Chengzong Pang

Electric vehicles as configurable distributed energy storage in the smart grid

Studying the impact of PHEVs/BEVs is quite complex since no other approach before had the unique capability of acting as dispersed and yet mobile energy storage that may be aggregated at different scales. This paper aims at demonstrating the potential benefits of using electrical vehicles (EVs) as distributed energy storage systems in smart grid. It discusses the options of grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operating modes that might be used to support the power grid through demand side management (DSM) program. The battery charging performance, implementation and benefits of using EVs as distributed energy storages for demand-side management are discussed and demonstrated with test cases.

Optimal siting and sizing of electric vehicle public charging stations considering smart distribution network reliability

Green House Gases (GHG) emissions due to oilbased fuel cars with Internal Conventional Engines (ICEs) in metropolitan areas is still a challenge. Plug-In Electric Vehicles (PEVs) eventually will become the economical choice for transportation due to their significant advantages of using flexible fuels, convenience, safe charging, high performance and cost saving. However, inappropriate place and size of aggregated PEVs may threaten power system reliability. Therefore, optimal planning of charging stations is required to maintain power system reliability. On the other hand, candidate places for placing charging stations should respect city traffic layout as well as electrical distribution networks. In this paper, an approach to optimal siting and sizing of public charging station considering traffic constraints of city is proposed. The objective function minimizing Energy Not Supplied (ENS) and charging stations related costs. Candidate places of charging stations are optimally found in 33 bus radial distribution network by Genetic Algorithm. Results reveal optimal location and size of charging stations in order to maintain power system reliability.

Optimal planning of parking lots and demand response programs in distribution network considering power loss and voltage profile

Plug-In Electric Vehicles (PEVs) have been developing to cope with fossil fuels pollution, which is produced by Internal Combustion Engine (ICE) vehicles in big cities. The vehicles are equipped by strong batteries, which can be charged and discharged for many times. This significant aspect enables vehicles to participate in various electricity power markets. In this paper, optimal sizing of parking lots along with Demand Response (DR) programs are presented to decline distribution network loss and voltage drop. Times of Use (TOU), Critical Peak Pricing (CPP) and Real Time Pricing (RTP) as three major time-based DR programs are applied to the problem. Genetic Algorithm (GA) is employed to solve the optimization problem. Simulation is carried out on a 33 bus radial distribution network. Results demonstrate optimal sizing of parking lots along with implemented DR programs has a significant effect on improving network loss and voltage drop.

Comparison of MPPT techniques for SEPIC converter based photovoltaic system

In the near future solar energy will be the primary energy source. More than 45% of required energy in the world will be generated by photovoltaic arrays. Therefore it is imperative to have focus on reduction of costs as well as on enhancing the efficiency of PV array. In order to carry out the latter part, Maximum Power Point Tracking Technique (MPPT) is used to improve the power output from solar array. With a proper review of the reported techniques, this paper attempts to take out the bewilderment while selecting a MPPT by a comparative review on most of the widely adopted MPPT algorithms such as P&O, Incremental Conductance, Fuzzy Logic and PSO, as every technique has its own merits and demerits. Their performance is evaluated using MATLAB and the results are compared for different types of MPPT algorithms.

Neuro-fuzzy based UPQC controller for Power Quality improvement in micro grid system

This paper demonstrates the Power Quality enhancement of grid interactive micro grids. The Power Quality problem is addressed by Unified Power Quality Conditioner (UPQC) which provides a cooperative control on voltage harmonics and unbalances in a micro grid. The proposed system presents Power Control strategies by using a single stage converter for a grid connected micro grid system in order to reduce the multiple DC-AC-DC conversions in an individual AC or DC grid. These micro grids with the proposed converter are applied to general renewable energy sources which will lead to maximum utilization of power at environmental free conditions with low losses improving the efficiency of the system. This paper also proposes the concept of neuro-fuzzy controller for frequency tracking and extraction of harmonics in grid voltage and load currents. This system is verified using Matlab/Simulink with the results being satisfactory.

Marginal levelized cost of energy bases optimal operation of distribution system considering photovoltaics

The significant increase in Distribution Generation (DG) technologies such as solar and wind can provide environmental and economic benefits. However, uncontrolled solar and wind penetration at distribution level can have adverse effects on the feeders, such as overleverage. On the other hand controlling DG output can reduce the benefits for the residential level DG operators. This paper proposes a methodology for controlling residential DG output while providing incentive for their participation. The control of residential level DG is based on the power-loss and node voltage. The proposed controller will maximize the real power output, will compensate the DG operator using the leveliazed cost of energy. Marginal Levelized Cost of Energy (MCLOE) is proposed in this work for PV modules using the concept of Levelized Cost of Energy in power system operations. The proposed method is able to minimize the electricity cost by using multi-objective optimized operation strategy for a distribution system with residential PVs. A case study is also presented to validate the feasibility of proposed methodology.

Determining Optimal Forming of Flexible Microgrids in the Presence of Demand Response in Smart Distribution Systems

Implementing microgrids in power systems will improve the network reliability and reduce the impact of outages on end-users. Determining the most efficient boundaries of microgrids under contingencies is one of the main challenges for utilities from reliability and economics points of view. Currently, most research works have been focused on predefined boundary or static microgrids regardless system conditions and priority or importance of customers. In this paper, a novel concept for designing and operation of flexible microgrids in order to improve the reliability of a power distribution system is proposed. Compared to current approaches, boundaries of the proposed flexible microgrids can be extended or shrunk based on generation and demand levels, technical constraints, and customers’ comfort. Furthermore, a demand response (DR) program is performed to maintain a balance between generation and consumption in the microgrid. In this paper, genetic algorithm (GA) and mixed-integer linear programming (MILP) are simultaneously applied to a model and solve two-stage optimization considering utilities’ profits and customers’ satisfaction. In planning level, GA is utilized for sitting and sizing of distributed generations and placement of switches. In operation level, MILP is used to select target switches as boundaries of optimal microgrids, model priority of customers, and determine the contribution of each load in the DR program. The case study is also presented and final results show the superiority of the proposed method compared with the traditional fixed boundaries method in microgrids.

Smooth shunt control of a fuzzy based distributed power flow controller to improve power quality

Presently, the quality of power supplied is essential to many customers. Power quality (PQ) is a valued utility service where many customers are prepared to pay and get it. In the future, distribution system operators ought to decide, to provide their customers with distinct PQ ranges at different prices. Here, in this paper, a new control action to improve and maintain and enhance the power quality of an electrical power system is proposed in this paper. Fuzzy based distributed power flow controller (DPFC) is designed and put into action to compensate the voltage imbalances arising in a power system. This customized DPFC is an advanced FACTS device, which has its structure analogous to unified power flow controller (UPFC). DPFC comprises of both series and shunt converters, in which its three phase series converter is distributed over the transmission line as several single phase static converters ensuring high controllability and reliability at a low cost compared to an UPFC. A central controlling circuit is designed to supply reference signals to each of the individual controlling circuits of both series and shunt converters. This customized device is applied to a single machine infinite bus power system having nonlinear loads connected to it and is simulated in MATLAB/Simulink environment by using OPAL-RT 5600 Real-time digital Simulator. The results demonstrate the validation of proposed technique to enhance the power quality.

Life time analysis of distribution transformer using experimental design

This paper presents a 24 factorial design to analyze the joint effect of loading, cooling characteristics, ambient temperature, and Oil Time Constant (OTC) on transformer Loss of Life (LOL). Transformer LOL is calculated for 16 combinations of factor levels. Residential load profile obtained from a utility is used to precisely model the loading factor. Design-Expert® Software Version 9 is used to statistically analyze the joint effect of factors. Results show the significance and contribution of factors and their interactions to distribution transformer loss of life.

A low cost sensor based autonomous and semi-autonomous fire-fighting squad robot

The use of robots in situations that can be too dangerous for human interventions is growing. Evolving sensor and mechanical advances, out dangers people from risk of fire hazards. This paper presents an intelligent multi sensor based autonomous & semi-autonomous robot, which rescues from fire accidents in common day-to-day life. The proposed robot can be materialized very economically, which constitutes six integral modules which includes its structure, obstacle avoidance & driver system, control system governed by a microcontroller, fire detection system, remote supervising system, Global System for Mobile communication module. In autonomous mode, when juxtaposed with a smoke detector, it takes lead as it can quench the fire at its inception than sitting tight for an object to smolder and create smoke. It voluntarily detects, navigates itself and extinguishes fire without any human aid, thus saving lives of many individuals. It also sends the emergency warning signal alerts to the security personnel in the duty and within reach fire station through the rooted GSM module. In semi-autonomous mode, this robot was designed to act upon voice commands as well as from a general user interface developed on the touch screen. This robot has added feature of operating in groups by communicating between them.