A reliable and accurate short-term load forecasting (STLF) helps utilities energy providers deal with the challenges posed by supply demand balance, higher penetration of renewable energies development electricity markets increasingly complex pricing strategies in future smart grids. Recent advances deep learning have been successively utilized to STLF. However, there is no certain study that e...

The integration of battery energy storage systems (BESS) in the electrical grid is accelerating to mitigate challenges associated with rapid deployment low carbon technologies (LCTs). This work investigates ability BESS provide power networks important ancillary services such as peak shaving and levelling through two case studies conducted collaboration Northern Ireland's distribution network o...

In a truly smart grid, system load would be known in advance with a high degree of confidence. Currently, this goal of “smart forecasting” is far from being realized. In the Pacific Gas and Electric (PG&E) aggregation area managed by the California Independent System Operator (ISO), the root mean squared day-ahead forecast error was about 3.8 percent of mean actual load over the period 1 April ...

We consider an environment where agents' tasks are tightly coupled and require real-time scheduling and execution. In order to complete their tasks, agents need to coordinate their actions both constantly and extensively. We present an approach that consists of a standard operating procedure and a look-ahead coordination. The standard operating procedure regulates task coupling and minimizes co...