AbstractâNowadays, large-scale wind power farms (WPFs) bring new challenges for both electrical systems and communication networks. The communication ...
2014 International Symposium on Computer, Consumer and Control
Hierarchical Communication Network Architectures for Offshore Wind Power Farms
Mohamed A. Ahmed
Young-Chon Kim*
Department of Computer Engineering Chonbuk National University Jeonju, Korea mohamed@jbnu.ac.kr
Smart Grid Research Center Chonbuk National University Jeonju, Korea *Corresponding Author, yckim@jbnu.ac.kr
Abstract—Nowadays, large-scale wind power farms (WPFs) bring new challenges for both electrical systems and communication networks. The communication networks represent the essential part in WPF because they provide real time monitoring and control for wind turbines from a remote location (local control center). However, different wind turbine applications have different requirements such as data volume, latency, bandwidth, QoS, etc. This paper proposes hierarchical communication network architectures consisting of a turbine area network (TAN), farm area network (FAN) and control area network (CAN) for offshore WPFs. The wind turbines are modelled based on the logical node (LN) concepts of IEC 61400-25 standard. To keep pace with the current development of wind turbine technology, the network design takes into account the extension of the LNs for both wind turbine foundation and meteorological measurements. The communication network of WPF is configured as a switch-based architecture where each wind turbine has a dedicated link to the wind farm main switch. Servers at the control center are used for storing and processing the received data from WPF. The network architecture is modelled and evaluated by OPNET. We investigated the end-to-end (ETE) delay for different WPF applications. Our network architecture is validated by analyzing the simulation results.
requirement and latency for proper operations and data exchange between wind turbines and control center. Conventional WPF communication infrastructure is a switch-based architecture where independent sets of switches and communication links are used for different network applications such as wind turbine generator network, protection and control network and telephone and security network [1]. In order to reduce the cost of deploying independent communication networks, one common infrastructure sharing all turbines traffic should be considered. However, the requirements of different applications should be satisfied in order to guarantee the new network configuration. Nowadays, there is no unified communication standard available for WPF nor the integration between the WPFs and the smart grid [2]. Also, the IEC 61400-25-2 standard focuses mainly on onshore WPFs and lack the development in offshore wind turbines such as floating turbines [3]. In [4], we proposed the architecture, design, simulation and evaluation of hybrid communication networks (WiFi, ZigBee and Ethernet) for monitoring a large-scale wind turbine. A. Objective of the Paper This paper proposes communication network architectures for offshore WPFs with determined measurements. Compared with conventional network architectures where independent communication infrastructures are used for different applications, the proposed network model allows the network traffic such as analogue measurements (AM), status information (SI) and protection & control information (PCI) to share a common architecture. We consider the extension of logical nodes for wind turbine foundation and meteorological data. Also, we define the latency requirements of WPF communication network for different applications. OPNET modeler is used for modelling WPF communication network at different levels, such as turbine area network (TAN), farm area network (FAN) and control area network (CAN). The simulator is validated by measuring the amount of received traffic at control center servers. The network performance is evaluated, analyzed and discussed in view of end-to-end (ETE) delay for different link bandwidth.
Keywords- Wind Power Farm; Communication Network; IEC 61400-25; Logical Nodes; OPNET.
I.
INTRODUCTION
In recent days, the wind power farm of South Korea has been moving toward offshore due to the limited space of onshore wind power farms (WPFs). The offshore WPFs are scattered in remote areas, where the selected locations are chosen based on wind speed, water depth and distance to shore. It is important to monitor WPFs with higher capacity as the size and numbers of wind turbines are continuously increasing. In order to provide monitoring and control in real time, a reliable bidirectional communication infrastructure is needed. With the absence of unified communication architecture, most of turbine manufacturers have developed their own monitoring and control systems. The performance of the monitoring and control system depends mainly on the communication capability to support the exchange of real-time data between the control centers and WPFs. Therefore, the WPF communication infrastructure requires high stability and reliability for the condition monitoring and control of wind turbines. Also, it should satisfy the bandwidth 978-1-4799-5277-9/14 $31.00 © 2014 IEEE DOI 10.1109/IS3C.2014.85
B. Outline The rest of this paper is organized as follows: Section 2 describes the wind power farm communication network. In section 3, we present the WPF modeling using OPNET. 299
the wind farm communication networks are configured based on the electric power topology, where the optical fiber cables are embedded in the electric power cable. The network configuration in this work is based on conventional switch-based architecture where the communication links between the control center and wind turbines are configured to have a direct wired connection as shown in Fig. 2.
Section 4 shows the simulation results. Finally, section 5 presents the conclusion and the future work. II.
WIND POWER FARM COMMUNICATION NETWORK
The communication network architecture of WPF is divided into three levels: turbine area network (TAN), farm area network (FAN) and control area network (CAN). A. Turbine Area Network Wind turbine consists of different parts, such as the rotor, generator, blades, etc. Each part is equipped with different types of sensors, actuators and measuring devices. A front end (FE) unit is installed inside the wind turbine nacelle, which consists of a data acquisition device (sensor unit and processing unit), main controller and communication interface. Based on the logical node (LN) concept of IEC 61400-25 standard, each wind turbine is represented by 9 LNs (WROT, WTRM, WGEN, WCNV, WTRF, WNAC, WYAW, WTOW and WMET). Each LN contains different types of data, such as analogue information, status information and control information. To keep pace with the current development of wind turbine technology, we considered the extension of LNs for the wind turbine foundation (WFOU) and the meteorological data defined in [3]. Figure 1 shows the communication network inside the wind turbine.
Figure 2. Structure of farm area network (FAN).
C. Control Area Network The main function of the control center is to maintain an efficient and continuous monitoring for the WPFs. The local control center (LCC) is dedicated for a single WPF. The LCC is responsible for collecting information from wind turbines, meteorological masts and substations as shown in Fig. 3. Independent servers are used for different applications received from the turbines front ends. The control center is designed according to the amount of information managed, the criticality of data and the need to utilize the data in the future [5].
Figure 1. Structure of turbine area network (TAN).
B. Farm Area Network The WPF consists of wind turbines, meteorological tower and control center. Most of the turbine manufacturers include their own SCADA system as a part of WPF supply where the SCADA function is to communicate with wind turbines, receive/send information and start/stop commands. The meteorological data have essential information estimated from the forecast due the deviations between energy offered to the energy market and real time power output [5]. The communication network of WPF could be configured for wired architecture or wireless configuration, where the connection between wind turbines could be made with different topologies such as linear, star and ring. Usually,
Figure 3. Hierarchical communication network for a WPF.
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III.
MODELING WPF COMMUNICATION NETWORK IN OPNET
switch and the control center is 5 Km. Two scenarios are configured for the main communication link; full-duplex link 100 Mbps and 1000 Mbps, respectively.
In this section, the WPF communication network is modeled using OPNET. The models used for wind turbines, wind power farm and control center are discussed in more details. OPNET allows the design and study of communication networks, devices, protocols and applications [6]. Note that the conventional WPF architecture uses independent communication links and switches for different application, while in our network model all applications share the same physical link.
C. Modeling of Control Center Network The control center has a model of 3 servers and a main Ethernet switch. The three servers are SCADA server, protection server and meteorological server. The SCADA server receives the packets for analogue measurements and status data, while the protection server receives the packet from P&C IED devices. We configured the meteorological server to receive data packets from the meteorological tower installed at the WPF. Table 2 summarizes the communication network configuration for TAN, FAN and CAN.
A. Modeling the Wind Turbine Network To calculate the network traffic inside the wind turbine, we considered 73 analogue measurements and 29 status data for a WT [4]. The remote monitoring data from WTs sensors and measuring devices include temperature, rotor speed, pressure, pitch angle, vibration, voltage, current, power, power factor, humidity, wind speed, wind direction, oil level, frequency and torque. The measuring requirements for different sensors are calculated according to the sampling frequency and the number of channels. We considered the extension of LNs for the wind turbine foundation (WFOU) and the meteorological data as shown in Table 1. The remote monitoring data for WFOU include accelerometer, strain gauge, tilt, acoustic doppler current profile (ADCP), water level and water temperature while meteorological measurements include temperature, pressure, humidity, wind speed and wind direction. The wind turbines and meteorological mast are modeled using OPNET workstations. The Ethernet protocol is used for physical layer and data link layer while the network layer and transport layer adopt the TCP/IP. The application layer in our model is configured for FTP.
WFOU
Met Mast
TABLE I.
TABLE II. Level
Sampling Freq.
# Channel
Data (Bytes/s)
Temperature
1 Hz
1
2
Pressure
100 Hz
1
200
Humidity
1 Hz
1
2
Wind Direction
3 Hz
1
6
Wind Speed
3 Hz
1
6
Accelerometer
200 Hz
3
1200
Strain gauge
10 Hz
3
Tilt-Inclinometer ADCP Water Level Water Temperature Total Traffic
10 Hz 2 Data rate 1,200 bits/sec Up to 2,000 meters 1 Hz 1 1 Hz
1
Application
Data rate
AM
225,544 bytes/sec
SI
58 bytes/sec
PCI
76,816 bytes/sec
Link Bandwidth
100 Mbps, 1Gbps
Wind Turbines
10
Wind Turbine Network
Wind Farm Network
Control Center Network
Ethernet Switch
1
Met. Mast
1,670 Bytes/sec
Link Bandwidth
100 Mbps, 1 Gbps
SCADA Server
1
PCI server
1
Meteorological Server
1
Ethernet Switch
1
Link Bandwidth
100 Mbps, 1 Gbps
D. Requirements for the WPF Communication Network There are different standards related to the communication network requirements in power system such as IEEE C37.1 for SCADA and automation system, IEEE 1379 for interoperability of IEDs and RTUs, and IEEE 1646 for internal and external to electric substation [7]. The main requirements of the WPF communication network are latency, bandwidth and quality of service (QoS). In this work, we consider the communication timing requirements for electric substation automation based on IEEE 1646 standard as shown in Table 3. For example, the requirement of time delay for the protection information is 4ms within a substation and 8-12 ms external to the substation. The network bandwidth is configured for 100 Mbps and 1Gbps. For QoS, we assume that all WPF applications have the same priority.
MEASURING REQUIREMENTS FOR SENSOR DATA
Measurement
WPF NETWORK TRAFFIC
60 40 150 2
TABLE III.
2
1,670 Bytes/sec
B. Modeling of Wind Farm Network We considered a wind farm consists of 10 wind turbines and a meteorological tower. Switch-based architecture is considered for network configuration where each wind turbine has a dedicated link to the wind farm main switch. The distance between the wind farm main
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TIMING REQUIREMENTS FOR DIFFERENT APPLICATIONS (IEEE 1646 STD)
Information Type
Internal
External
Monitoring and control
16 ms
1s
Protection
4 ms
8-12 ms
Operation and maintenance
1s
10 s
IV.
SIMULATION RESULTS
A. Network Model Validation Figure 4 shows the communication network model for WPF in OPNET. The network model of WPF is validated by measuring the amount of received traffic at control center servers and compares it with the amount of the generated transmission data. Figure 5 and Fig. 6 show the received traffic at the control center for different applications. The received traffic for analogue measurements, status data and protection IED are 2,255,440 Bytes/sec, 580 Bytes/sec and 760,160 Bytes/sec, respectively. Also, the received traffic at the meteorological mast server is 1,670 Bytes/Sec. All received traffic at the control center agrees with our calculation for 10 wind turbines.
Met. Mast 1,670 Bytes/sec
Status data 580 Bytes/sec
192.0.0.1
Figure 5. Received traffic at control center servers. 192.0.0.2 192.0.0.3 192.0.0.14
192.0.0.11
192.0.0.4 Main Communication Link
192.0.0.5
192.0.0.12
192.0.0.6
192.0.0.7
Analogue measurements 2,255,440 Bytes/sec
192.0.0.13
192.0.0.8
192.0.0.9 Protection IED 768,160 Bytes/sec
192.0.0.10
Figure 4. Network configuration of wind power farm in OPNET.
B. End-to-End Delay In OPNET, the end-to-end (ETE) delay represents the time (in seconds) taken for the packet to reach its destination or the difference between the time a packet arrives at its destination and the creation time of the packet. There are three applications: SCADA, protection and meteorological data. Each of these applications requires different response time. Figure 7 and Fig. 8 show the average ETE delay for different WPF applications. The average ETE delay with 100Mbps link bandwidth are 8.70 ms, 11.75 ms, 2.02 ms for SCADA, protection and meteorological data, respectively. Table 4 shows the average ETE delay with link capacity of 100 Mbps and 1Gbps. Compared with the communication timing requirements in Table 3, the ETE delay of proposed network model satisfies the requirement of electric power system for both link bandwidth of 100 Mbps and 1Gbps. TABLE IV.
Figure 6. Received traffic at control center servers.
Link BW 100Mbps
Protection Server
SCADA Server
Met. Mast Server
AVERAGE ETE DELAY FOR WPF
Link Capacity
SCADA
PCI
Met. Mast
100 Mbps
8.70 ms
11.75 ms
2.02 ms
1Gbps
0.83 ms
1.13 ms
0.57 ms
Figure 7. Average ETE delay for WPF traffic with link BW (100Mbps).
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[7] Link BW 1Gbps
Protection Server
SCADA Server
Met. Mast Server
Figure 8. Average ETE delay for WPF traffic with link BW (1Gbps).
V.
CONCLUSIONS
This paper proposes a hierarchical communication network architecture for offshore WPFs. We evaluated the hierarchical architecture through the OPNET modeler. The network model is validated by measuring the amount of traffic received at the control center servers. We investigated network delay according to different link bandwidths. It was observed that increasing the link bandwidth from 100 Mbps to 1 Gbps offered better performance for different WPF applications. In case of 1 Gbps, the average ETE delay for SCADA, protection and meteorological data are 0.83 ms, 1.13 ms and 0.75 ms, respectively. The simulation results showed that the proposed communication architecture satisfies the network requirements of the power system for different WPF applications. The proposed network will be extended in order to implement a reliable communication network for large-scale WPFs in future work. ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) funded by the Korea government (MSIP) (2010-0028509). REFERENCES [1]
[2]
[3]
[4]
[5]
[6]
M. Goraj, Y. Epassa, and D. Meadows, “Designing and deploying ethernet networks for offshore wind power applications-a case study,” in Proc. DPSP’10, 2010, pp. 1-5. B. K. Singh, et al., “Survey on communication architectures for wind energy integration with the smart grid,” International Journal of Environmental Studies, vol. 70, no. 5, 2013, pp. 765-776. T. H. Nguyen, A. Prinz, T. Friisø, and R. Nossum, “Smart grid for offshore wind farms: Towards an information model based on the IEC 61400-25 standard,” in Proc. ISGT, 2012, pp. 1-6. M. A. Ahmed and Y.-C. Kim, “Hybrid communication network architectures for monitoring large-scale wind turbine,” Journal of Electrical Engineering & Technology, vol. 8, no. 6, 2013, pp. 1626-1636. J.-M. Gallardo-Callesa, A. Colmenar-Santosb, J. Ontañon-Ruiza, and M. Castro-Gilb, “Wind control centres: State of the art,” Renewable Energy, vol. 51, 2013, pp. 93-100. OPNET Modeler, OPNET Technologies. http://www.OPNET.com
303
R. H. Khan and J. Y. Khan, “A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network,” Computer Networks, vol. 57, 2013, pp. 825-845.
