This PhD thesis presents an innovative control strategy for the integration of renewable energy sources in distribution and transmission networks. This work is based on a multilevel control approach that takes into account the current technology, state of the art and legislative limits and considering the most promising trends. The outer loop control is based on a real time strategy for optimal power flow in presence of storage devices and wind turbine driven by Doubly Fed Induction Generators. These elements work in cooperation defining a dy- namic bus where the generated power is subject to temporal constraints, which establish a coupling between traditional power flow problems related to consecutive time periods; further the uncertainty in wind power genera- tion forecasts requires a continuous update of the planned power profiles, in order to guarantee a dynamic equilibrium among demand and supply. Model predictive control is used for this purpose, considering the dynamic equations of the storage and the wind turbine rotor as prediction models. A proper target function is introduced in order to find a trade-off between the need of minimizing generation costs and the excursions of the storage state of charge and the wind turbine angular speed from reference states. In the case study under consideration storage, wind turbines and a traditional synchronous generator are operated by the Transmission System Operator in the form of a Virtual Power Plant to cover network losses. The inner loop control is based on a real time control strategy for dy- namically balancing electric demand and supply at local level, in a scenario characterized by a HV/MV substation with the presence of renewable energy sources in the form of photovoltaic generators and an electric energy storage system. The substation is connected to the grid and is powered by an equiv- alent traditional power plant playing the role of the bulk power system. A model predictive control approach is proposed to decide in time the storage setpoint, based on the storage state of charge, the forecast demand and the forecast output of renewable plants. The two loops allow to obtain an overall control system able to minimize the generation of traditional power systems during the day-ahead market in an hand, and to respect the local load forecasts in other hand thanks the introduction of non-dispatchable renewable energy system and the energy storage ones as well as an innovative predictive control strategy. Theoretical results are reported on the stability of the proposed control scheme, which is then validated also on a simulation basis. Simulations show the effectiveness of the proposed approach in managing fluctuations of network demand and renewable generation under realistic conditions.
This PhD thesis presents an innovative control strategy for the integration of renewable energy sources in distribution and transmission networks. This work is based on a multilevel control approach that takes into account the current technology, state of the art and legislative limits and considering the most promising trends. The outer loop control is based on a real time strategy for optimal power flow in presence of storage devices and wind turbine driven by Doubly Fed Induction Generators. These elements work in cooperation defining a dy- namic bus where the generated power is subject to temporal constraints, which establish a coupling between traditional power flow problems related to consecutive time periods; further the uncertainty in wind power genera- tion forecasts requires a continuous update of the planned power profiles, in order to guarantee a dynamic equilibrium among demand and supply. Model predictive control is used for this purpose, considering the dynamic equations of the storage and the wind turbine rotor as prediction models. A proper target function is introduced in order to find a trade-off between the need of minimizing generation costs and the excursions of the storage state of charge and the wind turbine angular speed from reference states. In the case study under consideration storage, wind turbines and a traditional synchronous generator are operated by the Transmission System Operator in the form of a Virtual Power Plant to cover network losses. The inner loop control is based on a real time control strategy for dy- namically balancing electric demand and supply at local level, in a scenario characterized by a HV/MV substation with the presence of renewable energy sources in the form of photovoltaic generators and an electric energy storage system. The substation is connected to the grid and is powered by an equiv- alent traditional power plant playing the role of the bulk power system. A model predictive control approach is proposed to decide in time the storage setpoint, based on the storage state of charge, the forecast demand and the forecast output of renewable plants. The two loops allow to obtain an overall control system able to minimize the generation of traditional power systems during the day-ahead market in an hand, and to respect the local load forecasts in other hand thanks the introduction of non-dispatchable renewable energy system and the energy storage ones as well as an innovative predictive control strategy. Theoretical results are reported on the stability of the proposed control scheme, which is then validated also on a simulation basis. Simulations show the effectiveness of the proposed approach in managing fluctuations of network demand and renewable generation under realistic conditions.
Control strategies for the integration of renewable energy sources in distribution and transmission networks / Lanna, Andrea. - STAMPA. - (2016).
Control strategies for the integration of renewable energy sources in distribution and transmission networks
LANNA, ANDREA
01/01/2016
Abstract
This PhD thesis presents an innovative control strategy for the integration of renewable energy sources in distribution and transmission networks. This work is based on a multilevel control approach that takes into account the current technology, state of the art and legislative limits and considering the most promising trends. The outer loop control is based on a real time strategy for optimal power flow in presence of storage devices and wind turbine driven by Doubly Fed Induction Generators. These elements work in cooperation defining a dy- namic bus where the generated power is subject to temporal constraints, which establish a coupling between traditional power flow problems related to consecutive time periods; further the uncertainty in wind power genera- tion forecasts requires a continuous update of the planned power profiles, in order to guarantee a dynamic equilibrium among demand and supply. Model predictive control is used for this purpose, considering the dynamic equations of the storage and the wind turbine rotor as prediction models. A proper target function is introduced in order to find a trade-off between the need of minimizing generation costs and the excursions of the storage state of charge and the wind turbine angular speed from reference states. In the case study under consideration storage, wind turbines and a traditional synchronous generator are operated by the Transmission System Operator in the form of a Virtual Power Plant to cover network losses. The inner loop control is based on a real time control strategy for dy- namically balancing electric demand and supply at local level, in a scenario characterized by a HV/MV substation with the presence of renewable energy sources in the form of photovoltaic generators and an electric energy storage system. The substation is connected to the grid and is powered by an equiv- alent traditional power plant playing the role of the bulk power system. A model predictive control approach is proposed to decide in time the storage setpoint, based on the storage state of charge, the forecast demand and the forecast output of renewable plants. The two loops allow to obtain an overall control system able to minimize the generation of traditional power systems during the day-ahead market in an hand, and to respect the local load forecasts in other hand thanks the introduction of non-dispatchable renewable energy system and the energy storage ones as well as an innovative predictive control strategy. Theoretical results are reported on the stability of the proposed control scheme, which is then validated also on a simulation basis. Simulations show the effectiveness of the proposed approach in managing fluctuations of network demand and renewable generation under realistic conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
