Non-Smooth Dynamics in Energy Market Models: A Complex Approximation from System Dynamics and Dynamical Systems Approach

This paper reports a general model that describes the supply and demand of electricity in a national market based on the system dynamics (SD) approach. From the resulting SD model, it derives piecewise smooth (non-smooth) differential equations from the nonlinear functions and feedback cycles of the...

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Autores:
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
eng
OAI Identifier:
oai:repository.udem.edu.co:11407/5985
Acceso en línea:
http://hdl.handle.net/11407/5985
Palabra clave:
Complexity
dynamic systems
energy markets
energy policy
Fillipov systems
modeling
non-smooth dynamic
power markets
simulations
system dynamics
Differential equations
Dynamical systems
Nonlinear equations
Power markets
System theory
Dynamical systems approach
Energy market modeling
Equilibrium point
Investment decisions
Non-smooth dynamics
Non-smooth vector fields
Nonlinear functions
Supply and demand
Investments
Rights
License
http://purl.org/coar/access_right/c_16ec
Description
Summary:This paper reports a general model that describes the supply and demand of electricity in a national market based on the system dynamics (SD) approach. From the resulting SD model, it derives piecewise smooth (non-smooth) differential equations from the nonlinear functions and feedback cycles of the corresponding stock-flow structure. Subsequently, the stability of the equilibrium points and non-smooth dynamics of the SD model are investigated using the dynamical systems theory. Filippov systems are found in the proposed SD model and non-smooth vector fields associated with generators investment decisions are accumulated. Under this combining methodology, the non-smooth dynamics of energy markets that are governed by the supply and demand laws are uncovered mathematically and deeply described. In fact, we extend our investigation results to any energy market model attached to various investment decisions, confirming the generalizability of our research. © 2013 IEEE.