In order to evaluate the integration of the AC/DC system and study the system performance during load variations, an experiment was conducted to show the system
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behavior and AC/DC power sharing control while the load variations take place in active and reactive power. In this experiment, the DC microgrid quantifies its DC power availability during the upcoming interval of time. Hence, it will inject any amount of active/reactive power demanded by the AC side, through the WAMPAC considering all constraints.
The DC system is connected to Bus-0050 through a bi-directional converter as shown in figure 6.7 and injects any specified amount of active and/or reactive power to the AC point of common coupling (PCC). In this experiment the DC microgrid was used to regulate the voltage at the PCC.
Figure 6.10 shows the experimental results which a unity power factor load of 700-W was initially connected to Bus-0050. The DC microgrid was commanded to receive 100 W and zero Vars. Hence, AC grid takes the responsibility of supplying both AC load and DC microgrid demand. The steady state voltage at PCC in this situation was 0.94 p.u. whereas the voltage on the DC bus was 1 p.u. After 20 sec, the DC microgrid was commanded by WAMPAC system to inject the total amount of demanded power on the AC side. Therefore, the voltage amplitude was increased to 1.02 p.u. The controlled rectifier regulating the voltage on the DC bus maintains a voltage of 1 p.u. after a transient period of around 6 sec with an overshoot of 0.02 p.u.
A reactive load of 450 VARs was increased to PCC after 43 sec. Consequently the voltage amplitude drops to around 0.95 p.u. The DC microgrid was then commanded by WAMPAC to inject 300-VARs to the AC grid. Hence, the voltage at the PCC increases to 0.98 p.u. The DC bus voltage is hardly affected by this change in its reactive
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power reference. The frequency variations are also shown in this figure. A maximum of 0.2 Hz deviation from 60 Hz was depicted in the measured frequency.
Figure 6.10: Performance of the integrated hybrid AC/DC microgrid corresponding to step change in the load demand reference. (a) the load, DC and AC active power share, (b) the load, DC and AC reactive power share, (c) the frequency of the AC bus, (d) the voltage of the AC and DC buses.
0 10 20 30 40 50 60 70 80 90 -1000 0 1000 A ctiv e P ow er (W ) 0 10 20 30 40 50 60 70 80 90 -500 0 500 R ea ct iv e P owe r ( V AR s) 0 10 20 30 40 50 60 70 80 90 59 60 61 F re que nc y ( H z) 0 10 20 30 40 50 60 70 80 90 0.9 1 1.1 Time (s) V ol tage (p .u .) Total PCC load AC power share DC power share DC voltage AC voltage AC frequency
Total PCC reactive load AC reactive power share DC reactive power share
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Figure 6.11 shows details about the quality of the active and reactive power transferred between the AC and DC grids after 10 sec. This figure also shows the current and voltage waveforms, as well as the THD at the PCC and the inverter terminals.
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Figure 6.11: Current and voltage waveforms, their THD after 10 s. (a) shows the PCC current and voltage waveforms, (b) the inverter side current and voltage phasors, (c) the current and voltage THD
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Figure 6.12 depicts also same details about the quality of the active and reactive power transferred between the AC and DC grids this time after 70 sec. This figure also presents the current and voltage and THD at the PCC at 70 seconds. Using this integrated controller for hybrid AC/DC microgrids will enhance the performance of the system.
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Figure 6.12: Current and voltage waveforms, their THD after 70 s. (a) shows the PCC current and voltage waveforms, (b) the inverter side current and voltage phasors, (c) the current and voltage THD.
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CHAPTER 7
IMPLEMENTATION OF REAL-TIME POWER SYSTEM SECURITY AND VOLTAGE STABILITY MONITORING SYSTEM
7.1 Introduction
This chapter explores the challenges and opportunities to implement online system analysis capability in order to monitor the system security and stability through the establishment of operational indices. Therefore, the implemented hardware/software setup for monitoring and analyzing system in real-time format was presented by the online results available from real-time software. Online load flow and contingency results aim to help provide proper security monitoring of the power system in wide area which is useful for most applications including system remedial actions.
In real-time operation of power system, the reliability is always referred to as security [156]. Power system security is the ability of the system to withstand contingencies which are subjected to it by wide variety of disturbances. For example, sudden change in load demand, loss of transmission line, system configuration change, equipment outage and generator failures are typical power system circumstances. The smart grid uses modern communication infrastructure at wide area power system to improve grid reliability, reduce the price of electricity, improve operational efficiency, security and safety and promote environmental quality [21], [22].
System state monitoring is technically can be achieved using fast wide area measurements and hence it enhances WAM system in order to demonstrate system current status which is known as normal state, restorative state and emergency state [156]. At normal operation, if one or more operational limit are violated the system state
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changes to emergency and if it leads to load disconnection such as partial or total blackout from which the rest of the system remained in a normal state, the system moves to the restorative state. A normal state is secure if all contingencies result in secure normal operation. Therefore, the secure power system is one that has low probability of blackout or equipment damage. The WAMPAC system is responsible to maintain a secure system state in order to prevent system state transition to emergency state. The wide range of operational control and protection strategies in smart and intelligent form should be implemented in WAMPAC system. Power system dynamics bring the new challenges for online changing at control scenarios. These control actions are deployed to ensure that the supply-demand balance is met reliably and securely [157]-[159].
The objective of this research is to use real-time measurements at smart grid to identify the power system state. Online power system analysis feature are developed to deploy real-time data in order to monitor system state with online load flow and security assessment results. The implemented laboratory setup for a micro smart power grid has been presented previously with the developed software environment to monitor real-time data as a SCADA center. The real-time software has the capability to run analysis software in engine mode and hence the system online analysis can be implemented by real-time data monitoring speed. In this setup, the monitoring system updates the SCADA system approximately every one second and then the analysis software can update the data immediately after and calculates security indices. Consequently, this system can analyze power system less than 3 seconds snapshot and returns the real-time calculation results. Figure 7.1 shows the power system phenomena time frame as well as control
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actions in their time frame. Studies related to the time range of phenomena and control actions has also shown as well as developed security assessment.