Smart Grid Seminar

The contribution of electrical power systems to global climate change has
become one of the more urgent problems facing the world; accordingly, a high
amount of distributed generation capacity, including photovoltaic, wind
power, biomass, and co-generated power, is being planned for installation
into large-scale power network systems in order to reduce greenhouse gas
emissions and fossil fuel reliance. However, it is well understood that many
renewable resources pose risks to power system stability in terms of adverse
effects on frequency and the creation of voltage fluctuations; hence, in
embedding renewables into a grid, it is necessary to create an explicit plan
for plant cooperation and generation optimization in order to ensure safety.
This talk deals with a game theoretic optimal real-time pricing method
based on dual decomposition and its application to load frequency control of
electrical power networks. The goal of this optimal real-time pricing
methodology is to solve the constrained optimization problem consist of each
players' utility and social welfare under selfish players. We can show that
selfish players' decision can be expressed via a kind of a Nash equilibrium
solution considering their own cost functions and it can lead selfish
players' decision to social welfare maximization via real-time pricing
method. Finally the proposed method is applied to a load frequency control
problem of power networks and the effectiveness can be shown via some
numerical simulations.