Flexibility and Balancing in Active Distribution Networks

Environmental concerns, together with the fast-pacing changes in the renewable energy technologies, have led to significant growth of renewable energy sources (RESs) in energy systems. Among different sources of renewable energy, wind and solar energy are the most progressed sources so far. However, high penetration of RESs in the power network can cause serious problems in the power system, as these energy sources are hardly dispatchable. On the other hand, appearance of new electric loads in the power system, especially electric vehicles (EVs), increases the electric demand of the network, and causes higher fluctuations in the demand.
In countries such as Denmark, different incentives have been proposed and applied to encourage customers for investing on solar photovoltaic (PV) panels. These policies have increased the number of household PV panels. However, presence of such small energy sources in low voltage (LV) network affects the traditional behavior of these systems, as it leads to reverse power flow, from the customers to the upper network. Such reverse power flow brings new challenges to the system, while it also brings new potentials for transmission system operator (TSO) and distribution system operator (DSO) to use the reverse power flow for balancing purposes.
The first objective of this research is to quantify and analyze the impact of PV panels and EVs on LV network, and to determine the maximum capacity of LV network for hosting PV panels and EVs. Details of the studies are presented in chapter 2. In the first step, a proper modeling approach has been defined for loads, EVs, and PV panels. Details of the load modeling are presented in chapter 2. For EVs, the modeling is applied considering lithium-ion (Li-ion) batteries, considering the growing interest of industries in these batteries. A detailed modeling of Li-ion battery is presented in chapter 2 as well. PV panels are modelled as a function of solar irradiation and ambient temperature. In the next step, the impact of PV panels and electric vehicles on LV network was quantified separately. For PV panels, different placement of panels in the LV network has been analyzed and studied to find out the network operating limits in dealing with these small energy sources. Besides, an optimization study has been applied to the network to determine the maximum ancillary service which can be provided by PV panels for the power system, considering the operating limits of the power system and transformer capacity. On the other hand, different charging strategies have been proposed for EVs to determine maximum penetration of EVs in the LV network. These strategies are based on voltage measurement of LV grid nodes, and location and placement of EVs in the LV network. Different types of EVs, with different distance profiles (DP) have been considered in the studies. In the third step, the potential of PV panels and EVs for providing grid support and ancillary service for the power system has been analyzed. The main objective of this analysis was to quantify the capacity of LV network for providing ancillary service for power system. To do so, an optimization problem has been proposed and applied to the network.
The second objective of this research is to evaluate the impact of active LV network on medium voltage (MV) network. To do so, an aggregated model of LV network in presence of PV panels and EVs has been proposed and simulated. The proposed aggregation technique is presented in chapter 3. Also, the impact of the LV network on the MV network has been quantified, considering residential, industrial, and commercial loads of the MV network. Chapter 4 presents the details of the analysis, as well as the details of the MV network. To generalize the analysis, a standard MV network has been used for the studies. The MV network is also an active network, i.e. it involves MV wind turbines and decentralized combined heat and power (DCHP). DCHP units play an important role in Danish power system, and they contribute to electricity production as well. Modeling of wind turbines is done considering real data of a Vestas wind turbine. For wind speed, a modified wind speed model has been used for wind turbines, considering the available wind measurement. Also, a detailed model of DCHP units has been used in this thesis. Details of wind turbine model, as well as details of DCHP are presented in the thesis.
The third objective of the research is to include the LV and MV networks in frequency response of the power system. Considering the increasing penetration of RESs in the power system, and the reducing role of traditional generation units, the power system frequency control needs to be modified as well. By other words, in the future grid scenario, active LV and MV networks are required to play a role in controlling the system frequency. Therefore, the traditional load frequency control (LFC) needs to be modified by including LV and MV networks. To do so, a modified LFC has been proposed in chapter 5 of this thesis. The main idea in this work was to use the fast response of DCHP units for frequency response of the system.
In conclusion, the main contribution of this thesis is to propose an intelligent strategy for managing high penetration of PV panels and EVs in the LV network, without reinforcing the network. Such solution helps DSOs to avoid or delay huge investments due to increase in demand, while it brings economic incentives for customers to consider RESs as a proper energy source. The other main contribution of this thesis is to propose a new aggregation technique for residential distribution networks, considering small energy sources and electric vehicles. Besides, this thesis proposes a modified LFC based on the DCHP units of MV network in order to improve system frequency response. The proposed modified LFC enables the LV and MV network to participate in system frequency response, and reduces the system dependency on central power plants for frequency regulation.