# Load Frequency Control for Multi-Area Power Plants with Integrated Wind Resources
## 1 Introduction  
Recently, more electrical power can be generated from wind turbines due to improvements in technology. Many power companies are investing in wind farms to supply electricity to their endOusers. Moreover, remote geographical locations that are outside of grid services have been fed by wind farms. Efforts are on-going to integrate wind turbines with the existing MAIPS in order to increase grid services. However, wind farms integrated with the existing power network raise some concerns due to frequency deviations. These concerns are intermittent problems associated with the wind energy source, which involve maximum power point tracking, synchronization problems, uncertainty, difficulty in system parameter measurements (since the dynamic behaviors are different from conventional power plants), etc. These are additional to the existing disturbances, such as nonlinearity, random and step-load disturbances, matched and mismatched uncertainty, etc., which are found in conventional MAIPSs. Thus, these factors give rise to large frequency errors and affect the power quality. The load frequency control (LFC) scheme has been utilized to takecare of the frequency deviation and to ensure the quality of the power supply. Moreover, the concerns, characteristics and behaviors of MAIPSs, as mentioned above, are vital issues in LFC design [1]. Classical, intelligent and optimal control techniques have been applied to LFC of MAIPSs in the past and are discussed in [2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17]. A major problem with the interconnection of the power systems is increasingly related to the system and system parameter uncertainties. Therefore, the control approaches outlined in [2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17] exhibit some limitations, as discussed in [18]. Thus, a robust LFC technique for MAIPS was proposed in [18]. The sliding mode control (SMC) scheme is one of the robust control approaches proposed in order to solve the above problem. It was selected because of its robustness against load disturbances and parameter variations. The SMC scheme was designed for the LFC of MAIPSs in various operating conditions, which are presented in [19; 20]. Recently, the adaptive technique combined with sliding mode control has been developed to study the LFC of MAIPSs [21]. Adaptive event-triggered SMC was used to investigate the LFC of an MAIPS under a deregulated environment [22]. More recently, double-integral SMC was applied for the decentralized adaptive LFC of an MAIPS, presented in [23]. However, these above SMC approaches act under the first-order time derivative. In further studies, the first-order SMC may suffer from the chattering phenomenon, which can cause inaccuracies in LFC due to the discontinuous control signal in the SMC controller, which causes harmonics and affects the system performance and the power quality. Therefore, second-order SMC is used to eliminate the above chattering problem. Second-order SMC was applied for the LFC of an MAIPS to solve the chattering problem and discussed in [24]. An adaptive SMC combined with the higher-order SMC for the LFC of an MAIPS was invented to improve the elimination of chattering, as presented in [25; 26; 27]. However, in a real MAIPS, the LFC design is better when load disturbances are not required to be measured. To solve this difficulty, the use of a disturbance observer has been applied for the LFC of MAIPSs [28]. In addition, the disturbance observer combination with SMC for the LFC of MAIPSs was also discussed in [29; 30; 31]. Recently, a state observer was used to estimate the non-measurement system state variables for designing the LFC of MAIPSs [32]. A non-linear SMC based on a generalized observer was developed to regulate frequency in a large power system [33; 34]. However, there are some limitations of the above approaches for the LFC of the MAIPS. First, the system state variables need to be measured for the feedback of the load frequency controller [23; 24; 25; 26; 27; 28; 29; 30; 31].