Decoupling and Control of Real and Reactive Power in Grid-Connected Photovoltaic Power System

The paper presents a detailed modeling and simulation of different control schemes of the real and reactive power flows in a three-phase voltage source inverter (VSI) interfacing a photovoltaic (PV) generation system to the power grid. Synchronisation of the inverter and grid AC waveforms is achieved using a phase-locked-loop (PLL) circuit. An effective decoupling strategy based on proportional-integral (PI) controllers is designed to eliminate the interaction between the two current components. Finally, the influence of the grid disturbances on the PV system and the influence of the solar energy intermittency on the power grid have been tested. The overall model is implemented in Matlab and Simulink/SimPowerSystems toolboxes. Simulations results with the PV system operating with real irradiance data will be presented to demonstrate the performance of the proposed decoupling and control strategies under different conditions of the power gridNon peer reviewe

Enhanced Electric Vehicle Integration in the UK Low Voltage Networks with Distributed Phase Shifting Control

Electric vehicles (EV) have gained global attention due to increasing oil prices and rising concerns about transportation-related urban air pollution and climate change. While mass adoption of EVs has several economic and environmental benefits, large-scale deployment of EVs on the low-voltage (LV) urban distribution networks will also result in technical challenges. This paper proposes a simple and easy to implement single-phase EV charging coordination strategy with three-phase network supply, in which chargers connect EVs to the less loaded phase of their feeder at the beginning of the charging process. Hence, network unbalance is mitigated and, as a result, EV hosting capacity is increased. A new concept, called Maximum EV Hosting Capacity (HC max) of low voltage distribution networks, is introduced to objectively assess and quantify the enhancement that the proposed phase-shifting strategy could bring to distribution networks. The resulting performance improvement has been demonstrated over three real UK residential networks through a comprehensive Monte Carlo simulation study using Matlab and OpenDSS tools. With the same EV penetration level, the under-voltage probability was reduced in the first network from 100% to 54% and in the second network from 100% to 48%. Furthermore, percentage voltage unbalance factors in the networks were successfully restored to their original values before any EV connection.Peer reviewedFinal Accepted Versio

Optimised Residential Loads Scheduling Based on Dynamic Pricing of Electricity : A Simulation Study

This paper presents a simulation study which addresses Demand Side Management (DSM) via scheduling and optimization of a set of residential smart appliances under day-ahead variable pricing with the aim of minimizing the customer’s energy bill. The appliances’ operation and the overall model are subject to the manufacturer and user specific constraints formulated as a constrained linear programming problem. The overall model is simulated using MATLAB and SIMULINK / SimPowerSystems basic blocks. The results comparing Real Time Pricing (RTP) and the Fixed Time Tariff (FTT) demonstrate that optimal scheduling of the residential smart appliances can potentially result in energy cost savings. The extension of the model to incorporate renewable energy resources and storage system is also discussedNon peer reviewedFinal Accepted Versio

Demand Response Strategy Based on Reinforcement Learning and Fuzzy Reasoning for Home Energy Management

As energy demand continues to increase, demand response (DR) programs in the electricity distribution grid are gaining momentum and their adoption is set to grow gradually over the years ahead. Demand response schemes seek to incentivise consumers to use green energy and reduce their electricity usage during peak periods which helps support grid balancing of supply-demand and generate revenue by selling surplus of energy back to the grid. This paper proposes an effective energy management system for residential demand response using Reinforcement Learning (RL) and Fuzzy Reasoning (FR). RL is considered as a model-free control strategy which learns from the interaction with its environment by performing actions and evaluating the results. The proposed algorithm considers human preference by directly integrating user feedback into its control logic using fuzzy reasoning as reward functions. Q-learning, a RL strategy based on a reward mechanism, is used to make optimal decisions to schedule the operation of smart home appliances by shifting controllable appliances from peak periods, when electricity prices are high, to off-peak hours, when electricity prices are lower without affecting the customer’s preferences. The proposed approach works with a single agent to control 14 household appliances and uses a reduced number of state-action pairs and fuzzy logic for rewards functions to evaluate an action taken for a certain state. The simulation results show that the proposed appliances scheduling approach can smooth the power consumption profile and minimise the electricity cost while considering user’s preferences, user’s feedbacks on each action taken and his/her preference settings. A user-interface is developed in MATLAB/Simulink for the Home Energy Management System (HEMS) to demonstrate the proposed DR scheme. The simulation tool includes features such as smart appliances, electricity pricing signals, smart meters, solar photovoltaic generation, battery energy storage, electric vehicle and grid supply.Peer reviewe

Demand-Response Based Energy Advisor for Household Energy Management

Home energy management systems (HEMS) are set to play a key role in the future smart grid (SG). HEMS concept enables residential customers to actively participate in demand response programs (DR) to control their energy usage, reduce peak demand and therefore contribute to improve the performance and reliability of the grid. The aim of this paper is to propose an energy management strategy for residential end-consumers. In this framework, a demand response strategy is developed to reduce home energy consumption. The proposed algorithm seeks to minimise peak demand by scheduling household appliances operation and shifting controllable loads during peak hours, when electricity prices are high, to off-peak periods, when electricity prices are lower without affecting the customer’s preferences. The overall system is simulated using MATLAB/Simulink and the results demonstrate the effectiveness of the proposed control strategy in managing the daily household energy consumption.Peer reviewe

Modeling and Control of a UPFC System Using Pole-Placement and Hinf Robust Control Techniques

This is an open access article distributed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/FACTS (Flexible AC Transmission Systems) technology has now been accepted as a potential solution to the stability problem and load flow. The Unified Power Flow Controller (UPFC) is considered to be the most powerful and versatile among all FACTS devices. This paper presents the modeling and control of a UPFC system using pole-placement and H robust control techniques. A simulation study using Matlab/Simulink is presented to compare the performance of these control strategies and their robustness with respect to variations is the system parameters such as the inductance of the transmission line.Peer reviewe

Grid Power Quality Enhancement Using Fuzzy Control-Based Shunt Active Filtering

Active filtering has proved efficient for the mitigation of harmonics in distribution grids. This paper deals with the design of fuzzy control strategies for a three-phase shunt active filter to enhance the power quality via the regulation of the DC bus voltage of the distribution network. The proposed control scheme is based on Interval Type 2 Fuzzy Logic controller. A simulation study is performed under Simulink/Matlab to evaluate the performance and robustness of the proposed control schemePeer reviewedFinal Accepted Versio

Power Quality Improvement and Low Voltage Ride through Capability in Hybrid Wind-PV Farms Grid-Connected Using Dynamic Voltage Restorer

© 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission.This paper proposes the application of a dynamic voltage restorer (DVR) to enhance the power quality and improve the low voltage ride through (LVRT) capability of a three-phase medium-voltage network connected to a hybrid distribution generation system. In this system, the photovoltaic (PV) plant and the wind turbine generator (WTG) are connected to the same point of common coupling (PCC) with a sensitive load. The WTG consists of a DFIG generator connected to the network via a step-up transformer. The PV system is connected to the PCC via a two-stage energy conversion (dc-dc converter and dc-ac inverter). This topology allows, first, the extraction of maximum power based on the incremental inductance technique. Second, it allows the connection of the PV system to the public grid through a step-up transformer. In addition, the DVR based on fuzzy logic controller is connected to the same PCC. Different fault condition scenarios are tested for improving the efficiency and the quality of the power supply and compliance with the requirements of the LVRT grid code. The results of the LVRT capability, voltage stability, active power, reactive power, injected current, and dc link voltage, speed of turbine, and power factor at the PCC are presented with and without the contribution of the DVR system.Peer reviewe

Power Quality Enhancement of DFIG Based Wind Energy System Using Priority Control Strategies

A. BOUZEKRI T. ALLAOUI, M. DENAI, 'Power Quality Enhancement of DFIG Based Wind Energy System Using Priority Control Strategies', Journal of Electrical Engineering, Vol. 15 (4): 139-145, 2015.The integration of intermittent renewable energy sources into the electric grid presents some challenges in terms of power quality issues, voltage regulation and stability. Power quality relates to those factors which affect the variability of the voltage level and distortion of the voltage and current waveforms which can cause severe adverse effects to the electric grid. The paper focuses on the design and evaluation of a priority control strategy for improving the quality of energy of a grid-connected variable speed Doubly Fed Induction Generator (DFIG) wind energy conversion system. The aim of priority control is to manage the priority among three different controls: active stator power control; reactive stator power control and harmonic rotor current control by using the active shunt filter with SRF method harmonic compensation, and to have a high performance and robustness; an adaptive-fuzzy PI control are including for currents rotor control. The simulation model was developed in Matlab/Simulink environment. The results show that the proposed control scheme can effectively reduce the Total Harmonic Distortion (THD) in the grid currents.Peer reviewedFinal Published versio

Power Quality Enhancement in Hybrid Photovoltaic-Battery System based on three–Level Inverter associated with DC bus Voltage Control

This modest paper presents a study on the energy quality produced by a hybrid system consisting of a Photovoltaic (PV) power source connected to a battery. A three-level inverter was used in the system studied for the purpose of improving the quality of energy injected into the grid and decreasing the Total Harmonic Distortion (THD). A Maximum Power Point Tracking (MPPT) algorithm based on a Fuzzy Logic Controller (FLC) is used for the purpose of ensuring optimal production of photovoltaic energy. In addition, another FLC controller is used to ensure DC bus stabilization. The considered system was implemented in the Matlab /SimPowerSystems environment. The results show the effectiveness of the proposed inverter at three levels in improving the quality of energy injected from the system into the grid.Peer reviewedFinal Published versio