TY - JOUR
T1 - Coordinated control of distributed energy resources to support load frequency control
AU - Ravikumar Pandi, V.
AU - Al-Hinai, A.
AU - Feliachi, Ali
N1 - Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2015/11/15
Y1 - 2015/11/15
N2 - The control of generating resources to follow the unscheduled load changes is considered to be an essential process in the power system in order to maintain the frequency of power supply. This load frequency control (LFC) problem has been given more importance in the recent smart grid environment because of the impact from high penetration of distributed energy resources (DER) installed at the distribution level. The renewable sources are highly intermittent in nature, so it is required to coordinate and control the DER units to maintain the feeder power flow at substation bus bar which is seen by transmission system operator during the LFC process. This paper aims to identify the impact of distributed generation and its control method to reduce the deviation of feeder power flow from the scheduled value in real time operation. The error in feeder power flow with respect to scheduled value is utilized by the PI controller to estimate the change in power reference of all DER units. The power output of DER units are maintained to reference values by the individual PI controllers. The particle swarm optimization algorithm is employed to minimize the error in feeder power flow by optimally tuning the gain values of all PI controllers. The proposed method is examined on a small transmission system along with the feeder of IEEE 37 bus distribution system with balanced loading condition. The complete system along with DER units is implemented in the MATLAB based stability package named Power Analysis Toolbox (PAT) for performing time domain analysis. The impact on feeder flow and system frequency for the disturbance in load and weather condition without feeder control scheme (NFC) is compared with the feeder control scheme (WFC).
AB - The control of generating resources to follow the unscheduled load changes is considered to be an essential process in the power system in order to maintain the frequency of power supply. This load frequency control (LFC) problem has been given more importance in the recent smart grid environment because of the impact from high penetration of distributed energy resources (DER) installed at the distribution level. The renewable sources are highly intermittent in nature, so it is required to coordinate and control the DER units to maintain the feeder power flow at substation bus bar which is seen by transmission system operator during the LFC process. This paper aims to identify the impact of distributed generation and its control method to reduce the deviation of feeder power flow from the scheduled value in real time operation. The error in feeder power flow with respect to scheduled value is utilized by the PI controller to estimate the change in power reference of all DER units. The power output of DER units are maintained to reference values by the individual PI controllers. The particle swarm optimization algorithm is employed to minimize the error in feeder power flow by optimally tuning the gain values of all PI controllers. The proposed method is examined on a small transmission system along with the feeder of IEEE 37 bus distribution system with balanced loading condition. The complete system along with DER units is implemented in the MATLAB based stability package named Power Analysis Toolbox (PAT) for performing time domain analysis. The impact on feeder flow and system frequency for the disturbance in load and weather condition without feeder control scheme (NFC) is compared with the feeder control scheme (WFC).
KW - Battery storage system
KW - Distributed energy resources
KW - Fuel cell
KW - Load frequency control
KW - Photovoltaic generation
KW - Responsive loads
KW - Wind power generation
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U2 - 10.1016/j.enconman.2015.08.046
DO - 10.1016/j.enconman.2015.08.046
M3 - Article
AN - SCOPUS:84952655782
SN - 0196-8904
VL - 105
SP - 918
EP - 928
JO - Energy Conversion and Management
JF - Energy Conversion and Management
ER -