Multiple Objective Compromised Method for Power Management in Virtual Power Plants
Abstract
:1. Introduction
2. Power Management in VPP
2.1. VPP as a Bridge between DERs and Public Grid
2.2. Electric Power Supply Chain in VPP
- (1)
- Microgrids, which have their own objectives and publish their output schedules in contracts;
- (2)
- Other suppliers which are scheduled by the VPP, such as wind farm or wind turbines which do not need any fuel, fuel batteries, and combined heat and power plants (CHP).
- (1)
- The sensitive loads which require high reliability and power quality with priority according to the contracts. Usually these loads are also predictable, such as industrial loads.
- (2)
- The public grid with the purchasing and selling contract. Form the view of the operators in public grid, it is expected the output power of the VPP is fixed to some extent according to the contrast especially when the power capacity of VPP is large.
- (3)
- The controllable load according to the load demand side management by ECCC [21].
- (4)
- The load which is random and can be shutdown in some situations according to the contracts, such as the smart houses and some unimportant loads.
- (1)
- The quantity and price of the electric power at different time segments;
- (2)
- Some special requirements for power reliability and power quality;
- (3)
- The fluctuating range of the set value;
- (4)
- The penalty methods.
3. Algorithm Formulation
3.1. Multi-objective Optimization with Priority
3.2. Fuzzy Description
3.3. Two-Step Compromised Method
3.4. Objective Functions
- (1)
- the wind turbine and solar energy are preferred for environmental protection;
- (2)
- the output power to the public grid is preset one-day ahead;
- (3)
- the actual lines are represented as an ideal line with impedance;
- (4)
- the reliability requirements of the customers are satisfied by the suitable topology design of the VPP.
3.5. The Constraints of the Power Suppliers
- (1)
- All Feeder lines must operate within their line capacity. The transmission capability of the feed is a basic requirement in VPP operations.
- (2)
- The DGs should operate within the pre-specified maximum limit. The rated powers of the converters have to be pre-determined depending on the maximum power flowing through them. The power suppliers cannot supply/absorb more power than the pre-specified maximum limit [22].
3.6. Optimization Process
4. Case Study
Node No. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
---|---|---|---|---|---|---|---|---|---|
Forecasted Power at jth hour (MW) | −0.107 | −0.1 | 0.1 | −0.2 | −0.3 | 0.46 | 0.1 | 0.1 | −0.105 |
Line | Node i | 6 | 1 | 6 | 3 | 6 | 6 | 7 | 8 |
---|---|---|---|---|---|---|---|---|---|
Node j | 1 | 2 | 3 | 4 | 5 | 7 | 8 | 9 | |
Length (km) | 1 | 6 | 3 | 7 | 12 | 5 | 3.5 | 5 |
Name | Price | |
---|---|---|
Fuel/Energy | Natural gas | ¥2.05/m3 |
H2 | ¥160.00/40 L(12.8 MPa) | |
O2 | ¥15.00/40 L(12.8 MPa) | |
Selling | Busy time | ¥0.83/kWh |
Normal time | ¥0.49/kWh | |
spare time | ¥0.17/kWh | |
Purchasing | Busy time | ¥0.65/kWh |
Normal time | ¥0.38/kWh | |
spare time | ¥0.13/kWh |
Areas | Level 1 | Level 2 | Level 3 | Min |
---|---|---|---|---|
I | f5 f4 | f3 f2 | f1 | 0.1077 |
II | f5 f3 | f4 f2 | f1 | 0.1086 |
III | f3 f5 | f2 f4 | f1 | 0.0282 |
IV | f3 f2 | f5 f4 | f1 | 0.0384 |
V | f3 f2 | f5 f1 | f4 | 0.0356 |
VI | f2 f3 | f1 f5 | f4 | 0.0014 |
VII | f2 f1 | f3 f5 | f4 | 0.0134 |
- Level 1: f3 and f2;
- Level 2: f4 and f5;
- Level 3: f1.
- k: k1 = 0.05, k2 = 0.05
Bus No. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
---|---|---|---|---|---|---|---|---|---|
V (p.u.) | 0.9866 | 0.9915 | 1.0032 | 0.9672 | 1.0310 | 0.9998 | 1.0475 | 1.0391 | 0.9971 |
Ang. (Rad.) | −0.0339 | −0.1486 | −0.0556 | −0.2886 | −0.6078 | −0.0009 | 0.0427 | 0.0327 | −0.0123 |
5. Conclusions
Acknowledgements
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Gong, J.; Xie, D.; Jiang, C.; Zhang, Y. Multiple Objective Compromised Method for Power Management in Virtual Power Plants. Energies 2011, 4, 700-716. https://doi.org/10.3390/en4040700
Gong J, Xie D, Jiang C, Zhang Y. Multiple Objective Compromised Method for Power Management in Virtual Power Plants. Energies. 2011; 4(4):700-716. https://doi.org/10.3390/en4040700
Chicago/Turabian StyleGong, Jinxia, Da Xie, Chuanwen Jiang, and Yanchi Zhang. 2011. "Multiple Objective Compromised Method for Power Management in Virtual Power Plants" Energies 4, no. 4: 700-716. https://doi.org/10.3390/en4040700