Hybrid power generation systems Essay

nonconventional contributions come from solar and wind, known to have uncertain availability. Recent hybrid power generation systems are equipped with energy storage and/or release system (such as fuel cell, aqua electrolyzer, battery energy system and ultra capacitor etc.) at adequate time to meet the challenges posed by uncertain power generation of wind and solar on voltage and frequency control [82].
One of the major problems in hybrid system is to control the frequency with excitation voltage at a specified level due to occurrence of random wind power generation and random solar photovoltaic (PV) system [7]. To obtain desired frequency response tuning of controllers is very important. Various methods like conventional tuning by Zeigler-Nicolous etc can be used for tuning of controllers but such methods are not suitable for non-linear system. The main problem with wind-solar system is time-varying nature under operating condition and therefore tuning of controller for energy storage devices can be carried out by soft computing techniques.
A hybrid system shown in Fig.-4.4 is analyzed effectiveness of hybrid statistically tracked PSO. The system consists of wind turbine generator, solar PV system as an energy source, diesel generator for backup, aqua electrolyzer, battery and ultra capacitor as an energy storage system. The value of gains and time constants of all components is given in Table-4.1.
The mathematical model of test system for wind-solar and various energy storage systems are given by first order transfer function as [104]
Wind system Using eqn-4.5 the power generated by a wind turbine is
(4.14)
Where, Gwtg is a first order transfer function of wind model.
(4.15)
Solar system For low frequency analysis, it is also represented by the first order transfer function as
(4.16)
Diesel Generator The transfer function of diesel generator for is given by
G_diesel=K_diesel/(T_deisel s+1) (4.17)
Aqua electrolyzer is also expressed by the first order transfer function as
G_AE=K_AE/(T_AE s+1) (4.18)
Ultra capacitor can also be modeled using a first order transfer function as
G_UC=K_UC/(T_UC s+1) (4.19)
The energy revolution rely on increasing amount of renewable energy and therefore requires bigger storage system (such as fuel cell, AE, battery energy system and UC etc.), capable of meeting the greater demands which will be placed on them. Therefore, the proposed work takes advantages of AE and UC to support power demand matching in maintaining the frequency of the system.
To maintain frequency at nominal value, the total power generation must meet the total power requirement of the load. The difference between them is expressed as [82]
Where, Pdemand total load demand
Pout total power generated which is given by following expression [82]
The frequency variation can be expressed by
The value of all the gains, time constants and constants are given in Appendix B.
The hybrid system shown in Fig.-4.4 is represented by following equivalent state space model
In the design of PID controller for hybrid STPSO system following fitness function is selected for minimization.
This objective function utilizes to optimized PID controller gains of energy storage devices using evolutionary algorithms