Effects of Distributed Generation on the Bidirectional Operation of Cascaded Step Voltage Regulators: Case Study of a Real 34.5 kV Distribution Feeder

This work investigates the impact of feeder bidirectional active power flow on the operation of two cascaded step voltage regulators (SVRs) located at a 34.5 kV rural distribution feeder. It shows that, when active power flow reversal is possible both by network reconfiguration and by high penetration levels of distributed generation (DG), typical SVR control mode settings are unable to prevent the occurrence of runaway condition, a phenomenon characterized by loss of SVR voltage control capabilities. Such developments are the basis for a DG pre-dispatch control strategy that aims to avoid the adverse effects of the described power flow reversal scenarios, as well as to ensure reliable operation of the utility distribution network.Comment: 8 pages, 11 figures, submitted to XXV SNPTEE 201

A Low-Computational High-Performance Model Predictive Control of Single Phase Battery Assisted Quasi Z-Source PV Inverters

Impedance network inverters are a good alternative for voltage-source and current-source inverters. The shoot-through solution and the boosting capability of such converters make them an excellent solution for photovoltaic (PV) application. Furthermore, energy storage integration in these inverters does not require any additional components in the converter; indeed, a battery can be directly connected in parallel with one of the capacitors of the Z- or quasi Z-network. However, for an optimal control of these converters, complex control and modulation strategies are required. Model Predictive Control (MPC) provides high control performance at the expense of the computational effort. In this paper, a low computational control method where both MPC and proportional resonant (PR) controller are combined, is proposed. This makes the proposed controller perform two iterations only instead of iterating for all the available switching states. As shown in the obtained results, the proposed controller conserves the high performance of the conventional MPC with 50% less computational burden

Synchronous Active Proportional Resonant-Based Control Technique for High Penetration of Distributed Generation Units into Power Grids

This paper deals with a synchronous active proportional resonant-based (SAPR) control technique for interfaced converters, enhancing the stable operation of the power grid under high penetration of distributed generation sources. By considering the grid specifications and load currents, both d and q axis of converter currents are obtained in terms of active and reactive power and also angular speed using small-signal linearization method. Then, swing equation is analyzed in detail to achieve the reference current components in the current control loop of the interfaced converter. By using the obtained swing equation and a non-ideal proportional resonant (PR) controller, a new control technique is proposed, which introduces the behavior of synchronous power generators based on power electronic converters in distributed generation (DG) technology. The effectiveness of the proposed control technique is verified through stringent simulation studies in MATLAB/SIMULINK. Index Terms—Distributed generation (DG), synchronous active PR-based (SAPR), synchronous power generator.Smart and Sustainable Insular Electricity Grids Under Large-Scale Renewable Integratio

Double synchronous controller for integration of large-scale renewable energy sources into a low-inertia power grid

Renewable energy sources are normally connected to the power grid via power electronic converters. High penetration of these energy sources into the power grid leads to high instability in voltage and frequency. This issue is caused by neglecting the inherent characteristics of synchronous generators i.e., inertia, damping and proper active and reactive power sharing in the structure of the used control technique in the control loop of the interfaced converter between power grid and renewable energy sources. This paper presents a powerbased control technique based on a double synchronous controller (DSC) for interfaced converter between the renewable energy sources and the power grid, including an active-reactive power based dynamic equation. Through the proposed DSC, a decoupled control method is performed in which both active and reactive power can be injected from renewable energy sources into the power grid by the interfaced power converter with the inherent features of synchronous power generators. By using the proposed control technique, a stable operation of the power grid can be guaranteed during the integration of large-scale renewable energy sources. Stringent simulation results performed in MATLAB/SIMULINK environment verify the proficiency of the proposed control technique.Smart and Sustainable Insular Electricity Grids Under Large-Scale Renewable Integratio

Optimal Planning of Microgrid-Integrated Battery Energy Storage

Battery energy storage (BES) is a core component in reliable, resilient, and cost-effective operation of microgrids. When appropriately sized, BES can provide the microgrid with both economic and technical benefits. Besides the BES size, it is found that there are mainly three planning parameters that impact the BES performance, including the BES integration configuration, technology, and depth of discharge. In this dissertation, the impact of each one of these parameters on the microgrid-integrated BES planning problem is investigated. Three microgrid-integrated BES planning models are developed to individually find the optimal values for the aforementioned parameters. These three microgrid-integrated BES planning models are then combined and extended, by including the impact of microgrid islanding incidents on the BES planning solution, to develop a comprehensive planning model that can be used by microgrid planners to simultaneously determine the installed BES optimal size, integration configuration, technology, and maximum depth of discharge. Besides applications in microgrids, this dissertation investigates the integration of BES to provide other types of support in distribution networks such as load management of commercial and industrial customers, distribution network expansion, and solar PV ramp rate control

Coordinated Voltage and Reactive Power Control for Renewable Dominant Smart Distribution Systems

Driven by their economic and environmental advantages, smart grids promote the deployment of active components, including renewable energy sources (RESs), energy storage systems (ESSs), and electric vehicles (EVs), for sustainability and environmental benefits. As a result of smart grid technologies and the amount of data collected by smart meters, better operation and control schemes can be developed to allow for cleaner energy with high efficiency, and without breaching network operating constraints. Power distribution networks may face some operational and control challenges as the integration of intermittent energy sources (wind and PV power systems) increases. Some of these challenges include voltage rise and fluctuation, reverse power flow, and the malfunction of conventional Volt/Var control devices. Depending on their location, RESs may introduce two issues related to the Volt/Var control problem, the first of which is that the severity of loading variations will be greater than the case without RESs. The second occurs when the RES is connected between the load center and any regulating devices. The power in-feed from the intermittent RESs may not only mislead the regulator’s control circuit, resulting in unfavorable voltage, but may also enforce the regulator taps to operate randomly following bus voltage variations. This thesis investigates and presents a methodology for the Volt/Var control problem in Smart Distribution Grids (SDGs) under the high penetration and fluctuation of RESs. The research involves the application of predictive control actions to optimally set Volt/Var control devices before the predicted voltage violation takes place. The main objective of this controller is to manage and control the operation of Volt/Var devices in an optimal way that improves the voltage profile along the feeders, reduces real power losses and minimizes the number of Volt/Var device taps and/or switching movements under all loading conditions and for high penetration RESs. This thesis first presents a very Short-Term Stacking Ensemble (STSE) forecasting model for solar PV and wind power outputs that is developed to predict the generated power for intervals of 15 minutes. The proposed model combines heterogeneous machine learning algorithms composed of three well-established models: Support Vector Regression (SVR); Radial Basis Function Neural Network (RBFNN); and Random Forest (RF) heuristically via SVR. The STSE model aims to minimize the prediction error associated with renewable resources when used in the real-time operation of power distribution networks. Secondly, a day-ahead Predictive Volt/Var Control (PVVC) model is developed to find the optimal coordination between Volt/Var control devices under the high penetration and power variations of RESs. The objective of the PVVC model is defined as simultaneous minimization of voltage deviation at each bus, power losses, operating cycle of regulation equipment, and RES curtailment. The benefit of using smart inverter interface RESs with the capability of injective/absorbing reactive power is examined and applied as ancillary services for voltage support. Thirdly, a Sequential Predictive Control (SPC) Strategy for smart grids is developed. The model uses the past and currently available data to forecast demand and RES outputs for intervals of 15 minutes, with real-time updating mechanisms. It then schedules the settings and operations of Volt/Var control devices by solving the Volt/Var control problem in a rolling horizon optimization framework. Because the optimization must be solved in a short interval with a global solution, a solution methodology for linearizing the nonlinear optimization problem is adapted. The original control problem, which is a Mixed-Integer Nonlinear Programming (MINLP) optimization problem, is transformed into a Mixed Integer Second Order Conic Programming (MISOCP) problem that guarantees a global solution through convexity and remarkably reduces the computational burden. Case studies carried out to compare the proposed model against state-of-the-art models provides evidence for the proposed model’s effectiveness. Results indicate that the SPC is capable of accurately solving the control problem within small time slots. The proposed models aim to efficiently operate SDGs at a high penetration level of RES for a day-ahead, as well as in real-time, depending on the preference of network operators. The primary purpose is to minimize operating costs while increasing the efficiency and lifespan of Volt/Var control devices