System Reliability by Prediction of Generator Output and Losses in a Competitive Energy Market
In a competitive energy market, system reliability
should be maintained at all times. Power system operation being of
online in nature, the energy balance requirements must be satisfied to
ensure reliable operation the system. To achieve this, information
regarding the expected status of the system, the scheduled
transactions and the relevant inputs necessary to make either a
transaction contract or a transmission contract operational, have to be
made available in real time. The real time procedure proposed,
facilitates this. This paper proposes a quadratic curve learning
procedure, which enables a generator-s contribution to the retailer
demand, power loss of transaction in a line at the retail end and its
associated losses for an oncoming operating scenario to be predicted.
Matlab program was used to test in on a 24-bus IEE Reliability Test
System, and the results are found to be acceptable.
Deregulation, learning coefficients, reliability,prediction, competitive energy market.