5 research outputs found
Optimal Connection of Offshore Wind Farm with Maximization of Wind Capacity to Power Systems considering Losses and Security Constraints
The technical, economic, and environmental constraints related to the construction of new transmission lines are complex issues related to the definition of points for connecting new offshore wind farms (OWFs) to the grid. In this context, it has become an important research topic to choose the best OWF connection point to a power system, among some geographically close to each other within a given region, aiming at ensuring maximum generation capacity of the wind farm and safe use of existing transmission network. The objective of this work is to present a methodology to determine the optimal OWF connection point in a power system, with maximum penetration of firm wind power and minimum loss, considering security constraints related to the βNβ1β contingency criterion, exchange limits between areas, and a strategy to reduce the number of constraints in the optimization problem. The algorithm is modeled using a Mixed Integer Nonlinear Programming (MINLP), and it is evaluated in a tutorial system and three well-known other networks from literature: IEEE 14-Bus, IEEE RTS-79, and Southern Brazilian System
Optimal planning of electrical infrastructure of large wind power plants
ΠΡΠ΅Π΄ΠΌΠ΅Ρ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° Π΄ΠΎΠΊΡΠΎΡΡΠΊΠ΅ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠ΅ ΡΠ΅ ΡΠ°Π·Π²ΠΎΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π° Π·Π°
ΡΠ½Π°ΠΏΡΠ΅ΡΠ΅ΡΠ΅ Π΅ΠΊΠΎΠ½ΠΎΠΌΡΠΊΠΈΡ
ΠΈ ΡΠ΅Ρ
Π½ΠΈΡΠΊΠΈΡ
ΡΡΠ»ΠΎΠ²Π° ΠΏΠ»Π°Π½ΠΈΡΠ°ΡΠ° ΠΈ ΠΈΠ·Π³ΡΠ°Π΄ΡΠ΅ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅. ΠΡΠ½ΠΎΠ²Π½ΠΈ
Π΄ΠΎΠΏΡΠΈΠ½ΠΎΡΠΈ ΡΡ ΡΠ»Π΅Π΄Π΅ΡΠΈ:
1. Π Π°Π·Π²ΠΈΡΠ΅Π½ ΡΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» Π·Π° ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΡ ΠΈΠ·Π±ΠΎΡΠ° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°.
Π£ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠΈ ΡΠ΅ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» Π·Π° ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΡ ΠΈΠ·Π±ΠΎΡΠ° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° Π·Π°
ΠΏΠΎΠ·Π½Π°ΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΡ Π²Π΅ΡΡΠ°. ΠΡΠ½ΠΎΠ²Π½ΠΈ Π΅Π»Π΅ΠΌΠ΅Π½ΡΠΈ ΠΏΡΠΈ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΠΈ ΠΈΠ·Π±ΠΎΡΠ° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° ΡΡ:
Π²ΠΈΡΠΈΠ½Π° ΡΡΡΠ±Π°, ΠΏΡΠ΅ΡΠ½ΠΈΠΊ Π²Π΅ΡΡΠΎΡΡΡΠ±ΠΈΠ½Π΅ ΠΈ Π½Π°Π·ΠΈΠ²Π½Π° ΡΠ½Π°Π³Π° Π²Π΅ΡΡΠΎΠ³Π΅Π½Π΅ΡΠ°ΡΠΎΡΠ°. ΠΠΎΠ΄Π΅Π» Π²ΡΡΠΈ
Π²Π°ΡΠΈΡΠ°ΡΠΈΡΡ ΠΊΡΡΡΠ½ΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΠ°ΡΠ° ΠΈ ΠΏΡΠΎΡΠ°ΡΡΠ½ ΡΠΊΡΠΏΠ½ΠΈΡ
Π°ΠΊΡΡΠ΅Π»ΠΈΠ·ΠΎΠ²Π½ΠΈΡ
ΡΡΠΎΡΠΊΠΎΠ²Π° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°,
ΠΊΠ°ΠΎ ΠΈ Π³ΠΎΠ΄ΠΈΡΡΠ΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΠ΅ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅ Π΅Π½Π΅ΡΠ³ΠΈΡΠ΅. Π£ Π½Π°Π²Π΅Π΄Π΅Π½ΠΎΠΌ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΎΠ½ΠΎΠΌ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ
ΠΏΠΎΡΡΠΎΡΠ΅ ΡΠ΅Ρ
Π½ΠΈΡΠΊΠ° ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅ΡΠ° Ρ ΠΏΠΎΠ³Π»Π΅Π΄Ρ ΠΌΠΈΠ½ΠΈΠΌΠ°Π»Π½ΠΈΡ
ΠΈ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»Π½ΠΈΡ
Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΠ°ΡΠ°
ΠΊΠΎΡΠ΅ Π½Π°ΠΌΠ΅ΡΠ΅ ΡΠ°ΠΌ ΠΏΡΠΎΠΈΠ·Π²ΠΎΡΠ°Ρ ΠΎΠΏΡΠ΅ΠΌΠ΅, Π° ΠΌΠΎΠΆΠ΅ ΡΠ²Π°ΠΆΠΈΡΠΈ ΠΈ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅ΡΠ° ΠΊΠΎΡΠ° Π½Π°ΠΌΠ΅ΡΠ΅ Π»ΠΎΠΊΠ°ΡΠΈΡΠ° Π½Π°
ΠΊΠΎΡΠΎΡ ΡΠ΅ ΠΏΠ»Π°Π½ΠΈΡΠ° ΠΈΠ·Π³ΡΠ°Π΄ΡΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅. ΠΠΎΠ΄Π΅Π» ΡΠ΅ Π±Π°Π·ΠΈΡΠ°Π½ Π½Π° Π³Π΅Π½Π΅ΡΡΠΊΠΎΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΡ ΠΊΠΎΡΠΈ
Π½Π°ΠΊΠΎΠ½ ΠΎΠ΄ΡΠ΅ΡΠ΅Π½ΠΎΠ³ Π±ΡΠΎΡΠ° ΠΈΡΠ΅ΡΠ°ΡΠΈΡΠ° Π΄ΠΎΠ»Π°Π·ΠΈ Π΄ΠΎ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½ΠΈΡ
ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠ° ΠΊΠΎΡΠΈ Π·Π°Π΄ΠΎΠ²ΠΎΡΠ°Π²Π°ΡΡ
ΡΡΠ½ΠΊΡΠΈΡΡ ΡΠΈΡΠ° ΠΈ Π·Π°Π΄Π°ΡΠ° ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅ΡΠ°. Π Π°Π·Π²ΠΈΡΠ΅Π½ΠΈ Π°Π»Π³ΠΎΡΠΈΡΠ°ΠΌ ΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» ΠΈΠΌΠ°ΡΡ ΠΎΠΏΡΡΠΈ
ΠΊΠ°ΡΠ°ΠΊΡΠ΅Ρ ΡΡ. ΠΏΡΠΈΠΌΠ΅Π½ΡΠΈΠ²ΠΈ ΡΡ Π·Π° ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΡ ΠΈΠ·Π±ΠΎΡΠ° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° Π·Π° Π»ΠΎΠΊΠ°ΡΠΈΡΠ΅ ΡΠ° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΠΌ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΠΌΠ° Π²Π΅ΡΡΠ°. ΠΡΠΈΠΌΠ΅Π½ΠΎΠΌ ΠΌΠΎΠ΄Π΅Π»Π° ΠΎΠ±Π΅Π·Π±Π΅ΡΡΡΠ΅ ΡΠ΅ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½ΠΎ ΠΈΡΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ ΠΏΠΎΡΠ΅Π½ΡΠΈΡΠ°Π»Π°
Π²Π΅ΡΡΠ° Π½Π° ΠΎΠ΄ΡΠ΅ΡΠ΅Π½ΠΎΡ Π»ΠΎΠΊΠ°ΡΠΈΡΠΈ, Π° ΡΠΈΠΌΠ΅ ΠΈ Π²Π΅ΡΠΈ ΠΏΡΠΎΡΠΈΡ Π²Π»Π°ΡΠ½ΠΈΠΊΡ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅. ΠΠ°ΠΎ ΡΠ»Π°Π·Π½ΠΈ
ΠΏΠΎΠ΄Π°ΡΠΈ ΠΊΠΎΡΠΈΡΡΠ΅ ΡΠ΅ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈ ΠΠ΅ΡΠ±ΡΠ»ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ΅ Π²Π΅ΡΡΠ° ΠΈ Π²ΠΈΡΠΈΠ½ΡΠΊΠΈ ΠΊΠΎΠ΅ΡΠΈΡΠΈΡΠ΅Π½Ρ ΡΠΌΠΈΡΠ°ΡΠ°
Π²Π΅ΡΡΠ°. ΠΠ° ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΈΠΌ ΠΏΡΠΈΠΌΠ΅ΡΠΈΠΌΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π° Π½Π° Π»ΠΎΠΊΠ°ΡΠΈΡΠ°ΠΌΠ° ΡΠ° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΠΌ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΠΌΠ°
ΠΠ΅ΡΠ±ΡΠ»ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ΅ Π²Π΅ΡΡΠ° Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠ°Π½Π° ΡΠ΅ ΠΏΡΠ°ΠΊΡΠΈΡΠ½Π° ΡΠΏΠΎΡΡΠ΅Π±ΡΠΈΠ²ΠΎΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎΠ³
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π°.
2. Π Π°Π·Π²ΠΈΡΠ΅Π½ ΡΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» Π·Π° ΠΏΡΠΎΡΠ°ΡΡΠ½ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ ΠΏΠΎΠ²ΡΡΠΈΠ½Π΅ ΠΏΠΎΠΏΡΠ΅ΡΠ½ΠΎΠ³
ΠΏΡΠ΅ΡΠ΅ΠΊΠ° ΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΈΠΊΠ° Ρ ΠΈΠ½ΡΠ΅ΡΠ½ΠΎΡ ΠΊΠ°Π±Π»ΠΎΠ²ΡΠΊΠΎΡ ΠΌΡΠ΅ΠΆΠΈ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅.
ΠΠ°ΠΊΠΎ ΠΏΡΠΎΡΡΠΎΡΠ½ΠΈ ΡΠ°ΡΠΏΠΎΡΠ΅Π΄ Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° Ρ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π°ΠΌΠ° Π²Π΅Π»ΠΈΠΊΠ΅ ΡΠ½Π°Π³Π΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΠ΅
ΡΠ΅Π»Π°ΡΠΈΠ²Π½ΠΎ Π²Π΅Π»ΠΈΠΊΠ° ΠΌΠ΅ΡΡΡΠΎΠ±Π½Π° ΡΠ΄Π°ΡΠ΅Π½ΠΎΡΡ, Π΄ΡΠΆΠΈΠ½Π° ΠΊΠ°Π±Π»ΠΎΠ²ΡΠΊΠ΅ ΠΊΠΎΠ»Π΅ΠΊΡΠΎΡΡΠΊΠ΅ ΠΌΡΠ΅ΠΆΠ΅ ΠΌΠΎΠΆΠ΅ Π±ΠΈΡΠΈ
Π½Π΅ΠΊΠΎΠ»ΠΈΠΊΠΎ Π΄Π΅ΡΠ΅ΡΠΈΠ½Π°, ΠΏΠ° ΠΈ ΡΡΠΎΡΠΈΠ½Π° ΠΊΠΈΠ»ΠΎΠΌΠ΅ΡΠ°ΡΠ°, ΡΠ΅ ΡΡ Π³ΡΠ±ΠΈΡΠΈ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅ Π΅Π½Π΅ΡΠ³ΠΈΡΠ΅ Ρ ΡΠΎΡ
Π·Π½Π°ΡΠ°ΡΠ½ΠΈ. ΠΠΎΡΠΈΡΡΠ΅ΡΠ΅ Π²Π΅ΡΠΈΡ
ΠΏΡΠ΅ΡΠ΅ΠΊΠ° ΠΊΠ°Π±Π»ΠΎΠ²Π° Ρ ΠΎΠ΄Π½ΠΎΡΡ Π½Π° ΡΠ΅Ρ
Π½ΠΈΡΠΊΠ΅ Π·Π°Ρ
ΡΠ΅Π²Π΅ ΡΠ΅ ΡΠ΅ΡΡΠΎ ΠΎΠΏΡΠ°Π²Π΄Π°Π½ΠΎ
ΠΈ ΠΌΠΎΠΆΠ΅ ΠΎΠ±Π΅Π·Π±Π΅Π΄ΠΈΡΠΈ Π·Π½Π°ΡΠ°ΡΠ½ΠΎ ΠΏΠΎΠ²Π΅ΡΠ°ΡΠ΅ Π΅ΡΠΈΠΊΠ°ΡΠ½ΠΎΡΡΠΈ, ΠΊΠ°ΠΎ ΠΈ Π±ΠΎΡΠ΅ Π΅Π½Π΅ΡΠ³Π΅ΡΡΠΊΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅ΡΠ΅
Π΅Π»Π΅ΠΊΡΡΠ°Π½Π΅. ΠΠΎΠ΄Π΅Π» ΡΠ°Π·Π²ΠΈΡΠ΅Π½ Ρ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠΈ Π²ΡΡΠΈ ΠΏΡΠΎΡΠ°ΡΡΠ½ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½ΠΎΠ³ ΠΏΡΠ΅ΡΠ΅ΠΊΠ° ΠΊΠ°Π±Π»Π° Π½Π° ΠΊΠΎΡΠΈ ΡΠ΅
ΠΏΡΠΈΠΊΡΡΡΠ΅Π½ ΠΏΡΠΎΠΈΠ·Π²ΠΎΡΠ°Π½ Π±ΡΠΎΡ Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°, ΠΊΡΠΎΠ· ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΡ ΠΎΠ΄Π½ΠΎΡΠ° ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½ΠΈΡ
ΠΈ
Π΅ΠΊΡΠΏΠ»ΠΎΠ°ΡΠ°ΡΠΈΠΎΠ½ΠΈΡ
ΡΡΠΎΡΠΊΠΎΠ²Π° ΡΡ. ΡΡΠΎΡΠΊΠΎΠ²Π° ΡΡΠ»Π΅Π΄ Π³ΡΠ±ΠΈΡΠ°ΠΊΠ° ΠΏΠΎ ΡΠ΅Π΄ΠΈΠ½ΠΈΡΠΈ Π΄ΡΠΆΠΈΠ½Π΅ ΠΊΠ°Π±Π»Π°. Π‘
ΠΎΠ±Π·ΠΈΡΠΎΠΌ Π½Π° ΡΠΎ Π΄Π° ΡΠ΅ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½ΠΈ ΡΡΠΎΡΠΊΠΎΠ²ΠΈ ΠΈΠ·Π΄Π²Π°ΡΠ°ΡΡ Π½Π° ΠΏΠΎΡΠ΅ΡΠΊΡ, ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ Ρ ΡΠ°Π·ΠΈ ΠΈΠ·Π³ΡΠ°Π΄ΡΠ΅
Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅, Π° ΡΡΠΎΡΠΊΠΎΠ²ΠΈ ΡΡΠ»Π΅Π΄ Π³ΡΠ±ΠΈΡΠ°ΠΊΠ° ΡΠ΅ Π³Π΅Π½Π΅ΡΠΈΡΡ ΡΠΎΠΊΠΎΠΌ Π΅ΠΊΡΠΏΠ»ΠΎΠ°ΡΠ°ΡΠΈΡΠ΅, Π²ΡΡΠΈ ΡΠ΅
Π°ΠΊΡΡΠ΅Π»ΠΈΠ·Π°ΡΠΈΡΠ° ΡΡΠΎΡΠΊΠΎΠ²Π°, ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΊΠΎΡΠΈΡΡΠΈ ΡΠ΅ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈ Π΅ΠΊΠΎΠ½ΠΎΠΌΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π». ΠΡΠ΅Π΄Π½ΠΎΡΡ
ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½ΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π° ΡΠ΅ ΡΡΠΎ ΡΡ ΠΏΡΠΎΡΠ°ΡΡΠ½ΠΈ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ ΡΠΎΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ ΠΈ ΠΏΡΠ΅ΡΠ΅ΠΊΠ° ΠΊΠ°Π±Π»ΠΎΠ²Π°
ΡΠ°ΡΠΏΡΠ΅Π³Π½ΡΡΠΈ, ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΌΠΎΠ³Ρ ΡΠ΅ ΡΠ΅ΡΠ°Π²Π°ΡΠΈ ΠΎΠ΄Π²ΠΎΡΠ΅Π½ΠΎ. ΠΡΠΈΠΌΠ΅Π½ΠΎΠΌ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π° Ρ ΠΏΠ»Π°Π½Π΅ΡΡΠΊΠΎΡ
ΡΠ°Π·ΠΈ ΡΠ°Π·Π²ΠΎΡΠ° ΠΏΡΠΎΡΠ΅ΠΊΡΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ ΠΌΠΎΠΆΠ΅ ΡΠ΅ ΠΎΠΏΡΠΈΠΌΠΈΠ·ΠΎΠ²Π°ΡΠΈ ΡΠ²Π°ΠΊΠΈ ΠΎΠ΄ ΡΠΈΠ΄Π΅ΡΠ° Π½Π° ΠΊΠΎΡΠΈ ΡΠ΅
ΠΏΡΠΈΠΊΡΡΡΠ΅Π½ ΠΏΡΠΎΠΈΠ·Π²ΠΎΡΠ°Π½ Π±ΡΠΎΡ Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°. ΠΠ° ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠΌ ΠΏΡΠΈΠΌΠ΅ΡΡ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ Ρ ΠΠ°Π½Π°ΡΡ
ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ ΡΠ΅ Π΄Π° ΡΠ΅ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½ΠΈΠΌ ΠΈΠ·Π±ΠΎΡΠΎΠΌ ΠΏΡΠ΅ΡΠ΅ΠΊΠ° ΠΊΠ°Π±Π»ΠΎΠ²Π° ΠΌΠΎΠ³Ρ Π·Π½Π°ΡΠ°ΡΠ½ΠΎ ΡΠΌΠ°ΡΠΈΡΠΈ ΡΡΠΎΡΠΊΠΎΠ²ΠΈ
ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΠ΅, ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΏΠΎΠ²Π΅ΡΠ°ΡΠΈ ΡΠΊΡΠΏΠ°Π½ ΠΏΡΠΎΡΠΈΡ ΡΠΎΠΊΠΎΠΌ ΠΆΠΈΠ²ΠΎΡΠ½ΠΎΠ³ Π²Π΅ΠΊΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅.
3. Π Π°Π·Π²ΠΈΡΠ΅Π½ ΡΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» Π·Π° ΠΈΠ·Π±ΠΎΡ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½ΠΎΠ³ Π½Π°ΠΏΠΎΠ½ΡΠΊΠΎΠ³ Π½ΠΈΠ²ΠΎΠ° ΠΈ
ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ ΡΠ°ΡΠΊΠ΅ ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π° Π²Π΅Π»ΠΈΠΊΠΈΡ
ΡΠ½Π°Π³Π° Π½Π° ΠΏΡΠ΅Π½ΠΎΡΠ½Ρ ΠΌΡΠ΅ΠΆΡ.
ΠΠ·Π±ΠΎΡ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ ΡΠ°ΡΠΊΠ΅ ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ Π½Π° ΠΏΡΠ΅Π½ΠΎΡΠ½Ρ ΠΌΡΠ΅ΠΆΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ°
Π·Π°Ρ
ΡΠ΅Π²Π°Π½ Π·Π°Π΄Π°ΡΠ°ΠΊ ΠΊΠΎΡΠΈ ΠΌΠΎΡΠ° ΠΎΠ±ΡΡ
Π²Π°ΡΠΈΡΠΈ Π±ΡΠΎΡΠ½Π΅ ΡΠ°ΠΊΡΠΎΡΠ΅. Π£ Π²Π΅Π»ΠΈΠΊΠΎΠΌ Π±ΡΠΎΡΡ ΡΠ»ΡΡΠ°ΡΠ΅Π²Π° Ρ ΠΏΠΎΠ³Π»Π΅Π΄Ρ
ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ Π½Π° ΠΏΡΠ΅Π½ΠΎΡΠ½Ρ ΠΌΡΠ΅ΠΆΡ ΠΏΠΎΡΡΠΎΡΠ΅ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Π΅ ΡΠ°ΡΠΊΠ΅ ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ°, ΠΏΠ°
ΡΠ΅ ΠΏΠΎΡΡΠ°Π²ΡΠ° ΠΏΠΈΡΠ°ΡΠ΅ ΠΈΠ·Π±ΠΎΡΠ° ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ ΡΠ°ΡΠΊΠ΅ Ρ ΠΊΠΎΡΠΎΡ ΡΠ΅ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π° Π±ΠΈΡΠΈ ΠΏΡΠΈΠΊΡΡΡΠ΅Π½Π° ΠΈ
Π Π΅Π·ΠΈΠΌΠ΅
iv
ΠΠΎΠΊΡΠΎΡΡΠΊΠ° Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠ°
ΠΠ½Π° ΠΠ΅ΡΡΠΎΠ²ΠΈΡ
ΠΏΠ»Π°ΡΠΈΡΠ°ΡΠΈ ΠΏΡΠΎΠΈΠ·Π²Π΅Π΄Π΅Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Ρ Π΅Π½Π΅ΡΠ³ΠΈΡΡ ΡΠΎΠΊΠΎΠΌ Π΅ΠΊΡΠΏΠ»ΠΎΠ°ΡΠ°ΡΠΈΡΠ΅. ΠΠΎΡΠ΅Π½ΡΠΈΡΠ°Π»Π½Π΅ ΡΠ°ΡΠΊΠ΅
ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° ΠΌΠΎΠ³Ρ ΡΠ΅ ΡΠ°Π·Π»ΠΈΠΊΠΎΠ²Π°ΡΠΈ ΠΏΠΎ ΡΠ΄Π°ΡΠ΅Π½ΠΎΡΡΠΈ, Π°Π»ΠΈ ΠΈ Ρ ΠΏΠΎΠ³Π»Π΅Π΄Ρ Π½Π°ΠΏΠΎΠ½ΡΠΊΠΎΠ³ Π½ΠΈΠ²ΠΎΠ°, ΠΏΠ° ΡΠ΅
ΠΈΠ·Π±ΠΎΡ ΡΠ°ΡΠΊΠ΅ ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° ΠΏΡΠΎΡΠΈΡΡΡΠ΅ ΠΈ Π½Π° ΠΈΠ·Π±ΠΎΡ Π½Π°ΠΏΠΎΠ½ΡΠΊΠΎΠ³ Π½ΠΈΠ²ΠΎΠ° Π½Π° ΠΊΠΎΡΠΈ ΡΠ΅ Π±ΠΈΡΠΈ ΠΏΡΠΈΠΊΡΡΡΠ΅Π½Π°
Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π°.
Π Π°Π·Π²ΠΈΡΠ΅Π½ΠΈ ΠΌΠΎΠ΄Π΅Π» Π²ΡΡΠΈ ΠΏΡΠΎΡΠ°ΡΡΠ½ ΡΠΊΡΠΏΠ½ΠΈΡ
Π°ΠΊΡΡΠ΅Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΈΡ
ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½ΠΈΡ
ΠΈ
Π΅ΠΊΡΠΏΠ»ΠΎΠ°ΡΠ°ΡΠΈΠΎΠ½ΠΈΡ
ΡΡΠΎΡΠΊΠΎΠ²Π° ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° Π½Π° ΠΏΡΠ΅Π½ΠΎΡΠ½Ρ ΠΌΡΠ΅ΠΆΡ, Ρ ΡΡΠ½ΠΊΡΠΈΡΠΈ ΡΠ΄Π°ΡΠ΅Π½ΠΎΡΡΠΈ ΠΎΠ΄
ΠΏΡΠΈΠΊΡΡΡΠ½Π΅ ΡΠ°ΡΠΊΠ΅. ΠΠΎΡΠ΅Π΄ ΡΡΠΎΡΠΊΠΎΠ²Π° ΠΎΠ΄ΡΠΆΠ°Π²Π°ΡΠ°, Ρ Π΅ΠΊΡΠΏΠ»ΠΎΠ°ΡΠ°ΡΠΈΠΎΠ½Π΅ ΡΡΠΎΡΠΊΠΎΠ²Π΅ ΡΡ ΡΠ²ΡΡΡΠ°Π½ΠΈ ΠΈ
ΡΡΠΎΡΠΊΠΎΠ²ΠΈ Π½Π΅ΠΈΡΠΏΠΎΡΡΡΠ΅Π½Π΅ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅ Π΅Π½Π΅ΡΠ³ΠΈΡΠ΅ ΡΡΠ»Π΅Π΄ Π½Π΅ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠΈΠ²ΠΎΡΡΠΈ ΠΌΡΠ΅ΠΆΠ΅. OΠΏΡΠΈΠΌΠ°Π»Π°Π½
Π½Π°ΠΏΠΎΠ½ΡΠΊΠΈ Π½ΠΈΠ²ΠΎ ΠΈ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π° ΡΠ°ΡΠΊΠ° ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° ΠΎΠ΄ΡΠ΅ΡΠ΅Π½ΠΈ ΡΡ ΠΏΡΠΎΡΠ°ΡΡΠ½ΠΎΠΌ ΠΊΡΠΈΡΠΈΡΠ½ΠΈΡ
ΡΠ΄Π°ΡΠ΅Π½ΠΎΡΡΠΈ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΈΡ
ΠΏΡΠΈΠΊΡΡΡΠ½ΠΈΡ
ΡΠ°ΡΠ°ΠΊΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ ΠΎΠ΄ΡΠ΅ΡΠ΅Π½Π΅ ΠΈΠ½ΡΡΠ°Π»ΠΈΡΠ°Π½Π΅ ΡΠ½Π°Π³Π΅,
Π·Π° ΠΊΠΎΡΠ΅ ΡΡ ΡΡΠΎΡΠΊΠΎΠ²ΠΈ ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° ΡΠ΅Π΄Π½Π°ΠΊΠΈ. Π Π°Π·Π²ΠΈΡΠ΅Π½ΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» ΠΎΠΌΠΎΠ³ΡΡΠ°Π²Π°
ΠΎΠΏΠ΅ΡΠ°ΡΠΎΡΠΈΠΌΠ° ΠΏΡΠ΅Π½ΠΎΡΠ½ΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ°, ΠΊΠ°ΠΎ ΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΎΡΠΈΠΌΠ°, Π΄Π° ΠΎΠΏΡΠΈΠΌΠ°Π»Π½ΠΎ ΡΠ°Π³Π»Π΅Π΄Π°ΡΡ ΠΈ ΠΏΠ»Π°Π½ΠΈΡΠ°ΡΡ
ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ΅ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ Π½Π° ΠΏΡΠ΅Π½ΠΎΡΠ½Ρ ΠΌΡΠ΅ΠΆΡ. ΠΠ° ΠΏΡΠΈΠΌΠ΅ΡΡ ΡΠ΅Π°Π»Π½ΠΎΠ³ ΠΈΠ½ΠΆΠ΅ΡΠ΅ΡΡΠΊΠΎΠ³ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°
ΠΏΡΠΈΠΊΡΡΡΠ΅ΡΠ° Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ Π§ΠΈΠ±ΡΠΊ 1 Ρ ΡΡΠΆΠ½ΠΎΠΌ ΠΠ°Π½Π°ΡΡ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠ°Π½Π° ΡΠ΅ ΠΏΡΠ°ΠΊΡΠΈΡΠ½Π°
ΡΠΏΠΎΡΡΠ΅Π±ΡΠΈΠ²ΠΎΡΡ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΎΠ³ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π°.
4. Π Π°Π·Π²ΠΈΡΠ΅Π½ ΡΠ΅ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠΈΡΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» ΡΠ΅ΠΌΠ΅ΡΠ½ΠΎΠ³ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° Π·Π°
Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»Π½ΠΎ ΠΎΠ΄ΡΠ΅ΡΠΈΠ²Π°ΡΠ΅ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ° Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°.
ΠΠ°ΡΠΎΡΠΈΡΠ° ΠΏΠ°ΠΆΡΠ° Ρ ΡΠΎΠΊΡ ΠΈΠ·Π³ΡΠ°Π΄ΡΠ΅ Π²Π΅ΡΡΠΎΠ΅Π»Π΅ΠΊΡΡΠ°Π½Π΅ ΠΏΠΎΡΠ²Π΅ΡΡΡΠ΅ ΡΠ΅ ΠΏΡΠΎΡΠ΅ΠΊΡΠΎΠ²Π°ΡΡ
ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠΊΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ°. Π£ ΠΊΠ°Π±Π»ΠΎΠ²ΡΠΊΠΎΠΌ ΡΠΎΠ²Ρ Π·Π°ΡΠ΅Π΄Π½ΠΎ ΡΠ° Π΅Π½Π΅ΡΠ³Π΅ΡΡΠΊΠΈΠΌ ΠΊΠ°Π±Π»ΠΎΠ²ΠΈΠΌΠ° ΠΏΠΎΠ»Π°ΠΆΡ ΡΠ΅
Π±Π°ΠΊΠ°ΡΠ½Π° ΡΠΆΠ°Π΄ ΠΊΠΎΡΠ° ΠΏΠΎΠ²Π΅Π·ΡΡΡ ΡΠ΅ΠΌΠ΅ΡΠ½Π΅ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ΅ Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°. Π’Π΅ΠΌΠ΅ΡΠ½ΠΈ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°Ρ
Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° ΠΈΠ·Π²ΠΎΠ΄ΠΈ ΡΠ΅ ΠΏΠΎΠ»Π°Π³Π°ΡΠ΅ΠΌ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ° Ρ Π±Π΅ΡΠΎΠ½ΡΠΊΠΈ ΡΠ΅ΠΌΠ΅Ρ, Π»ΠΎΡΠΈΡΠ°Π½ ΠΏΠΎΠ΄ ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΎΠΌ
Π·Π΅ΠΌΡΠ΅, Ρ ΠΎΠ±Π»ΠΈΠΊΡ Π·Π°ΡΠ²ΠΎΡΠ΅Π½ΠΈΡ
ΠΊΠΎΠ½ΡΡΡΠ° (ΠΏΡΡΡΠ΅Π½ΠΎΠ²Π°) ΠΎΠ΄ Π±Π°ΠΊΠ°ΡΠ½ΠΈΡ
ΡΡΠ°ΠΊΠ° ΠΊΠΎΡΠ΅ ΡΠ΅ ΡΠΏΠ°ΡΠ°ΡΡ ΡΠ°
Π°ΡΠΌΠ°ΡΡΡΠΎΠΌ Ρ ΡΠ΅ΠΌΠ΅ΡΡ. ΠΠ»Π΅ΠΊΡΡΠΈΡΠ½Π° ΡΠ²ΠΎΡΡΡΠ²Π° ΠΎΠ²Π°ΠΊΠ²ΠΎΠ³ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ° ΡΡ ΠΎΠ΄ΡΠ΅ΡΠ΅Π½Π° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠΎΠΌ
ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ°, ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠ° Π±Π΅ΡΠΎΠ½Π°, Π°ΡΠΌΠ°ΡΡΡΠ΅, ΡΠ°ΡΡΠ°Π²ΠΎΠΌ ΡΠ»Π° ΠΈ ΡΡΠ°ΡΠ΅ΠΌ ΡΠ»Π° (Π΄ΠΎΠΌΠΈΠ½Π°Π½ΡΠ½ΠΎ
ΡΠ°Π΄ΡΠΆΠ°ΡΠ΅ΠΌ Π²Π»Π°Π³Π΅). ΠΠ±ΠΎΠ³ ΡΠ²ΠΎΡΠ΅ ΡΠ»ΠΎΠΆΠ΅Π½Π΅ ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΡΠ΅, ΡΠ΅ΠΌΠ΅ΡΠ½ΠΈ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°Ρ Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ° ΡΠ΅
Π²Π΅ΠΎΠΌΠ° ΡΠ΅ΡΠΊΠΎ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠΈ. Π Π°Π΄ΠΈ ΠΎΠ΄ΡΠ΅ΡΠΈΠ²Π°ΡΠ° ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ° ΠΊΠΎΡΠ΅ ΡΡ
ΠΎΠ΄ Π·Π½Π°ΡΠ°ΡΠ° Π·Π° ΡΠ΅Π³ΠΎΠ²ΠΎ Π΄ΠΈΠΌΠ΅Π½Π·ΠΈΠΎΠ½ΠΈΡΠ°ΡΠ΅ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ ΡΠ΅ ΡΠΈΠ·ΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π» ΡΠ΅ΠΌΠ΅ΡΠ½ΠΎΠ³ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ°
Π²Π΅ΡΡΠΎΠ°Π³ΡΠ΅Π³Π°ΡΠ°, ΠΊΠΎΡΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ° Π΅ΠΊΠ²ΠΈΠ²Π°Π»Π΅Π½Ρ ΡΠ΅Π°Π»Π½ΠΎΠΌ ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ° ΠΊΠΎΠΌΠ΅ΡΡΠΈΡΠ°Π»Π½ΠΎΠ³
ΠΏΡΠΎΠΈΠ·Π²ΠΎΡΠ°ΡΠ°. Π£Π·Π΅ΠΌΡΠΈΠ²Π°Ρ ΡΠ΅ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ Ρ ΡΠ»ΠΎ ΡΠΈΡΠ΅ ΡΡ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅ Ρ ΠΏΠΎΠ³Π»Π΅Π΄Ρ Π΅Π»Π΅ΠΊΡΡΠΈΡΠ½Π΅
ΠΏΡΠΎΠ²ΠΎΠ΄Π½ΠΎΡΡΠΈ Π²Π°ΡΠΈΡΠ°Π½Π΅. ΠΠ½Π°Π»ΠΈΠ·ΠΈΡΠ°Π½ΠΈ ΡΡ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈ Π΄ΠΎΠ±ΠΈΡΠ΅Π½ΠΈ ΠΌΠ΅ΡΠ΅ΡΠΈΠΌΠ° Π½Π° ΡΠΌΠ°ΡΠ΅Π½ΠΎΠΌ ΠΌΠΎΠ΄Π΅Π»Ρ
ΡΠ·Π΅ΠΌΡΠΈΠ²Π°ΡΠ°.The subject of the doctoral dissertation is development of mathematical models for the
improvement of economic and technical conditions of planning and construction of wind farms. The
main contributions are the following:
1. A mathematical model for optimal wind turbine selection has been developed.
In the dissertation, a mathematical model for optimal wind turbine selection, for known wind
statistics, was developed. The main elements for wind turbine optimization are: the hub height, the
wind turbine diameter, and the wind turbine rated power. The model varies key parameters and
calculates the total wind turbine actualization costs, as well as the annual electricity production. In
the mentioned optimization problem, there are technical limitations regarding the minimum and
maximum values of parameters imposed by the equipment manufacturer. The model is based on a
genetic algorithm which, after a certain number of iterations, leads to optimal results that satisfy
both, the optimisaton function and the given constraints. The developed algorithm and mathematical
model have a general character ie. can be used to optimize WT selection for locations with different
wind parameters. The application of the model ensures optimal use of wind potential at a certain
location, and also provides a higher profit to the owner of the wind farm. The parameters of the
Weibull wind statistics and the wind shear coefficient are used as input data. The practical
applicability of the proposed mathematical model was demonstrated on specific examples of WPPs
at locations with different Weibull parameters.
2. A mathematical model for the calculation of the optimal cross-section of cables of the
wind farm internal cable network has been developed.
As the spatial arrangement of wind turbines in wind farms is characterized by a relatively
large distance from each other, the length of the cable collector network can be several tens or even
hundreds of kilometers, so electricity losses are significant. The use of larger cable cross-sections in
relation to technical requirements is often justified, and can provide a significant increase in
efficiency and better energy performance of the power plant. The model developed in the
dissertation calculates the optimal cable cross-section to which an arbitrary number of wind turbines
is connected, through the optimization of the ratio of investment and operating costs, i.e. costs due
to losses per unit length of cable. Considering that investment costs are segregated at the beginning
i.e. in the phase of wind power plant construction, and the costs of losses are generated during
operation in each year, the costs are actualized i.e. a dynamic economic model is used. The
advantage of the presented model is that the calculations of the optimal topology and cable crosssection are decoupled i.e. they can be solved separately. By applying the developed model in the
planning phase of the wind power plant project, each of the connection feeders to which an arbitrary
number of WTs are connected can be optimized. On specific example of wind power plant in Banat
region is shown that the optimal choice of cable cross-section can significantly reduce production
costs, i.e. increase the total profit during the lifetime of the wind farm.
3. A mathematical model for the selection of the optimal voltage level and the optimal point
of connection of large wind power plants to the transmission network has been developed.
The selection of the optimal wind farm connection point is a demanding task that must
include many parameters. In many cases of connecting a wind farm to the transmission network
there are competing connection points, so the question is how to choose the optimal point at which
wind farm will be connected and deliver the produced energy during operation. Potential connection
points can differ in distance, but also in terms of voltage level, so the choice of connection point is
extended in terms of choosing the voltage level to which the wind farm will be connected.
The developed model calculates the total actualized investment and operating costs of
connection to the transmission network, as a function of the distance from the connection point. In
Abstract
vi
ΠΠΎΠΊΡΠΎΡΡΠΊΠ° Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠ°
ΠΠ½Π° ΠΠ΅ΡΡΠΎΠ²ΠΈΡ
addition to maintenance costs, operating costs also include the costs of undelivered electricity due
to the unavailability of the network. The optimal voltage level and the optimal connection point are
determined by calculating the critical distances of competing connection points for wind power
plant of a certain rated power, for which the connection costs are equal. The developed
mathematical model enables transmission system operators, as well as investors, to optimally
consider and plan the connection of wind power plants to the transmission network. The practical
applicability of the proposed mathematical model is demonstrated on the example of a real
engineering problem of connecting the WPP Δibuk 1, located in South Banar region.
4. A laboratory model of the wind turbine grounding has been developed for the
experimental determination of the grounding system characteristics.
During the construction of the wind power plant, special attention is given to the design of the
earthing system. Copper ropes are laid in the cable trench together with the power cables, which
connect the basic earthing conductors of the wind turbine. The basic earthing of the wind turbine is
performed by laying the earthing in a concrete foundation, located below the ground surface, in
form of closed contours (rings) of copper strips that are connected to the reinforcement in the
foundation. The electrical properties of such an earthing system are determined by the earthing
conductor geometry, concrete characteristics, reinforcement characteristics, soil composition and
soil condition (dominantly moisture content). Due to its complex construction, the grounding of the
wind turbine is very difficult to model mathematically. In order to determine the characteristics of
the earthing system that are important for its sizing, a physical model of the wind turbine earthing
system has been developed, which is equivalent to the real model of the earthing system of a
commercial manufacturer. The grounding conductor is laid in the ground whose characteristics in
terms of electrical conductivity vary. The results obtained by measurements on a scale model of the
earthing system were analyzed
Determinação do ponto ótimo de conexão de parques eólicos offshore a sistemas interligados considerando a maximização da capacidade de geração de energia
Due to growing environmental issues and depletion of conventional energy sources, alternative energy sources, especially renewable ones, are receiving more attention than ever. In this sense, wind energy is one of the most prominent in the context of investments in renewable sources in Brazil and globally. In some cases, regions with high potential for wind generation are far from load centers and are located in a maritime environment; in such situations, it makes sense to install wind farms in an offshore environment. In this scenario, a comprehensive analysis is required to determine the optimal connection point for Offshore Wind Farms (OWF) to the network to ensure maximum wind generation penetration safely and efficiently, taking into account such aspects as load profile, conventional system power generations, impacts caused by intermittent renewable energy sources in grid operation, capacity constrains of the transmission line and wind speed behavior of all the potential regions under study. In this context, this paper aims to propose two methodologies for determining the optimum OWF connection point to interconnected systems while considering how to maximize the capacity for power generation. The first methodology proposes a formulation based on Nonlinear Programming with Linear Power Flow (NLP-DC), where it is possible to observe the wind generation penetration path to the system until the maximum viable value is obtained, considering the minimization of losses in the transmission system and presenting an efficient strategy for the incorporation of active restrictions regarding the βN-1β safety criterion. The second method addresses a computationally efficient optimization problem, which proposes a two-step formulation, both based on Nonlinear Programming (NLP) with a Nonlinear Power Flow approach, which determines the optimum OWF connection point, with their respective maximum wind generation penetration and generating capacity values, considering all contingency scenarios (βN-1β safety criterion), modeled here with the help of the Benders Mathematical Decomposition technique. The proposed methodologies are applied in small, medium and large test systems in order to explore their characteristics and their contributions. Studies in small and medium-sized systems allow for a more tutorial analysis of the problem, while studies of real large systems are able to demonstrate the applicability and effectiveness of the proposed methodology in practical cases.Devido Γ s crescentes questΓ΅es relacionadas ao meio ambiente e ao esgotamento de fontes de energia convencionais, as fontes alternativas de energia, principalmente as renovΓ‘veis, estΓ£o recebendo mais atenção do que nunca. Nesse sentido, a energia eΓ³lica Γ© uma das que apresentam maior destaque na conjuntura de investimentos em fontes renovΓ‘veis no cenΓ‘rio brasileiro e mundial. Em alguns casos, as regiΓ΅es com alto potencial de geração eΓ³lica estΓ£o longe dos centros de carga e localizadas em ambiente marΓtimo; em situaçáes como essa, torna-se interessante a instalação de parques eΓ³licos em ambiente offshore. Nesse cenΓ‘rio, Γ© necessΓ‘ria uma anΓ‘lise abrangente para se determinar o ponto Γ³timo de conexΓ£o de Parques EΓ³licos Offshore (PEO) Γ rede principal que garanta a mΓ‘xima penetração de geração eΓ³lica, de forma segura e eficiente, levando-se em consideração questΓ΅es como o perfil de carga, as geraçáes convencionais de energia existentes no sistema, os impactos causados pela inserção de fontes de energia renovΓ‘veis intermitentes na operação da rede, as restriçáes relacionadas Γ s capacidades das linhas de transmissΓ£o e o comportamento da velocidade do vento de todas as regiΓ΅es potenciais em estudo. Nesse contexto, este trabalho tem por objetivo propor duas metodologias para a determinação do ponto Γ³timo de conexΓ£o de PEO a sistemas interligados considerando a maximização da capacidade de geração de energia. Na primeira metodologia Γ© proposta uma formulação baseada em Programação NΓ£o Linear associada a um Fluxo de PotΓͺncia Linearizado (PNL-CC), em que Γ© possΓvel observar a trajetΓ³ria de penetração de geração eΓ³lica ao sistema atΓ© se obter o valor mΓ‘ximo viΓ‘vel, considerando-se a minimização de perdas no sistema de transmissΓ£o e apresentando uma estratΓ©gia eficiente para a incorporação das restriçáes ativas referentes ao critΓ©rio de seguranΓ§a βN-1β. O segundo mΓ©todo aborda um problema de otimização computacionalmente mais eficiente, em que se propΓ΅e uma formulação dividida em duas etapas, ambas baseadas em Programação NΓ£o Linear e com uma abordagem de Fluxo de PotΓͺncia CA (PNL-CA), que determina o ponto Γ³timo de conexΓ£o do PEO, com seus respectivos valores mΓ‘ximos de penetração de geração eΓ³lica e de capacidade de geração, considerando-se todos os cenΓ‘rios de contingΓͺncia (critΓ©rio de seguranΓ§a βN-1β), modelados atravΓ©s da tΓ©cnica de Decomposição MatemΓ‘tica de Benders. As metodologias propostas sΓ£o aplicadas a sistemas-testes de pequeno, mΓ©dio e grande porte, de forma a explorar suas caracterΓsticas e suas contribuiçáes. Os estudos realizados em sistemas de pequeno e mΓ©dio porte permitem uma anΓ‘lise do problema com cunho mais tutorial, enquanto que o estudo de sistemas reais de grande porte sΓ£o capazes de demonstrar a aplicabilidade e eficΓ‘cia das metodologias propostas em casos prΓ‘ticos.CAPES - Coordenação de AperfeiΓ§oamento de Pessoal de NΓvel Superio