Applied Power Electronics

Most of the electric machines had a conventional design for speed –control. Previously, the speed regulation of these motors was done via traditional or mechanical contacts, for example: inserting resistors to the armature circuit or controlling the excited circuit of DC motor, and other methods of control. These classical methods, however, lead to non-linearity in mechanical or electromechanical characteristics [ω= f(M) or ω= f(I)], which in turn lead to increased power losses as the result of the non-soft regulation of speed, as well as the great inertia of classical control methods that rely on mechanical and electromagnetic devices.

Energy Storage System and Its Power Electronic Interface

This chapter examines the modeling and simulation of energy storage (battery, flywheel, etc.) systems interfaced to the power grid by using power electronic device, like chopper module, Rectifier module, and filter circuits, which are essential to the load balance between supply and demand, and to eliminate harmonics and to ensure efficient, cost effective, and reliable operations. Energy storage system in power grid is the same as memory in computer system. Energy efficiency is a key performance indicator for energy storage system. The energy storage system is the most promising component to enhance the system reliability and flexibility.

State Estimation of Active Distribution Networks

Monitoring and controlling the electrical distribution system for real time is becoming very important to improve its operating performance after transition to active distribution systems. So, many sensors are needed to monitor all parts in the systems. But if sensors are installed at all buses, investment cost becomes huge. To reduce the number of sensors, state estimation approach can be used to estimate the voltage of buses, which do not have sensors. State Estimation (SE) algorithms are broadly classified into Static State Estimator (SSE) and Dynamic State Estimator (DSE). This chapter classifies most algorithms used in active distribution networks, also State estimation in unbalanced distribution systems, and Role of PMU in Distribution System State Estimation.

Loss Minimization in Active Distribution Network

Power loss reduction is an important problem that needs to be addressed with respect to generating electrical power. It is important to reduce power loss using locally generated power sources and/or compensations. This chapter brings a method of presents a method of maximizing energy utilization, feeder loss reduction, and voltage profile improvement for radial distribution network using the active and reactive power sources. Distributed Generation (DG) (wind and solar with backup by biomass generation) and shunt capacitor (QG) for reactive power demand are used. Integrating DG and QG at each bus might reduce the loss but it is economically unaffordable, especially for developing countries. Therefore, the utilization optimization method is required for finding an optimal size and location to feeders for placing QG and DG to minimize feeder loss.

Introduction to Electric Distribution System

Distribution system is the final stage of electric power system, and can be classified based on voltage level, location, number of wires, and types of customers. This chapter explains the various classifications of the distribution system in detail. System reliability is one of the important design concerns for any distribution system. The various methods of design concept to improve reliability are clarified. Reactive power compensation is another main concern in a distribution system. Methods of reactive power compensation are also detailed.

Micro-Grid Planning and Resilience Within Bulk System Planning and Operation

Micro grid is widely used in real worlds for advanced forecasting and demand response of renewable energy source, grid integration, and operations. Micro grid consists of conventional and nonconventional energy source such as wind energy, solar energy, biomass energy, hydro power, diesel power, fuel cell, geothermal power, thermal power, etc. Micro grid is a combination of AC power and DC power such as wind, solar, fuel cell, biomass, and Hydro power, which is mostly used in micro grids. Grid can be operated by grid connected mode or islanding modes. Micro grid is classified into traditional micro grids and smart micro grids.

Generation Extension Arrangement in Power Engineering Networks Using Chaotic Grasshopper Optimization Algorithm

Electric utilities over the domain affected with ecological issues associated with standard fossil fuel-established plants are examining more within the potentiality of interposing energy sources type of plants into the system as an alternative. Integration of Demand Side Management (DSM) and Supply Side Management (SSM) is required in a rational power system planning that implies concurrent deliberation of both qualitative and quantitative problems like costs, fuel mix, and reliability of power supply. This chapter examines the economic and environmental ability of power supplies initiation into an existing peak deficit power system, incorporating both DSM and SSM plans. The Generation Expansion Planning (GEP) study is carried out in the power system for the period of 24 years planning horizon.

Smart Home Energy Management System

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

Improvement of the Electrical Network Stability by Using a Renewable Distributed Generator

In this chapter, a control strategy for a Renewable Distribution Generator (RDG) operates in grid-connected and standalone mode is suggested. This RDG is made up of a wind generator associated with a Super-Capacitors (SC) considered as a storage system. The study investigates a control scheme for RDG integrated into power electrical system to maintain the voltage and the frequency of the grid in an allowable range and to ensure the continuity of power supply in case of grid faults. The proposed control strategy has three parts: a vector control of the wind generator to extract the maximum power; the control of the DC bus voltage by inserting the SC; and a droop control loop proposed to ensure the grid stability. The simulation results demonstrate the reliability of the control system.

Voltage Drop Mitigation in Smart Distribution Network

Voltage dip in the distribution network is caused by disturbance at different voltage levels and experienced by low voltage customers are established. Voltage dips are those disturbances which damage the power quality of the distribution network and causing heavy economic damage to the customers. This chapter investigates procedures of mitigating the voltage dip by reducing the number of faults due to short circuits, lowering the fault clearing time, and changing the power system design and DSTATCOM Compensator with DG and dynamic voltage restorer.