Title :
A stochastic approximation approach to load shedding inpower networks
Author :
Gatsis, Nikolaos ; Marques, Antonio G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Texas at San Antonio, San Antonio, TX, USA
Abstract :
A system comprising a utility company serving a set of electricity end-users is considered. The utility company can purchase energy from the wholesale market. It is also connected to a renewable energy production facility, from which it can harvest energy at no cost, and also to a battery for energy storage. Ahead of a scheduling horizon, the utility purchases energy based on forecasted demand and renewable energy production. During online operation, if the renewable energy is not adequate, real-time decisions with respect to user load shedding, energy procurement, and battery charging or discharging need to be made. The problem is cast in a stochastic approximation framework, and is solved online via a dual stochastic subgradient method with low per-slot complexity.
Keywords :
demand side management; energy harvesting; load shedding; power markets; renewable energy sources; secondary cells; stochastic processes; transmission networks; battery charging; battery discharging; demand forecasting; energy harvesting; energy procurement; energy purchasing; energy storage battery; load shedding; power networks; renewable energy production; stochastic approximation framework; utility company; wholesale market; Approximation methods; Batteries; Procurement; Production; Real-time systems; Renewable energy sources; Stochastic processes; Dual stochastic subgradients; load shedding; smart grid; stochastic approximation;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
DOI :
10.1109/ICASSP.2014.6854849
