12
Frequency Regulation in Isolated Systems with Dispersed Power Sources
Numerous new distributed power generation technologies, such as the photovoltaic (PV) generation, the wind turbine generation, the micro gas turbine generation, and the energy storage devices, are currently available to offer integrated performance and flexibility for the power consumers.1–4 Frequency regulation in interconnected networks is one of the main control challenges posed by emerging new uncertainties and numerous distributed generators, including renewable energy sources in a modern power system.5 Significant interconnection frequency deviations due to distributed power fluctuations can cause under- or overfrequency relaying and disconnect some loads and generations. Under unfavorable conditions, this may result in a cascading failure and system collapse.6
This chapter presents a multiagent-based automatic generation control (AGC) scheme for isolated power systems7–9 with dispersed power sources such as PV units, wind generation units, diesel generation units, and energy capacitor systems (ECS)10–12 for the energy storage. The ECS consists of electrical double-layer capacitors. The power generation from the PV units and also from the wind generation units depends on environmental factors, such as the solar insolation and wind velocity; therefore, complete regulation of the power from these units is quite difficult.
Contribution of ECS units to the frequency regulation in coordination with conventional AGC participant generating units was addressed in Chapter 10, and the application of multiagent systems in AGC synthesis was discussed in Chapters 7 and 8. In this chapter, the ECS is coordinated with the diesel units to propose a new multiagent-based AGC scheme.
As mentioned in Chapter 10, since the ECS units are able to provide a fast charging/discharging operation, the variations of power from the wind turbine units and also from the PV units can be absorbed through the charging or discharging operation of the ECS units. In addition, the variation of power consumption at the variable load can also be absorbed through the charging/discharging operation of the ECS units. A small-sized ECS is considered in this study; therefore, the continuous charging or discharging operation is not available on the ECS because of its restricted capacity. To overcome this situation, the regulation power on the diesel units is inevitable to keep the stored energy of the ECS in a proper range for the continuous AGC operation on the ECS. In the proposed AGC scheme, the ECS provides the main function of AGC, while the diesel units provide a supplementary function of the AGC system. Namely, a coordinated AGC between the ECS and the diesel units has been proposed for balancing the total power generation and the total power demand in the isolated power systems. The proposed multiagent system consists of three types of agents: monitoring agents for the distribution of required information through the computer network, control agents for the charging/discharging operation on the ECS and also for the power regulation on the diesel units, and finally, a supervisor agent for the coordination between the ECS and diesel units. Experimental studies in a power system laboratory have been performed to demonstrate the efficiency of the proposed multiagent-based AGC scheme.
12.1 Configuration of Multiagent-Based AGC System
In the proposed AGC scheme, the system frequency monitored on a diesel unit is regulated to its nominal frequency by balancing the total generation and the total power consumption in the isolated power system. Namely, the AGC function can be achieved through the charging/discharging operation of the ECS in coordination with the produced regulation power from the available diesel units.
Figure 12.1 illustrates the configuration of the proposed multiagent-based AGC system for isolated power systems with dispersed power sources. This configuration, which will be described later, is similar to the agent-based frequency regulation scheme presented in Figure 3.8.
12.1.1 Conventional agC on Diesel Unit
In the conventional scheme, the diesel units are utilized for the AGC system to regulate the power generation following the monitored frequency deviation on itself. Figure 12.2 illustrates the configuration of the AGC system based on the flat frequency control (FFC) with a proportional-integral (PI) control loop. Here, ∆f and ∆PC represent the measured frequency deviation on the diesel unit and the provided signal for the output setting of the diesel unit.
12.1.2 Coordinated agC on the eCS and Diesel Unit
In this study, a new AGC scheme has been proposed considering the coordination between the ECS and the diesel units. The basic configuration of the proposed feedback control system for the ECS on the supervisor agent is shown in Figure 12.3. Here, Tdelay and PSECS represent the communication time delay13 and the control signal for the output setting of the ECS unit. The configuration, except the time delay block, is the same as that in Figure 12.2, where the diesel units are utilized for the AGC. Applying the control signal PSECS from the mentioned loop provides an appropriate charging/discharging operation on the ECS for the frequency regulation purpose.
FIGURE 12.1
Configuration of multiagent-based AGC system.
FIGURE 12.2
Configuration of AGC on diesel unit.
FIGURE 12.3
Feedback control system for ECS on the supervisor agent.
Because of the specific feature of the ECS dynamics, it is possible to achieve the fast charging/discharging operation in an ECS unit. Therefore, the variations of power generation from the wind turbine and PV units, as well as the variation of demand power on the variable loads, can be efficiently absorbed through the charging/discharging operation of the ECS unit. A small-sized ECS is considered in this study. Therefore, similar to the proposed frequency regulation in Chapter 10, an additional regulation power (from the diesel units) is required to keep the stored energy level of the ECS in a proper range.
Figure 12.4 illustrates the configuration of the coordinated controller for the diesel unit on the supervisor agent. In this figure, Wr and WECS are the target and measured (current) stored energies. PECS and Pm represent the regulation powers provided by the ECS and diesel units, respectively. In the proposed AGC scheme, the ECS provides the main function of the AGC, and the diesel units provide a supplementary function to support the charging or discharging operation on the ECS unit. Namely, a coordinated AGC between the ECS and the diesel units has been performed to balance the power demand and the total power generation.
FIGURE 12.4
Coordinated AGC system for diesel unit on the supervisor agent.
In order to realize the proposed coordinated AGC scheme, a multiagent system has been utilized, as shown in Figure 12.1. The required AGC performance is achieved through the charging/discharging operation on the ECS following the monitored frequency deviation ∆f on the diesel unit. As shown in Figure 12.1, three different types of agents are specified in the proposed multi-agent-based AGC system: monitoring agents for the distribution of required information through the computer network, control agents for the charging/ discharging operation on the ECS and also for the power regulation on the diesel units, and finally, a supervisor agent for the coordination between the ECS and the diesel units. These three agent types can communicate with each other through a secure computer network to achieve a desirable AGC performance.
12.2 Configuration of Laboratory System
The simplified single line diagram of the studied laboratory system is shown in Figure 12.5. Figure 12.6 shows an overview of the experimental laboratory system. The laboratory system consists of a 5 kVA generator driven by a DC motor representing the diesel unit, a 70 Wh ECS with the maximum charging/discharging power of 3 kW, a variable load, and the transmission line modules. The variations of power generation from the PV and the wind turbine units are represented by the variations of power consumption on the variable load. During the start-up process, the laboratory system is connected to the external commercial power source, i.e., the switch S1 is closed. Following the start-up process, the switch S1 is opened to change the study system to an isolated power system.
FIGURE 12.5
Single line diagram of the laboratory system.
FIGURE 12.6
Overview of the experimental laboratory system.
12.3 Experimental Results
The performance of the proposed AGC scheme is examined in the presence of various load disturbance scenarios. The tuning of control parameters was performed for the step load change scenario 1 shown in Figures 12.7 and 12.8. The tuned parameters for the ECS controller are as follows: KP = 4 and KI = 10. In this case, the step load change is applied just for a specific range of time. Therefore, the integration of the discharging power did not reach its critical level. Namely, the coordination from the diesel unit is not required in this case. However, in the cases of the step load change scenarios 2 and 3, the step load changes are not cleared; therefore, the coordination from the diesel unit was inevitable to keep the stored energy of the ECS within a prespecified range. The diesel unit cannot follow the fast random load change because of its response speed; therefore, the coordination is not considered for the random load change. For the large disturbance caused by the line switching S2, coordination is not necessary because any load change is not applied to the laboratory system.
FIGURE 12.7
Conventional AGC for step load change scenario 1.
FIGURE 12.8
Proposed AGC for step load change scenario 1 (ECS controller: KP = 4, KI = 10).
Typical experimental results are illustrated in Figures 12.7 to 12.14. In these figures, the frequency deviation ∆f (Hz) monitored on the generator (representing the diesel unit), the control signal UECS (V) for the charging or discharging operation on the ECS, the charging/discharging power PECS (kW) on the ECS, the ECS terminal voltage VECS (V), the generator power PG (kW), the generator terminal voltage VG (V), the power consumption PL (kW) on the variable load, and the terminal voltage VL (V) of the variable load are illustrated from the top to the bottom.
FIGURE 12.9
Proposed AGC for periodical load change (scenario 4).
The averaged frequency deviation and the maximum frequency deviation are shown in Table 12.1 for both the conventional AGC and the proposed multiagent-based AGC under different types of load changes, and the large disturbance given by the line switching. As clearly indicated in Table 12.1, the AGC performance is highly improved by applying the proposed multiagent-based AGC scheme. The estimated time delay is around 70 ms during the experiments. For the larger time delay, the compensation is inevitable to maintain better control performance.
The stored energy on the ECS is easily monitored by the voltage VECS (V) measured at the ECS terminal. During the experiments, the operation range of the ECS terminal voltage VECS (V) is specified from 140 to 240 V. As shown in Figures 12.10 and 12.11, the ECS terminal voltage was kept almost constant by the coordination from the generator representing the diesel unit.
FIGURE 12.10
Proposed AGC for step load change scenario 2.
FIGURE 12.11
Proposed AGC for step load change scenario 3.
FIGURE 12.12
Proposed AGC for random load change (scenario 5).
FIGURE 12.13
Random load change without control (scenario 5).
FIGURE 12.14
Proposed AGC under large disturbance without load change (scenario 6).
TABLE 12.1
Averaged and Maximum Frequency Deviation under Different Load Change Scenarios
12.4 Summary
An intelligent multiagent-based automatic generation control scheme for a power system case study with dispersed power sources such as photovoltaic, wind generation, diesel generation, and an energy capacitor system is proposed. An experimental study is used to demonstrate the capability of the proposed control structure. The experimental results clearly indicate the advantages of the proposed control scheme in comparison to the conventional AGC framework.
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