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Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids' EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.

List of Figures vii List of Tables ix List of Acronyms xi Nederlandse samenvatting xiii English summary xvii the two afore-mentioned distinct contributions of the proposed model-based coordinating approach namely "looking-ahead" and "communication", since the decentralized deadband approach lacks both anticipation and coordination, and the decentralized MPC approach ignores the communications with neighbors. 1 Ultra high voltage transmission voltage levels have been experimentally used at 1200 kV in the former Soviet Union and today in Kasachastan, and at 1100 kV in Japan. 1.1.3 Voltage stability Voltage stability, the main focus of this thesis, refers to the ability of a power system to maintain all its bus voltage magnitudes within a prescribed interval around the nominal bus voltages, even following a disturbance. In other words, voltage instability implies that the post-disturbance power system is unable to reach a new set of permissible steady-state voltages at some buses. A more formal definition of voltage instability is given in [6]: (2q − 1) 2 − 4(p 2 + q 2) ≥ 0 (1.7) or 1 − 4q − 4p 2 ≥ 0 This inequality represents the possible combinations of active and reactive power that the combined generation-transmission system of Fig. 1.2 can supply to the

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The present study addresses the calibration of four types of partial discharge (PD) emulators used in the development of a PD Wireless Sensor Network (WSN). Three PD emulators have been constructed: a floating-electrode emulator, and two internal PD emulators. Both DC and AC high-voltage power supplies are used to initiate PD, which is measured using concurrent free-space radiometry (FSR) and a galvanic contact method based on the IEC 60270 standard. The emulators have been measured and simulated, and a good agreement has been found for the radiated fields. A new method of estimating the absolute PD activity level from radiometric measurements is proposed

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In this paper, an adaptive type-2 fuzzy controller is proposed to control the load frequency of a two-area power system based on descending gradient training and error back-propagation. The dynamics of the system are completely uncertain. The multilayer perceptron (MLP) artificial neural network structure is used to extract Jacobian and estimate the system model, and then, the estimated model is applied to the controller, online. A proportional–derivative (PD) controller is added to the type-2 fuzzy controller, which increases the stability and robustness of the system against disturbances. The adaptation, being real-time and independency of the system parameters are new features of the proposed controller. Carrying out simulations on New England 39-bus power system, the performance of the proposed controller is compared with the conventional PI, PID and internal model control based on PID (IMC-PID) controllers. Simulation results indicate that our proposed controller method outperforms the conventional controllers in terms of transient response and stability.

The objective of this study is minimizing the frequency deviation due to the load variations and fluctuations of renewable energy resources. In this paper, a new type-2 fuzzy control (T2FLC) approach is presented for load frequency control (LFC) in power systems with multi-areas, demand response (DR), battery energy storage system (BESS), and wind farms. BESS is used to reduce the frequency deviations caused by wind energy, and DR is utilized to increase network stability due to fast load changes. The suggested T2FLC is online tuned based on the extended Kalman filter to improve the LFC accuracy in coordination of DR, BESS, and wind farms. The system dynamics are unknown, and the system Jacobian is extracted by online modeling with a simple multilayer perceptron neural network (MLP-NN). The designed LFC is evaluated through simulating on 10-machine New England 39-bus test system (NETS-39b) in four scenarios. Simulation results verifies the desired performance, indicating its superiority compared to a classical PI controllers, and type-1 fuzzy logic controllers (FLCs). The mean of improvement percentage is about 20%. INDEX TERMSRenewable energy; LFC, Type-2 adaptive neuro-fuzzy, Extended Kalman filter, Demand response, BESS.