Ehab F. El-Saadany

Adaptive Decentralized Droop Controller to Preserve Power Sharing Stability of Paralleled Inverters in Distributed Generation Microgrids

This paper addresses the low-frequency relative stability problem in paralleled inverter-based distributed generation (DG) units in microgrids. In the sense of the small-signal dynamics of a microgrid, it can be shown that as the demanded power of each inverter changes, the low-frequency modes of the power sharing dynamics drift to new locations and the relative stability is remarkably affected, and eventually, instability can be yielded. To preserve the power sharing stability, an adaptive decentralized droop controller of paralleled inverter-based DG units is presented in this paper. The proposed power sharing strategy is based on the static droop characteristics combined with an adaptive transient droop function. Unlike conventional droop controllers, which yield 1-DOF tunable controller, the proposed droop controller yields 2-DOF tunable controller. Subsequently, the dynamic performance of the power sharing mechanism can be adjusted, without affecting the static droop gain, to damp the oscillatory modes of the power sharing controller. To account for the power modes immigration at different loading conditions, the transient droop gains are adaptively scheduled via small-signal analysis of the power sharing mechanism along the loading trajectory of each DG unit to yield the desired transient and steady-state response. The gain adaptation scheme utilizes the filtered active and reactive powers as indices; therefore, a stable and smooth power injection performance can be obtained at different loading conditions. The adaptive nature of the proposed controller ensures active damping of power oscillations at different operating conditions, and yields a stable and robust performance of the paralleled inverter system.

Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy

Environmental concerns and fuel cost uncertainties associated with the use of conventional energy sources have resulted in rapid growth in the amount of wind energy connected to distribution grids. However, based on Ontarios standard offer program (SOP), the utility has the right to curtail (spill) wind energy in order to avoid any violation of the system constraints. This means that any increase in wind energy production over a specific limit might be met with an increase in the wind energy curtailed. In spite of their cost, energy storage systems (ESSs) are considered to be a viable solution to this problem. This paper proposes a methodology for allocating an ESS in a distribution system with a high penetration of wind energy. The ultimate goal is to maximize the benefits for both the DG owner and the utility by sizing the ESS to accommodate all amounts of spilled wind energy and by then allocating it within the system in order to minimize the annual cost of the electricity. In addition, a cost/benefit analysis has been conducted in order to verify the feasibility of installing an ESS from the perspective of both the utility and the DG owner.

A wideband vibration-based energy harvester

We present a new architecture for wideband vibration-based micro-power generators (MPGs). It replaces a linear oscillator with a piecewise-linear oscillator as the energy harvesting element of the MPG. A prototype of an electromagnetic MPG designed accordingly is analyzed analytically, numerically and experimentally. We find that the new architecture increases the bandwidth of the MPG during a frequency up-sweep, while maintaining the same bandwidth in a down-sweep. Closed-form expressions for the response of the new MPG as well as the up-sweep bandwidth are presented and validated experimentally. Simulations show that under random-frequency excitations, the new MPG collects more energy than the traditional MPG.

An Improved Deadbeat Current Control Scheme With a Novel Adaptive Self-Tuning Load Model for a Three-Phase PWM Voltage-Source Inverter

In this paper, an improved deadbeat current control scheme with a novel adaptive self-tuning load model for a three-phase pulsewidth-modulated (PWM) voltage-source inverter is proposed. First, to achieve high-bandwidth current control characteristics, an improved deadbeat current controller with delay compensation is adopted. The compensation method forces the delay elements, which are caused by voltage calculation, PWM, and synchronous frame rotation, to be equivalently placed outside the closed-loop control system. Hence, their effect on the closed-loop stability is eliminated, and the current controller can be designed with a higher bandwidth. Second, to relax the parameter sensitivity issue of the deadbeat controller and to realize a control scheme with reduced sensors, a novel adaptive self-tuning load model is emerged in the control structure. The adaptive model is designed with low computational demand to estimate in real time the load parameters (R,L) and the back-electromotive-force voltage simultaneously. A unified solution to the present nonlinear estimation problem is presented by adopting a parallel observer structure. Furthermore, the adaptive model has the necessary phase advance of the estimated quantities, which compensates for the total systems delay. Comparative evaluation results are presented to demonstrate the validity and effectiveness of the proposed control scheme

Power quality disturbance classification using the inductive inference approach

This paper presents a novel approach for the classification of power quality disturbances. The approach is based on inductive learning by using decision trees. The wavelet transform is utilized to produce representative feature vectors that can accurately capture the unique and salient characteristics of each disturbance. In the training phase, a decision tree is developed for the power quality disturbances. The decision tree is obtained based on the features produced by the wavelet analysis through inductive inference. During testing, the signal is recognized using the rules extracted from the decision tree. The classification accuracy of the decision tree is not only comparable with the classification accuracy of artificial Neural networks, but also accounts for the explanation of the disturbance classification via the produced if... then rules.

Impact of DG interface control on islanding detection and nondetection zones

Islanding detection of Distributed Generation (DG) is considered as one of the most important aspects when interconnecting DGs to the distribution system. With the increasing penetration and reliance of the distribution systems on DGs, new interface control strategies are being proposed. Aside from its main task of supplying active power, the DG could provide voltage support, improve the power factor, or mitigate other power quality problems. This paper examines the impact of the interface control strategy of inverter based DGs on islanding detection. The Nondetective Zone (NDZ) for over/under voltage and over/under frequency is derived analytically for each interface control and validated by simulation.

A novel control algorithm for the DG interface to mitigate power quality problems

Distributed Generation (DG) exists in distribution systems and is installed by either the utility or the customers. This paper proposes a novel utilization of the existing DG nonlinear interface not only to control the active power flow, but also to mitigate unbalance and harmonics, and to manage the reactive power of the system. The proposed Flexible Distributed Generation (FDG) is similar in functionality to FACTS, but works at the distribution level. Moreover, a novel ADAptive LINEar neuron (ADALINE) structure is presented. The new structure is applied to multi output (MO) systems for parameter tracking/estimation, and is called MO-ADALINE. It is dedicated to symmetrical components estimation. The control loop combines a Fuzzy Logic Controller (FLC) for voltage regulation, and a processing unit-based ADALINE to deal with unbalance, harmonics and reactive power compensation. One advantage of the proposed control system is its insensitivity to parameter variation, a necessity for distribution system applications. Simulations of the suggested FDG based control algorithm are conducted to evaluate the performance of the novel system.

Implementing Virtual Inertia in DFIG-Based Wind Power Generation

Although wind power as a renewable energy is assumed to be an advantageous source of energy, its intermittent nature causes difficulties especially in the islanding mode of operation. Conventional synchronous generators can help to compensate for wind fluctuations, but the slow behavior of such systems may result in stability concerns. Here, the virtual inertia method, which imitates the kinetic inertia of synchronous generator, is used to improve the system dynamic behavior. Since the proposed method focuses on short-term oscillations and incorporates no long-term power regulation, it needs no mass storage device. Thus, the method is economical. To prevent any additional cost, the rotating mass connected to the DFIG shaft or a super-capacitor connected to the DC-link of a back-to-back inverter of a wind power generator could be used. The concept and the proposed control methods are discussed in detail. Eigen-value analysis is used to study how the proposed method improves system stability. The advantages and disadvantages of using DFIG rotating mass or super-capacitor as the virtual inertia source are compared. The proposed approach also shows that while virtual inertia is not incorporated directly in long-term frequency and power regulation, it may enhance the system steady-state behavior indirectly. A time domain simulation is used to verify the results of the analytical studies.

Reliability Evaluation for Distribution System With Renewable Distributed Generation During Islanded Mode of Operation

Keen interest in the development and utilization of wind-based distributed generations (DGs) has been currently observed worldwide for several reasons. Among those is controlling the emission of environmentally harmful substances, limiting the growth in energy costs associated with the use of conventional energy sources and encouraging the independent power producers for participation in the electricity market system. One of the most important issues is to quantitatively assess the impact of such type of DGs on the distribution system reliability. This paper presents a probabilistic technique to evaluate the distribution system reliability utilizing segmentation concept and a novel constrained Grey predictor technique for wind speed profile estimation.

Grey predictor for wind energy conversion systems output power prediction

Wind energy is considered one of the most rapidly growing sources of electricity generation all over the world. This letter presents a novel technique for wind speed forecasting and wind power prediction based on using the Grey predictor model GM(1,1). The effectiveness of the proposed predictor is revealed using simulation results