Advanced Control and Optimization of Inverter-Based Microgrids


Student thesis: Doctoral Thesis

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Award date21 Jun 2023


With the improvement of environmental awareness and the development of science and technology, the renewable energy generation and electric vehicle (EV) industry are developing rapidly to reduce the consumption of fossil energy. However, uncertain renewable energy generation and the increasing electricity demand pose a threat to the stable operation of the grid. Therefore, the concept of microgrids comes into being, which can reduce the loss caused by long-distance power transportation, and can also avoid large-scale electricity blackouts due to local failures. In the future microgrids, the regulation of power supply output and the stable control of frequency and voltage are mainly undertaken by the inverters. Therefore, this thesis proposes advanced control and optimization of inverter-based microgrids.

Firstly, the development of inverter-based microgrids is reviewed. The thesis analyses the state of art of microgrid development, gridable inverter application, frequency and voltage control and restoration, and economic scheduling.

Secondly, a novel distributed event-triggered control for fast frequency restoration is proposed based on the real-time virtual synchronous generator (VSG) control at the bottom level. The power reference values generated by the proposed control can accelerate the frequency restoration with accurate power sharing. Meanwhile, by designing event-triggering conditions, parallel inverter controllers only need to communicate with neighbours at the event-triggered moments.

Thirdly, the presentation of primary control, which is composed of the VSG-based frequency control and the voltage droop control with a low-pass filter (LPF), is unified as a first-order ordinary differential equation system. Based on the unified primary control model, the low-sampling model predictive control (MPC) is proposed as secondary frequency and voltage control. The MPC-based secondary control and the primary control have different sampling rates. Due to the discrete and difference characteristics of MPC, the stability and dynamic performance of the proposed dual-rate sampling control system are investigated for the first time.

Fourthly, EV-based virtual energy routers (EV-based VERs) are designed to participate in the frequency and voltage regulation of inverter-based microgrids. EV-based VERs decouple electricity supply functions from specific renewable energy generation to flexibly mobile EVs. Due to their flexibility and movability, they can carry the energy to move and replace the physical energy router. The available capacity of EV clusters is variable. Therefore, adaptive primary control and distributed predictive control are proposed to achieve frequency and voltage regulation in microgrids with virtual EV routers. Considering the microgrid network, the proposed distributed MPC method can overcome the disproportionate impedances of interconnecting lines among buses. Then the frequency and voltage of islanded microgrid can be restored to rated values with accurate power sharing.

Finally, considering EV-based VERs, the upper-level day-ahead and hour-ahead economic scheduling are designed for radial microgrids. The day-ahead scheduling aims to maximize the social utility considering the charging and discharging of EV-based VERs. Centralized mixed-integer nonlinear programming (MINLP) is adopted to solve the optimization problem. With the charging and discharging operation determined by the day-ahead scheduling, the hour-ahead scheduling maximizes the social utility and minimizes the power loss for the next hour. The power flow constraints are added to the optimization problem. Distributed predictor corrector proximal multiplier (PCPM) method is adopted to solve the hour-ahead optimization problem.

Moreover, the interaction among the proposed economic optimization, secondary control, and real-time primary control is analysed. With the proposed hierarchical control, the inverter-based microgrids present stable, reliable, economical, and environment-friend characteristics.