.png){kind=icon}
.png){kind=icon}
Return
Multi objective unit commitment with voltage stability and PV uncertainty
.png){kind=icon}
PRE
AI
DOI：10.1016/j.apenergy.2018.06.074.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper proposes a novel multipurpose operation planning method for minimizing the prediction error of photovoltaic power generator outputs (PV); towards reducing the operating cost and improving voltage stability of power systems. The operation schedule (coordination) of demand response (DR) program and storage system are taken into account as the main parameters for achieving an improved voltage stability and reduction of PV output prediction error. In this approach, the stochastic programming algorithm is introduced for incorporating the uncertainty of PV output and the utility demand response for consumer side management. This is achieved by using the multi-objective genetic algorithm (MOGA) for multipurpose operation plan. The MATLAB optimization toolbox and neural network toolbox were applied in this research study. An IEEE-6 bus system is used to demonstrate the effectiveness of the proposed solution in power systems operation. The approach led to $25003.39(=1$99594.53-$74591.14) reduction in the system operating cost, compared to the conventional approach. The simulation results also show that by using the proposed algorithm, the capacity of installed PV generators was increased and the voltage stability was improved at the same time. This accounted for the reduction in the effective operating cost and the improved operating condition of the power system.
Keywords:
Stochastic unit commitment
Power system security
Power system economics
PAT uncertainty
Renewable energy Technology
Pareto set
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
11
Papers:
2.6W
Citations:
17.8W
