Operation and Power Flow Control of Multi-Terminal DC Networks for Grid Integration of Offshore Wind Farms Using Genetic Algorithms
Abstract
:1. Introduction
2. Model Description
Line Name | Nodes | Length [km] | Line Name | Nodes | Length [km] |
---|---|---|---|---|---|
line1 | N1-N4 | 60 | line5 | N5-N8 | 120 |
line2 | N4-N7 | 120 | line6 | N5-N6 | 220 |
line3 | N4-N5 | 190 | line7 | N3-N6 | 50 |
line4 | N2-N5 | 60 | line8 | N6-N9 | 110 |
Parameter | Symbol | Unit | Value |
---|---|---|---|
System Base Power | MVA | 1000 | |
AC Grid Short-Circuit Power | MVA | 3000 | |
AC Grid Voltage-HV Side | kV | 380 | |
AC Grid Voltage-LV Side | kV | 275 | |
OWF Collection Voltage | kV | 33 | |
OWF-VSC Voltage | kV | 275 | |
Traformers Impedance | pu | 0.005 + j0.100 | |
VSC Filter Size-AC Grid | MVA | 200 | |
VSC Filter Size-OWF | MVA | 50 | |
Phase reactor Impedance | pu | 0.003 + j0.150 | |
VSC DC-side Capacitor | C | μF | 75 |
MTDC Network Voltage | kV | ±320 | |
DC Cable Resistance | Ω/km | 0.0195 | |
DC Cable Inductance | mH/km | 19 | |
DC Cable Capacitance | nF/km | 220 | |
DC Cable Cross Section | mm | 2200 | |
DC Cable Rated Current | kA | 2.086 |
2.1. AC Network Model
2.2. Wind Farm Model
2.3. Wind Turbine Model
2.4. VSC-HVDC Model
2.4.1. Grid-Side VSC Control
2.4.2. Wind-Farm VSC Control
2.5. DC Network Model
3. MTDC Control Description
3.1. The Distributed Voltage Control Method
3.2. Genetic Algorithm
- no need for calculating derivatives;
- no information about the optimization goals is required besides evaluating the fitness function;
- it is possible to use continuous and discrete variables;
- it is easier to include problem constraints and variables boundaries;
- multi-objective optimization, even though not considered here, is possible.
Step 1—Population initialization
Parameter | Description | Parameter | Description |
---|---|---|---|
Population size | 150 | Mutation | 10% |
Tournament Selection | 4-th | Constraint violation | |
Mating Pool size | 9% | Upper boundary | 1.1 pu |
Crossover | 80% | Lower boundary | 0.9 pu |
Elite size | 1% |
Step 2—Fitness evaluation
Step 2.4—Constraints
Step 3—Termination Criterion
Step 4—Selection
Step 5—Genetic Operators
3.3. Information Flow
3.4. Telecommunication Needs for the DVC Method
Technology | Pros | Cons |
---|---|---|
Microwave | The infrastructure implementation cost is low since there is no need to install physical means. | Transmission repeaters might be necessary, leading to the necessity for offshore platforms. |
Satellite | Low implementation cost as all the needed infrastructure basically already exists. | Low data transmission speed and reliability can substantially impact the control cycle time. |
Fiber Optics | Data reliability, low transmission time, mature industry for installation of offshore optic cables. | The main downside is cost. It can be overcome if integrated in the offshore HVDC cables. |
3.4.1. Control Cycle Time—Information Traffic Time
3.4.2. VSAT Satellite
3.4.3. Fiber Optics
4. Case Studies
Case Sutdy | Description | |
---|---|---|
1. Start-up Procedures | 1a. MTDC Start-up | During start-up, the DC system voltage is charged from zero to the rated value by the GS-VSC terminals. |
2. Normal Operation | 2a. Priority | Priority is given to the country where the wind energy is being produced, i.e., all the power goes to the rightful country; while there is no energy trade. |
2b. Proportional Sharing | The sum of all the energy being produced by the OWFs is equally divided amongst all the countries through energy trade via the MTDC network. | |
2c. Power flow Reversal | The power flow of the German node is reversed. At first the power is flowing from the MTDC network into Germany. | |
3. Wind Curtailment | 3a. Low-wind Scenario | The MTDC system behavior is analyzed during wind curtailment in a scenario where the wind energy generation is low. |
3b. High-wind Scenario | The MTDC system behavior is analyzed during wind curtailment in a scenario where the wind energy generation is high. | |
4. AC Contingency | 4a. Low-wind Scenario | The system behavior is analyzed during an ac fault at the UK node in a scenario with low wind energy generation. In this case study the MTDC network is secure. |
4b. High-wind Scenario | The system behavior is analyzed during an ac fault at the UK node with high wind generation. In this the MTDC network may not be secure. |
5. Results
- The offshore wind farm power series is generated according to Section 2.2 (see Figure 3);
- An optimal power flow is solved via the genetic algorithm. For simulation purposes, a 5 s control cycle time based on the OWF average power has been employed (see Section 3.2, Section 3.3 and Section 3.4);
- The MTDC is simulated with the DVC based on the GA-generated direct voltage references.
5.1. Start-up Procedures (Case Study 1)
5.2. Normal Operation (Case Study 2)
5.3. Wind Curtailment (Case Study 3)
5.4. AC Contingency (Case Study 4)
5.5. Transmission Losses and Trade
6. Conclusions
Acknowledgments
References
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Pinto, R.T.; Rodrigues, S.F.; Wiggelinkhuizen, E.; Scherrer, R.; Bauer, P.; Pierik, J. Operation and Power Flow Control of Multi-Terminal DC Networks for Grid Integration of Offshore Wind Farms Using Genetic Algorithms. Energies 2013, 6, 1-26. https://doi.org/10.3390/en6010001
Pinto RT, Rodrigues SF, Wiggelinkhuizen E, Scherrer R, Bauer P, Pierik J. Operation and Power Flow Control of Multi-Terminal DC Networks for Grid Integration of Offshore Wind Farms Using Genetic Algorithms. Energies. 2013; 6(1):1-26. https://doi.org/10.3390/en6010001
Chicago/Turabian StylePinto, Rodrigo Teixeira, Sílvio Fragoso Rodrigues, Edwin Wiggelinkhuizen, Ricardo Scherrer, Pavol Bauer, and Jan Pierik. 2013. "Operation and Power Flow Control of Multi-Terminal DC Networks for Grid Integration of Offshore Wind Farms Using Genetic Algorithms" Energies 6, no. 1: 1-26. https://doi.org/10.3390/en6010001