Title :
State forecasting of power systems with intermittent renewable sources using Viterbi Algorithm
Author :
Livani, Hanif ; Jafarzadeh, Saeed ; Evrenosoglu, Cansin Yaman ; Fadali, Sami
Author_Institution :
Electr. & Biomed. Eng. Dept., Univ. of Nevada, Reno, NV, USA
Abstract :
This paper presents a new stochastic method for state forecasting in electrical power systems with high intermittent renewable energy penetration. The method utilizes Markov Models (MM) and the Viterbi Algorithm (VA) with a grid of power system states. Only feasible states of the MM are used to model the transition matrix, which significantly reduces the amount of data needed. We simulated a 4-bus and the IEEE 14-bus system using wind and load data available from the Bonneville Power Administration (BPA). The results show good correlation between the predictions and the actual data.
Keywords :
Markov processes; load forecasting; matrix algebra; power grids; renewable energy sources; stochastic processes; Bonneville power administration; IEEE 14-bus system; IEEE 4-bus system; Markov model; Viterbi algorithm; electrical power system; high intermittent renewable energy source; load data; power system state forecasting; power system state grid; stochastic method; transition matrix; wind data; Data models; Forecasting; Load modeling; Markov processes; Power system dynamics; Wind power generation; Markov model; State forecasting; Viterbi algorithm; Wind power;
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
DOI :
10.1109/PES.2011.6039673
