微型電網(Microgrid)作為一種高效利用可再生能源分散式發電(Distributed Generation)的方法，可被用於解決偏遠地區的發電問題或為關鍵負荷提供不間斷供電。為了保證微型電網的可靠性和經濟運行，首要任務是維持系統電壓/頻率穩定和實現分散式發電單元之間功率的精確分配。
微型電網通常運行於中低壓電力系統中，其線路阻抗主要呈現電阻電感性，傳統的P-f/Q-U下垂控制(Droop Control)性能不佳，雖然可通過採用虛擬複阻抗(Virtual Complex Impedance)的方法，使線路阻抗中的電阻分量被虛擬負電阻抵消。但由於存在線路阻抗參數漂移和估計誤差等問題，若虛擬負電阻設計不當會導致系統不穩定。本文根據中低壓微型電網的線路參數特點，採用P-U/Q-f下垂控制，並且在控制迴路中引入由虛擬負電感和虛擬電阻組成的虛擬複阻抗，其中虛擬負電感用於減小系統阻抗中電感分量引起的功率耦合(Power Coupling)，虛擬電阻用於增強系統中的電阻分量，並且調整阻抗匹配度以提高功率分配精度。然而此作法功率分配仍然會受到系統線路阻抗參數的影響。此外，下垂控制結合虛擬阻抗方法易引起電壓偏差問題。因此本文研究了一種新型的基於虛擬複阻抗的穩壓均流控制方法，在不受線路阻抗參數變化影響的情況下實現精確的功率分配，並且提高電壓品質。本研究同時建立基於所提出方法的微型電網系統小信號模型(Small-Signal Model)，用於分析系統的穩定性和動態性能，同時為控制器參數的設計提供理論依據。分析結果表明，所提出方法對線路阻抗參數漂移和估計誤差具有強健性，並且使系統具有較大的穩定裕度和較快的動態響應速度。
再者，本文針對微型電網併聯逆變器的有功功率分配和電壓偏差問題探討，基於全域滑動模式控制(Total Sliding-Mode Control)技術重新設計功率-電壓下垂控制器和內迴路電壓調節器。首先，針對功率-電壓下垂控制回路，定義有功功率與公共耦合點(Point-of-Common-Coupling)電壓幅值之間的下垂控制關係誤差。然後通過採用全域滑動模式控制以獲得新的下垂控制關係，從而同時實現有功功率分配和電壓幅值恢復。由於全域滑動模式控制方案可為系統提供快速的動態性能和強健性，高精度的暫態有功功率分配也可在不受線路阻抗影響的情況下被實現。
更進一步，本文針對微型電網提出基於自我調整模糊類神經網路(Adaptive Fuzzy Neural Network)的分散式二級控制(Distributed Secondary Control)方案，以實現電壓/頻率恢復和最優功率分配。首先，建立微型電網動態系統模型，該模型由逆變器介面分散式電源模型和微型電網電力網絡模型組成，其中分散式電源模型可通過具有最優有功功率分配方案的初級控制器的動態模型來表示。微型電網電力網絡模型由潮流動態模型和負荷模型組成。然後定義基於一致性演算法的誤差函數，並提出基於模型的全域滑動模式控制技術來處理同步和跟蹤問題。為達到無須詳細動態控制設計，本文設計自我調整模糊類神經網路方案來模擬全域滑動模式控制律，以繼承其快速動態響應性能和強健性。同時，所提出的自我調整模糊類神經網路控制方法可以解決全域滑動模式控制對微型電網動態模型精確資訊的依賴。藉由投影演算法(Project Algorithm)和李雅普諾夫穩定性(Lyapunov Stability)定理，推導模糊類神經網路的參數自我調整調節律，以保證基於自我調整模糊類神經網路的分散式二級控制系統的穩定性。本文所提出方法的有效性和優越性將通過數值模擬和實驗進行驗證。

A microgrid (MG) has been introduced as a promising, effective, and efficient way to utilize the distributed generation (DG) of renewable resources. Moreover, it can solve the problem of power supplies in remote areas, where the interconnection with the utility power is not conceivable, or enable uninterrupted power supplies for critical loads. In order to ensure the reliability and economical operation of the MG, the primary tasks are to maintain the voltage/frequency stability and the accurate power sharing among multiple DGs, where appropriate control schemes are critical.
A MG usually operates in medium/low voltage systems, where the line impedance parameters are mainly resistive, and the performance of traditional P–f/Q–U droop control is degenerate. When the virtual complex impedance method is adopted, the resistance component of line impedance can be counteracted by a virtual negative resistance. Unfortunately, the improper design of the virtual negative resistance will result in an unstable system due to the problem of line impedance parameter drift and estimation error. According to the line parameters characteristics of the islanded MG with medium/low voltage, the P–U/Q–f droop control is adopted in this dissertation, where the virtual complex impedance composed of a virtual negative inductance and a virtual resistance is introduced in the control loop. The virtual negative inductance is used to reduce the power coupling caused by the inductive component of the system impedance. The virtual resistance is implemented to enhance the resistive component and adjust the impedance matching degree for raising the accuracy of power sharing. However, the power sharing is still affected by the system hardware parameters; meanwhile, the voltage deviation caused by the droop control and the virtual impedance exists. In this dissertation, a novel voltage stabilization and power sharing control method based on the virtual complex impedance is investigated to achieve accurate power sharing without the impact of hardware parameters variations and to improve the voltage quality. Moreover, the small-signal model of the inverter-based islanded MG with the proposed controller is established, which can be utilized to analyze the stability and dynamic performance of the system. Meanwhile, the control parameters can be sequentially determined. Analysis shows that the strategy is robust against the line-impedance parameter drift and the estimation error and has a large stability margin and fast dynamic-response speed.
Focused on the problems of active power sharing and voltage deviation of parallel-connected inverters in an islanded MG, the power-voltage droop controller and the inner voltage regulator are redesigned based on a total sliding-mode control (TSMC) technique in this dissertation. As for the power-voltage droop control loop, a droop control relation error between the active power and the point-of-common-coupling (PCC) voltage amplitude is defined. Then, the TSMC scheme is adopted to reach the new droop control relation, where the active power sharing and voltage amplitude recovery can be achieved simultaneously. Owing to the faster dynamic response and strong robustness provided by the TSMC framework, high-precision active power sharing during transient state also can be ensured without the influence of line impedances.
In this dissertation, an adaptive fuzzy-neural-network (AFNN) control scheme is further proposed for an islanded MG as a distributed secondary controller (DSC) to achieve the aims of voltage and frequency restoration and the optimal power sharing. Firstly, the dynamic model of an islanded MG is built, which consists of an inverter-interfaced DG model and a MG architecture model. The DG model can be represented by considering the dynamics of a primary controller with an optimal active power sharing scheme. The MG architecture model is composed of power flow dynamics and loads. Then, a consensus-algorithm-based error function is defined, and a model-dependent TSMC technique is presented for dealing with synchronization and tracking problems. Moreover, an AFNN scheme is designed to mimic the TSMC law to inherit its fast dynamic response with robust properties. Meanwhile, the requirement of precise information of the MG dynamic model in the TSMC law can be relaxed by the AFNN scheme. Adaptive tuning algorithms for network parameters of the AFNN-based DSC (AFNN-DSC) strategy are derived by using the projection algorithm and the Lyapunov stability theorem, which can guarantee the stability of the AFNN-DSC-controlled system. Numerical simulations and experimental results are provided to verify the effectiveness and the superiority of all the proposed methods in this dissertation.

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