Abstract:
High penetration of renewable energy sources coupled with
decentralization of transport and heating loads in future power
systems will result even more complex unit commitment problem
solution using energy storage system scheduling for efficient load
leveling. This paper employees an adaptive approach to load leveling
problem using the Volterra integral dynamical models. The problem is
formulated as solution of the Volterra integral equation of the
first kind which is attacked using Taylor-collocation numerical
method which has the second-order accuracy and enjoys
self-regularization properties, which is associated with confidence
levels of system demand. Also the CESTAC method is applied to find
the optimal approximation, optimal error and optimal step of
collocation method. This adaptive approach is suitable for energy
storage optimization in real time. The efficiency of the proposed
methodology is demonstrated on the Single Electricity Market of the
Island of Ireland.