Di Shi

Adaptive control of energy storage for voltage regulation in distribution system

With the increasing penetration of renewables, the traditional distribution system design philosophy is being challenged. One well-known concern is the voltage rise problem caused by the reverse power flow, when the PV generation substantially exceeds the load demand. Existing solutions of these voltage issues include either restricting PV output or tripping it with over-voltage/under-voltage relays, both of which are disruptive. This paper proposes a novel framework for distribution network voltage regulation by integrating PV system with distributed energy storage system (ESS) and adaptively dispatching the ESS. In the proposed framework, the voltage and current phasors at the point of common coupling (PCC) are continuously monitored to establish a real-time Thevenin equivalent of the distribution grid. Based on this equivalent, the maximum and minimum power injections allowed at PCC are continuously tracked. The voltage violation margins at PCC are calculated and the ESS is controlled adaptively to prevent the occurrence of voltage violation. The proposed method can also be used to mitigate the detrimental effects of sudden change in PV output. The proposed scheme is tested on a typical US distribution system and its effectiveness is demonstrated through simulations.

A decision tree based approach for microgrid islanding detection

This paper proposes a passive islanding detection technique for microgrid. The proposed technique relies on capturing the underlying signatures of a wide variety of system events on critical system parameters through the utilization of pattern recognition tools for islanding detection in a microgrid. The proposed technique is tested on a microgrid model implemented on IEEE 13-node distribution feeder system under a wide variety of system operating states. Results from test case study have been analyzed to evaluate the effectiveness of the proposed method. Case study results indicate that the proposed method can detect islanding events with high accuracy and reliability.

Adaptive control of distributed generation for microgrid islanding

A microgrid (MG) is supposed to operate in both grid-tied mode and islanded mode, smooth transition between which is critical for its reliability. Past efforts have shown that proper control of converter-interfaced distributed generation (DG) units can help maintain stability of MG against islanding. However, it remains unknown as how to quantify and when to initialize such controls. This paper presents a novel DG control strategy for MG islanding purpose using phasor measurements at point of common coupling. During the transition, the proposed controller adjusts DG outputs adaptively to compensate for system power imbalance. To verify the proposed method, a full MG dynamic model with different types of DGs is developed in PSCAD/EMTDC. Case studies demonstrate the advantages of the proposed method in improving load sharing, transient issues and system stability during MG islanding.

Economic analysis, optimal sizing and management of energy storage for PV grid integration

This paper investigates the optimal procurement and scheduling of battery storage a in distribution system with high photovoltaic (PV) penetration. The battery under study is assumed to be owned by private entities with the objective of minimizing the electricity bill (or, interchangeably, maximizing the PV system yields). Voltage regulation is achieved by controlling the net metered real power at the point of common coupling of (PCC) of each entity. Dynamic energy conversion equation is used to model the battery with the impact of cyclic aging considered. The procurement-scheduling problem is formulated as a nonlinear programming (NLP) problem. A recursive method is proposed to determine the lifetime of the battery. The proposed methodology is validated on the IEEE 33-bus feeder system. A thorough economic analysis is conducted to quantify the financial benefits brought in by battery.

Microgrid reactive power management during and subsequent to islanding process

In a microgrid (MG) with high penetration of single phase induction motors (SPIMs), the voltage recovery process after a fault-induced islanding can be very slow. The reason lies in the stall of SPIMs caused by low voltage. During stalling, a SPIM can withdraw as high as three times of its rated power. This phenomenon can cause many problems including the loss of critical load due to the action of protection devices. This paper explores the role of reactive power support during MG islanding and proposes a novel approach to managing the reactive power generation of electronic-interfaced distributed generators (EIDGs). The concept of sensitivity factors is used in the proposed algorithm for regulating voltages at weak load buses. The optimal sharing of reactive power among EIDGs is formulated as a linear programming problem, which can be solved in a very fast manner for real-time control purpose. The proposed method is validated on a MG test-bed evolved from the IEEE standard 13-bus test feeder.

A mixed-mode management system for grid scale energy storage units

Grid scale storage offers valuable benefits for economic and reliable operation of the grid. To justify expensive capital cost of this new technology, it is desirable to increase the revenue stream for storage providers by stacking multiple applications on a single unit. In this paper, we present a mixed-mode management system for grid scale storage which can forecast day-ahead market prices, schedule the storage for participation in energy and frequency regulation markets, and provide voltage regulation service to the grid in real-time. Simulation results show the effectiveness of the proposed method in scheduling and operation of grid scale storage for multiple applications.

A comparative analysis of intelligent classifiers for passive islanding detection in microgrids

This paper proposes a passive islanding detection technique for distributed generations in grid-connected microgrids and presents a comprehensive comparative analysis of intelligent classifiers for passive islanding detection application. The proposed method utilizes pattern recognition techniques in classification of underlying signatures of wide variety of system events on critical system parameters for islanding detection. Case study on a grid-connected microgrid model with different types of distributed generations is performed to evaluate the proposed method and compare the classifier performances. Test results demonstrate the effectiveness of the proposed method in detection of islanding events.

Adaptive Control of Hybrid Ultracapacitor-Battery Storage System for PV Output Smoothing

The integration of hybrid energy storage system (ESS) with PV has been considered an effective solution for PV power smoothing, e.g. the hybrid Ultracapacitor (UC)-Battery storage system. This paper proposes a fuzzy-logic-based adaptive power management system for smoothing PV power output, which manages the power sharing between the UC and Battery system. In this method, the real-time system dynamics are reflected in the adaptive control parameter settings. At the same time this method effectively considers the characteristics and operational constraints of the energy storage devices, e.g. SOC limit, charge/discharge current limit, etc., in order to sustain the system operation. A hybrid PV/UC/Battery power system is modeled by Matlab/Simulink. The simulation studies are performed to demonstrate the effectiveness and advantages of the proposed control method in PV fluctuation suppression, sustainable system operation, energy storage performance.Copyright

A Multi-Dimensional Holomorphic Embedding Method to Solve AC Power Flows

It is well-known that ac power flows of a power system do not have a closed-form analytical solution in general. This paper proposes a multi-dimensional holomorphic embedding method that derives analytical multivariate power series to approach true power flow solutions. This method embeds multiple independent variables into power flow equations and hence, can, respectively, scale power injections or consumptions of selected buses or groups of buses. Then, via a physical germ solution, the method can represent each bus voltage as a multivariate power series about symbolic variables on the system condition so as to derive approximate analytical power flow solutions. This method has a non-iterative mechanism unlike the traditional numerical methods for power flow calculation. Its solution can be derived offline and then evaluated in real time by plugging values into symbolic variables according to the actual condition, so the method fits better into online applications, such as voltage stability assessment. The method is first illustrated in detail on a 4-bus power system and then demonstrated on the IEEE 14-bus power system considering independent load variations in four regions.

Microgrid security assessment and islanding control by Support Vector Machine

A Support Vector Machine (SVM) based approach for microgrid islanding decision and control is investigated. The IEEE 13-feeder system is modified and serves as the microgrid model connected to Kundur four-machine two-area system that models the main transmission grid. A representative data set is obtained through simulations in MATLAB/Simulink considering multiple typical scenarios with or without a fault. A SVM classifier is designed to identify insecure scenarios with satisfying accuracy. Comparisons between different kernel functions are then carried out, which indicate that linear SVM can be effective for the islanding control. The SVM approach is further compared with a decision tree based approach in terms of training and testing accuracies for the microgrid islanding control problem.