New approach using structure-based modeling for the simulation of real power/frequency dynamics in deregulated power systems

Load frequency control (LFC) is one of the significant ancillary services in the electricity markets. The major concerns with LFC models have long been their dynamic response and complexity, as well as market price sensitivity. To cater to the complexity of the dynamic model that is introduced by the LFC and algebraic constraints by the transmission network, the differential-algebraic equation is transformed into a set of ordinary differential equations. This is done by differentiating the network constraints under a certain assumption that can be held throughout the system. To make the model suitable in a market environment, the real power (MW) variable is substituted by the energy (Dolar) variable to emphasize the price signal in the market. The obtained results show that the model is much easier to understand and simpler to implement. The computational complexity of the model is further reduced. Based on the performed simulations, the proposed LFC model functions better in a deregulated environment. A test case comprising 5 buses and 3 machines, with a 2-region system, is used to address the advantages of the proposed LFC model.

New approach using structure-based modeling for the simulation of real power/frequency dynamics in deregulated power systems

Load frequency control (LFC) is one of the significant ancillary services in the electricity markets. The major concerns with LFC models have long been their dynamic response and complexity, as well as market price sensitivity. To cater to the complexity of the dynamic model that is introduced by the LFC and algebraic constraints by the transmission network, the differential-algebraic equation is transformed into a set of ordinary differential equations. This is done by differentiating the network constraints under a certain assumption that can be held throughout the system. To make the model suitable in a market environment, the real power (MW) variable is substituted by the energy (Dolar) variable to emphasize the price signal in the market. The obtained results show that the model is much easier to understand and simpler to implement. The computational complexity of the model is further reduced. Based on the performed simulations, the proposed LFC model functions better in a deregulated environment. A test case comprising 5 buses and 3 machines, with a 2-region system, is used to address the advantages of the proposed LFC model.

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