Voltage control design of wind energy harvesting networks
- Autores: Elena Saiz Marín
- Directores de la Tesis: Enrique Lobato Miguélez (dir. tes.), Ignacio Egido Cortés (codir. tes.)
- Lectura: En la Universidad Pontificia Comillas ( España ) en 2015
- Idioma: español
- Tribunal Calificador de la Tesis: José Luis Martínez Ramos (presid.), Pablo Frías Marín (secret.), Luis Fernando Ochoa Pizzali (voc.), José Antonio Aguado Sánchez (voc.), Luis Rouco Rodríguez (voc.)
- Materias:
- Enlaces
- Tesis en acceso abierto en: TESEO
- Resumen
Specific networks developed solely to harvest wind energy (HNet) are becoming a common scheme. Moreover, it is foreseen that in the near future, they will be the solution adopted for large integration of wind, commanding greater transmission system impact potential. However, despite the huge literature available related to wind farms and their integration, few works focus on these networks, a gap covered in depth by this thesis. These potentials are highly dependent on the HNet characteristics; hence its classification is essential. This is done by analyzing the influence of OLTC transformers based on three relevant indices: PQ chart, power losses, and voltage margins deriving three different HNets types (A, B and C). For each one, the most suitable control strategy is proposed considering simple control schemes which can nowadays be implemented without additional investments. Consequently their steady-state performance and temporal evolution analysis are required. In that sense a wide variety of techniques are used throughout the thesis: data-mining techniques (regressions, clustering, decision trees ¿), metaheuristic algorithms (genetic algorithms and multiple particle swarm optimization), quadratic programming or multi-period OPF.
Specifically, for type A, power loss minimization strategy based on control rules is suggested allowing the understanding of power flows performance within the grid and identifying those wind farms with negligible impact. For that purpose a novel variable, active power losses from wind farm i to the transmission network bus (Plossi), was defined. In addition, to avoid online computations, the total HNet active power has been considered as an explanatory variable resembling the power factor concept (with respect a global magnitude instead of the individual wind farm active power). In that manner, simple regression rules are used to estimate wind farm reactive power, and a classification tree for each transformer is used to estimate their taps.
For type B, a minimum HNet impact on the transmission network strategy is suggested analyzing different possible control schemes: reference control, power factor control, local voltage control (representative of the current regulation direction) and remote voltage control. For each control scheme static fit-and-forget settings are obtained thanks to the AC-multi-period OPF and therefore autonomous control schemes are obtained. Comparing these control schemes it has been observed that the best option is a voltage control where wind farms control the voltage at a remote bus. Otherwise, of the localized control schemes that do not require telemetry, power factor control scheme has a better performance contrary to the widespread idea of local voltage control adequacy as many regulation proposals suggest.
Finally for type C, a pro-active voltage control (i.e., the whole HNet resembles a conventional power plant) is suggested demanding adaptive static parameters contrarily to what was proposed for the previous HNet types. Hence, a central controller distributes set-point depending on the operational and external conditions. This central controller has been developed following the guidelines of well-known TNet hierarchical voltage control and more specifically in its secondary loop performing and optimization by means of quadratic programming every 10 seconds. Nonetheless, several modifications have been made in accordance with HNet characteristics and the nature of distributed generation such as its variability as are explained throughout the thesis.
In addition, any control scheme design should also consider the dynamic coordination of wind farms and cascade OLTC transformers to ensure that such set points redispatche can be harmoniously achieved. In that sense this thesis proposes tuning offline relevant dynamic settings (i.e., settings that affect the control scheme temporal time evolution) to be applied to Type B and C HNets. These settings are wind farms¿ controller time constants and for OLTC transformers the time delay and dead band. This last setting is not commonly used with coordination purpose although there is no barrier that impedes its use, as this thesis proposes. For that purpose two well-known metaheuristics algorithms (Genetic algorithm and MOPSO) have been used. On one hand the former provides the settings tendency whereas the latter one provides the whole Pareto frontier; allowing the settings categorization depending on the agents preferences (tap changes minimization, voltage breaches minimization and voltage deviation minimization). Concerning type B, this analysis reinforces the idea of inadequacy of local voltage control scheme owing to the necessity of slow controller action for avoiding oscillations. Finally, a demanding voltage control such as the remote one significantly increases the number of tap changes. Concerning type C, the same method has been employed focusing this time only on the MOPSO algorithm. The results obtained have been expanded clustering the Pareto front obtaining different dynamic settings patterns.
