Design of an Adaptive Neurofuzzy Inference Control System for the Unified Power-Flow Controller

This paper presents a new approach to control the operation of the unified power-flow controller (UPFC) based on the adaptive neurofuzzy inference controller (ANFIC) concept. The training data for the controller are extracted from an analytical model of the transmission system incorporating a UPFC. The operating points' space is dynamically partitioned into two regions: 1) an inner region where the desired operating point can be achieved without violating any of the UPFC constraints and 2) an outer region where it is necessary to operate the UPFC beyond its limits. The controller is designed to achieve the most appropriate operating point based on the real power priority. In this study, the authors investigated and analyzed the effect of the system short-circuit level on the UPFC operating feasible region which defines the limitation of its parameters. In order to illustrate the effectiveness of the control algorithm, simulation and experimental studies have been conducted using the MATLAB/SIMULINK and dSPACE DS1103 data-acquisition board. The obtained results show a clear agreement between simulation and experimental results which verify the effective performance of the ANFIC controller

A Modelling Tool for Distribution Networks to Demonstrate Smart Grid Solutions

The increased deployment of low carbon technologies in power distribution networks, particularly at the distribution level, is expected to cause significant problems to network operation unless existing networks are appropriately adapted and actively controlled as part of a smart grid. This paper describes the development of a modelling tool to examine Smart Grid solutions to a number of issues affecting low voltage power distribution networks. Use of the tool in the context of transformer overload, line overvoltage, active load control, Grid storage and Black Start analysis is examined

Evaluation of domestic electrical demand and its effect on low voltage network performance

Electrical demand in a house depends on various factors mainly being the user’s behaviour and the rating of the appliances. Some researchers have used daily domestic electrical demand profile at half hour time resolution for the energy management. When data of half hour time interval is used for the analysis of on-site generation, it can lead to over/under -estimates of the proportion of generated energy used on site. As a consequence, this could lead to over/under-estimating in the import and export of power from and to the power grid. In this paper, domestic electricity use profile recorded at high time resolution of one minute is used to analyse the profile obtained at different time resolution and its effect on on-site generation. Daily load profile for summer and winter at time resolution of 30 minute is generated from a data set of 22 houses consisting data of a whole year which is then compared with the daily load curve obtained after diversity maximum demand from the literature. The generated daily load profile is then used to see effect on the low voltage network. For the analysis on the low voltage network, a typical UK low voltage network is developed in the Matlab/Simulink softwar

Maximum power point tracking for variable-speed fixed-pitch small wind turbines

Variable-speed, fixed-pitch wind turbines are required to optimize power output performance without the aerodynamic controls. A wind turbine generator system is operated such that the optimum points of wind rotor curve and electrical generator curve coincide. In order to obtain maximum power output of a wind turbine generator system, it is necessary to drive the wind turbine at an optimal rotor speed for a particular wind speed. In fixed-pitch variablespeed wind turbines, wind-rotor performance is fixed and the restoring torque of the generator needs to be adjusted to maintain optimum rotor speed at a particular wind speed for maximum aerodynamic power output. In turbulent wind environment, control of wind turbine systems to continuously operate at the maximum power points becomes difficult due to fluctuation of wind speeds. Therefore, special emphasis is given to operating at maximum aerodynamic power points of wind rotor. In this paper, the performance of a Fuzzy Logic Maximum Power Point Tracking (MPPT) controller is investigated for applications on variable-speed fixed-pitch small- scale wind turbines

Predictive control of wind turbines by considering wind speed forecasting techniques

A wind turbine system is operated such that the points of wind rotor curve and electrical generator curve coincide. In order to obtain maximum power output of a wind turbine generator system, it is necessary to drive the wind turbine at an optimal rotor speed for a particular wind speed. A Maximum Power Point Tracking (MPPT) controller is used for this purpose. In fixed-pitch variable-speed wind turbines, wind-rotor parameters are fixed and the restoring torque of the generator needs to be adjusted to maintain optimum rotor speed at a particular wind speed for optimum power output. In turbulent wind environment, control of variable-speed fixed-pitch wind turbine systems to continuously operate at the maximum power points becomes difficult due to fluctuation of wind speeds. In this paper, wind speed forecasting techniques will be considered for predictive optimum control system of wind turbines

Fast-individual-harmonic-extraction technique

One outcome of a PhD project (C H Ng, University studentship) A collaborative work (the Energy Systems Group, Northumbria and Durham University). It deals with the problem of harmonic suppression or elimination in power systems for safety and power quality purposes. The speed of harmonic extraction being is a crucial issue in power systems to avoid damage of electrical equipments. Traditionally, harmonic suppression is done via Fourier transform. The main originality of this paper is on the use of a fast harmonic extraction algorithm, which is six times faster than traditional harmonic extraction techniques

Optimal Charging Strategy for EVs with Batteries at Different States of Health

The electric vehicle (EV) is targeted as an efficient method of decreasing CO2 emission and reducing dependence on fossil fuel. Compared with filling up the internal combustion engine (ICE) vehicle, the EV power charging time is usually long. However,to the best of our knowledge, the current charging strategy does not consider the battery state of health (SOH). It is noted that a high charging current rate may damage the battery life. Motivated by this, an optimal charging strategy is proposed in the present paper, providing several optimal charging options taking into account the EV battery health, trying to prevent ‘abused battery utilization’ happening