling, Analysis and Forecasting of Electricity generation and consumption in Pakistan using System Dynamics approach
Objective
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. We propose development of a macro level, multi-scale, multi-resolution, hierarchical simulation model of nationwide energy generation and consumption using System Dynamics approach. The SD based simulation will provide a conceptual modeling framework and a tool for simulation, visualization and analysis of the future demand and supply of electricity energy in Pakistan. Furthermore various influencing factors including prices, tariffs, policies, regulations, available resources and the environment will be coupled with the simulation model to study their sensitivity. Our simulation framework will be used by analysts to answer different energy related research questions, which further will lead the decision makers to adopt optimal choices for future electricity energy planning in the country.
Methodology
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System Dynamics Modeling & Simulation
System Dynamics (SD), is a simulation-based approach to understand the nonlinear behavior of complex systems over time using stocks and flows (Stocks are the accumulations of quantities, influenced by the flows over a period of time and with a specified rate), internal feedback loops and time delays. Because of the complexity of energy systems with a huge number of variables, SD is being considered as an appropriate approach to make a simulation model with the consideration of specific characteristics of Pakistan.
Proposed Approach and Architecture
We propose development of a hierarchical, multi-scale, multi-resolution SD model based on composition of sub-models in a hierarchical order. The proposed SD model will consist of five modules :
The Energy Generation Module is composed of different sub-modules, each
representing different source of electricity. The data collection activity for each
power generation methods was started in July 2016. Energy generation data from
various power plants in Pakistan was collected and used for developing the
simulation models.
Equations for Solar Power Plant
PAC="PSTC× M × D(x) × TD(x) × Pk Hrs "
TD(x)= 1 + Pmax (Tmodule-Tinst)
Tinst="Tamb+(Tcel – Tnorm)" ⁄ ("Normal Operating Solar Irradiance " ×" Solar Radiation" )
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PAC is Estimated daily AC output from a solar source (MWH)
PSTC is Max Power At STC
M is Number Of Modules
D(x) is De-rating-Factor
TD(x) is Temperature De-rating Factor
Pk Hrs is Peak Sun Hours (Day Of Year)
Tmodule is STC Module Temp
Tinst is Instantaneous Operating Cell Temp
Conceptual Model
Simulation Result of Solar Plant
Equations for Wind Power Plant
Power=Cp ρA/2 [Vw]^3
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Cp is an efficiency factor known as the Power Coefficient which depends on the machine design
A is the area of the wind front intercepted by the rotor blades (the swept area)
ρ is the density of the air (averaging 1.225 Kg/m3 at sea level)
v is the wind speed/velocity
Conceptual Model
Simulation Result of Wind Plant
Conclusion
The System Dynamics based simulation will provide as a framework and a tool for conceptual modeling, simulation and visualization of the future demand and supply of electricity energy in Pakistan. Our System Dynamics based simulation framework for electricity demand and supply will be useful in forecasting future energy demand and therefore will play a very significant role in electricity 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