A low-complexity FS-MPDPC with extended voltage set for grid-connected converters

The conventional finite control set model predictive control (FS-MPC) for converter control is a well-studied area, but performance degradation due to the finite candidate vector set is still limiting its practical applications. Extending the voltage vector set using discrete space vector modulation has been proposed as a solution to overcome the limitations, but the brute-force search inherent to FS-MPC increases the computational complexity for a larger voltage set. This paper proposes a technique to alleviate the above issue by avoiding the brute-force search that is being executed in FS-MPC. The technique utilises the basics of direct-power-control theory to cut down the number of candidate voltage vectors applied in each cycle in the optimization problem. In this work, a design example having a voltage vector set of 37 elements is considered, and the proposed technique narrows down the search to eight optimal vectors. The proposed controller is specifically designed for active–reactive power control of a grid-connected converter that interlinks an energy storage system to the grid. The system is modelled in MATLAB Simulink environment and simulations are carried out to analyse the performance in all four active–reactive bidirectional power flow modes. Results validate the performance of the controller, both in steady-state and transient conditions. Further, the reduction in computational complexity due to the proposed algorithm is evaluated. It is observed that the number of computations was reduced approximately by 75% after applying the proposed algorithm for a system with a 37 voltage vector set

Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey

: Integration of high volume (high penetration) of photovoltaic (PV) generation with power grids consequently leads to some technical challenges that are mainly due to the intermittent nature of solar energy, the volume of data involved in the smart grid architecture, and the impact power electronic-based smart inverters. These challenges include reverse power flow, voltage fluctuations, power quality issues, dynamic stability, big data challenges and others. This paper investigates the existing challenges with the current level of PV penetration and looks into the challenges with high PV penetration in future scenarios such as smart cities, transactive energy, proliferation of plug-in hybrid electric vehicles (PHEVs), possible eclipse events, big data issues and environmental impacts. Within the context of these future scenarios, this paper reviewed the existing solutions and provides insights to new and future solutions that could be explored to ultimately address these issues and improve the smart grid’s security, reliability and resilienc

Case study on the effects of partial solar eclipse on distributed PV systems and management areas

Photovoltaic (PV) systems are weather-dependent. A solar eclipse causes significant changes in these parameters, thereby impacting PV generation profile, performance, and power quality of larger grid, where they connect to. This study presents a case study to evaluate the impacts of the solar eclipse of 21 August 2017, on two real-world grid-tied PV systems (1.4 MW and 355 kW) in Miami and Daytona, Florida, the feeders they are connected to, and the management areas they belong to. Four types of analyses are conducted to obtain a comprehensive picture of the impacts using 1 min PV generation data, hourly weather data, real feeder parameters, and daily reliability data. These analyses include: individual PV system performance measurement using power performance index; power quality analysis at the point of interconnection; a study on the operation of voltage regulating devices on the feeders during eclipse peak using an IEEE 8500 test case distribution feeder; and reliability study involving a multilayer perceptron framework for forecasting system reliability of the management areas. Results from this study provide a unique insight into how solar eclipses impact the behaviour of PV systems and the grid, which would be of concern to electric utilities in future high penetration scenarios

ANALYSIS OF THE EFFECT OF ELECTRIC AND MAGNETIC LOA DINGS ON THE DESIGN PARAMETERS OF AN INDUCTION MOTOR AND ITS PER FORMANCE USING MATLAB/SIMULINK

This paper looks at the effect of magnetic loading and electric loading on the design parameters of an induction motor and its performance. The study involves the u se of MATLAB to simulate 50kW, 3-phase, 415V, 50Hz, 6 poles induction machine. Based on the variation of the ma gnetic and electric loading of the machine, the var ious design values of the rotor and stator of the machine are s pecified. The performance index which includes stat or loss, rotor loss, cost, power factor, efficiency, and torque ar e also specified for squirrel cage induction motor (SCIM) Keyword: MATLAB, stator, rotor, magnetic loading, e lectric loading, SCIM

Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey

Integration of high volume (high penetration) of photovoltaic (PV) generation with power grids consequently leads to some technical challenges that are mainly due to the intermittent nature of solar energy, the volume of data involved in the smart grid architecture, and the impact power electronic-based smart inverters. These challenges include reverse power flow, voltage fluctuations, power quality issues, dynamic stability, big data challenges and others. This paper investigates the existing challenges with the current level of PV penetration and looks into the challenges with high PV penetration in future scenarios such as smart cities, transactive energy, proliferation of plug-in hybrid electric vehicles (PHEVs), possible eclipse events, big data issues and environmental impacts. Within the context of these future scenarios, this paper reviewed the existing solutions and provides insights to new and future solutions that could be explored to ultimately address these issues and improve the smart grid’s security, reliability and resiliency