Modern industries, transportation means, and nearly all mankind’s requirements mainly depend on electrical power. Traditionally, electrical power generation is essentially based on fossil fuel resources. Nevertheless, fossil fuels suffer from several drawbacks, such as depletion by 2050. However, the rapid growth of the world’s population increases the world electrical power demand. The global energy demand estimated 2.1% in 2017 (more than twice the average increase over the previous five years) [1
]. Also, it generates harmful emissions that form the essential cause of the phenomena of global warming and many environmental problems. Energy-related carbon dioxide (CO2
) emissions rose—by an estimated 1.4% in 2017—for the first time in four years, at a time when climate scientists said that emissions needed to be in steep decline [1
]. Several decades ago, renewable energy resources have gained more attention as a sustainable replacement for fossil fuels. Renewable energy resources have great advantages as they are clean, do not deplete, and are available everywhere. Many renewable energy resources [2
] have been introduced recently, such as photovoltaic (PV), wind, ocean wave, ocean tides, and micro hydro. Thanks to technology advances and rapid growth, dramatic reductions in the costs of solar PV and wind energy systems have occurred [6
]. In the same context, new energy alternative technologies like biomass, geothermal, microturbines, and fuel cells (FCs) have been investigated [7
]. Now, electricity generation by renewable systems is less expensive than the newly installed fossil and nuclear power plants in many parts of the world. An assessment of different renewable energy resources for electrical power production showed that wind energy is the first choice [8
Renewable energy systems may be classified into grid-connected systems and standalone systems. The present capacities of the grid-connected renewable energy systems vary from several kilowatts of residential PV systems to large-scale wind farms. The grid-connected systems do not need any storage as the generated energy is injected directly to the grid. These systems are suitable for urban regions where the grid is available. However, standalone systems are suitable for rural areas, where grid extension is not feasible. In standalone renewable energy systems, the load is an individual house and not connected to a grid. The capacities of these systems are usually small. In some applications, several houses are connected to form a small power grid called microgrids (MGs) [9
]. Microgrid technology has become popular in islands as it provides a cost-effective alternative where power grid extension is expensive and fuel transportation is difficult and costly [11
The major obstacle for utilizing one technology of renewable energy sources is the intermittent nature of that source. That intermittent behavior of the renewable energy sources comes from the strong dependency on the environmental conditions, which are changing continuously. A suggestion to solve the intermittency problem of the renewable energy systems is the use of energy storage element. Energy storage units are classified as capacity-oriented storage systems and access-oriented storage systems. The capacity-oriented storage systems include pumped hydroelectric storage, compressed air energy storage, and hydrogen storage systems. It has a slow response and is considered long-term energy storage. Batteries, superconducting magnetic energy storage, supercapacitors, and flywheels are considered access-oriented storage systems. It has a fast time response that is useful for short duration disturbance applications [13
]. In fact, the integration of energy storage systems with one technology of renewable energy sources has many disadvantages. One of them is the load power variations, which may harm the storage system and degrade its lifetime. On the other hand, the size and cost of the system increase [17
]. Hybrid power generation systems are introduced essentially to alleviate these disadvantages. These systems contain two or more energy sources with a storage system. Hybrid renewable energy systems have benefits of high reliability, high efficiency, better power quality, and low energy storage requirements [18
Usually, microgrids can operate in two modes: grid-connected mode and autonomous mode. So, the main benefit of a microgrid is that it is able to operate in both the above two modes [20
]. The microgrid can then function autonomously. Both loads and generation in microgrids are usually interconnected at low levels of voltages. However, one issue regarding the microgrid is that the operator needs to be very vigilant because numbers of power system areas are connected to microgrid. Also, in microgrid generation resources can include wind, photovoltaic, fuel cells, energy storage, or other power generation sources [21
In the literature, there are different types of standalone hybrid power sources have been reported [22
]. They usually combine solar energy and/or wind energy with another green power source such as FC, biomass, etc. As the work in this paper is directed to hybrid wind/FC generation systems, we focus on the literature review of that subject. Khan et al. [28
] investigates a hybrid wind/FC generation system and presented a detailed life cycle analysis of the system for application in Newfoundland and Labrador. It concludes that the system is highly nonlinear and difficult to model. Battista et al. [29
] presents a wind/hydrogen power system with a novel power conditioning algorithm. It introduces a Maximum Power Point Tracking (MPPT) control strategy that was developed using concepts of the reference conditioning technique and of the sliding mode control theory. Gorgun et al. [30
] presents a wind/hydrogen power system and developed the electrolyzer and hydrogen storage dynamic model. Bizon et al. [31
] introduces a hybrid wind/FC generation system with a global extremum seeking a control algorithm for optimal operation of the wind turbine under the turbulent wind.
This paper presents a novel hybrid wind/FC energy system. In addition, it presents the system detailed dynamic model, the application of mine blast optimization, the controller design, the performance analyses, and the simulations of the developed system under the turbulent wind speed.
In this study, the microelectrical power grid is managed and controlled based on an optimal controller using mine blast algorithm. The proposed microgrid system mainly consists of R-L static load, IM as a dynamic load, a wind generation system, FC generation system, water electrolyzer, uncontrolled rectifier, and controlled DC/AC converter.
The power system management is adapted to make the wind power generation is the master source for the loads. Also, hydrogen gas is produced using a water electrolyzer during wind power generation peaks. Hydrogen is fed back to the FC system adding to its energy storage.
The main contribution of this study can be seen from the obtained results that the proposed renewable generation system can supply the system loads perfectly in addition to a better prediction of the electrical parameter waveforms. Also, the controller response follows up the desired load demand with a small maximum overshoot and little settling time. In addition to, the generated power is managed such that the load required power is supplied by the wind power and the more needed power is covered by the fuel cell generation unit.
This paper is arranged as follows. Section 2
includes the discussion of the system description. Section 3
presents the proposed system dynamic model. Details of the system controllers are found in Section 4
. The simulation results and their discussion are presented in Section 5
. Finally, Section 6
shows the conclusions.
2. System Description
The proposed system is a hybrid wind/FC microgrid supplies two loads, as shown in Figure 1
. The wind turbine drives a 3-φ Induction Generator (IG) The output voltage of the IG is rectified via a diode rectifier producing the Direct Current (DC) bus voltage. That bus supplies a water electrolyzer that produces hydrogen gas to be saved in the FC generator. Then, the output voltage of the FC is connected to the system DC bus. In addition, the DC bus supplies the 3-φ inverter that converts DC power into Alternating Current (AC) power to feed the system loads. General R-L impedance represents the static load. In addition, the dynamic load is a speed controlled induction motor. That inverter is controlled in such a way to supply loads with a regulated AC voltage and frequency.
Usually, wind speed variations cause the IG output power to vary as well. Therefore, an FC unit supplies power to loads when the power of the wind generation unit drops. Hence, it acts as a slave to compensate for any decrease in the generated wind energy. In addition, it can supply additional power demanded by the loads.
Frequently, the load voltage of the system is not regulated due to the speed variations of the wind and load changes. Therefore, the voltage controller is used for the main inverter to regulate the load voltage and frequency. Also, the optimization algorithm is applied to control the speed of a vector controlled induction motor.
5. Simulation Results
Computer simulations have been carried out to prove the performance of the proposed system under loads and wind speed changes. The proposed system shown in Figure 2
is simulated using MATLAB software package (MATLAB 16, Math Works, Torrance, CA, USA) and tested under various values of wind velocity, IM speed changes, and static load changes. The management of the energy exchange algorithm of the proposed island microgrid is shown by the flowchart of Figure 9
shows the obtained results for various system parameters like wind speed, FC power, IG (torque-stator-current-speed), the FC pressure of hydrogen and oxygen, the power required by the load, Dc bus voltage, static load (current–voltage), and IM (speed-torque-stator current). The system response is tested at step changes in wind velocity, load impedance, IM speed, and IM load torque. This figure shows that the wind speed varies between 11 and 14 m/s, as shown in Figure 10
a. This figure shows also that as the wind speed increases the IG (speed-torque-stator current) increases as well, as indicated in Figure 10
b–d, respectively. Enlarging of Figure 10
d is shown in Figure 10
e. The FC pressure of H2
are present in Figure 10
f. Also, the wind power increases with the wind speed increase as shown in Figure 10
g. On the other hand, Figure 10
g shows that the fuel cell compensates any reduction in wind power and the load power is the sum of the wind power plus FC power.
Per unit DC-link actual and desired load voltage and its enlarging are shown in Figure 10
h,i, respectively. These figures show that the applied controller tracks well the desired load voltage. It is clear that the response has little overshoot and settling time against all disturbances. This leads also to constant AC output voltage of the inverter as shown in Figure 10
The FC power increased at a time of 2 s, where the static load current is increased as shown in Figure 10
g,l. Also, Figure 10
g shows that the fuel cell generated power is more increased in time 2.25 s, where the wind power is decreased. However, the FC power is increased to recover the load power increase. Figure 10
g shows also that the FC power decreased when the static load current decreased at time 4.5 s as shown in Figure 10
n,o show the speed response of the induction motor and its enlarging respectively. From these figures it is seen that the vector controller tracks very well the reference speed of the induction motor. As indicated there is no overshoot and without settling time. Figure 10
q shows the stator current of the IM at different speeds and torques. However, the IM load torque changes between 7 and 10 Nm and the IM speed varies between 120 and 200 rad/s, as shown in Figure 10
The obtained results are compared with the results obtained in [37
], where sliding mode control (SMC) and NARMA-control are applied. The results show that both the proposed optimal control and the robust SMC are able to achieve good voltage and current waveforms parameters and to track the reference DC-link voltage and motor speed with very small overshoot and zero steady state error.
This article proposed a microelectrical power grid system composed of an optimal controller design using an MBA algorithm. This studied controlled power system mainly includes hybrid wind/fuel cell generation unit which feeding both dynamic and static loads. These loads are fed by the fuel cell and the wind power generation system. At high values of wind speed wind power acts as the master source that supplies the loads and store hydrogen in the FC via the electrolyzer. Consequently, at low values of the wind speed, the FC acts as a slave that supplies the loads.
IM as a dynamic load, a series R-L load, and as a static load are considered in this paper. The main inverter controller has two nested control loops. The outer loop (voltage loop) uses an optimal PI controller, while the inner loop (current loop) uses hysteresis controller current. On the other hand, the rotor speed of the IM is controlled using optimal vector control.
The proposed microgrid system is simulated using Simulink/MATLAB software and is tested in step variations of wind speed, IM rotor speed, IM torque, and static load current. The results of the simulation show that the proposed generation system success to supply the loads perfectly under all disturbances. It is indicated that the performance of the main inverter controller is excellent, as the load power responses have low overshoot accompanied by small settling time. Also, the proposed optimal controller is able to maintain the DC-link voltage and hence the AC load voltage at its reference value for any variations in wind velocity and the current of the static load and/or dynamic load parameters variations. We also found that the speed of the IM follows its desired value without any settling time or any overshoot. The obtained results show that both the generated wind and fuel cell powers are generated so that the wind power feeds the load power demand, while the fuel cell power compensates for any extra needed power.