2004아테네 올림픽대회출전 한국레슬링 대표선수의 무산소성 운동능력 및 등속성 근력

Fast depleting fossil fuels and the growing awareness for environmental protection have led us to the energy crisis. Hence, efforts are being made by researchers to investigate new ways to extract energy from renewable sources. ‘Microgrids’ with Distributed Generators (DG) are being implemented with renewable energy systems. Optimization methods justify the cost of investment of a microgrid by enabling economic and reliable utilization of the resources. This paper strives to bring to light the concept of Hybrid Renewable Energy Systems (HRES) and state of art application of optimization tools and techniques to microgrids, integrating renewable energies. With an extensive literature survey on HRES, a framework of diverse objectives has been outlined for which optimization approaches were applied to empower the microgrid. A review of modelling and applications of renewable energy generation and storage sources is also presented.

Optimization in microgrids with hybrid energy systems – A review

A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks

To extract the maximum potential advantages in light of environmental, economical and technical aspects, the optimum installation and sizing of Distributed Generation (DG) in distribution network has always been challenging for utilities as well as customers. The installation of DG would be of maximum benefit where setting up of central power generating units are not practical, or in remote and small areas where the installation of transmission lines or availability of unused land is out of question. The objective of optimal installation of DG in distribution system is to achieve proper operation of distribution networks with minimization of the system losses, improvement of the voltage profile, enhanced system reliability, stability and loadability etc. In this respect analytical (classical) methods, although well-matched for small systems, perform adversely for large and complex objective functions. Unlike the analytical (classical) methods, the intelligent techniques for optimal sizing and siting of DGs are speedy, possess good convergence characteristics, and are well suited for large and complex systems. However, to find a global optimal solution of complex multi-objective problems, a hybrid of two or more meta-heuristic optimization techniques give more effective and reliable solution. This paper presents the fundamentals of DG and DG technologies review the classical and heuristic approaches for optimal sizing and placement of DG units in distribution networks and study their impacts on utilities and customers. An attempt has also been made to compare the analytical (classical) and meta-heuristic techniques for optimal sizing and siting of DG in distribution networks. The present study can contribute meaningful knowledge and assist as a reference for investigators and utility engineers on issues to be considered for optimal sizing and siting of DG units in distribution systems.

Optimal sizing and siting techniques for distributed generation in distribution systems: A review

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Power management and power flow control with back-to-back converters in a utility connected microgrid

A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using Fireworks Algorithm

Optimal location and size of distributed generation (DG) in the distribution system play a significant role in minimizing power losses, operational cost and improving voltage stability. This paper presents a new approach to find the optimal location and size of DG with an objective of minimizing network power losses, operational costs and improving voltage stability. Loss sensitivity factor is used to identify the optimal locations for installation of DG units. Bacterial Foraging Optimization Algorithm (BFOA) is used to find the optimal size of DG. BFOA is a swarm intelligence technique which models the individual and group foraging policies of the Escherichia coli bacteria as a distributed optimization process. The technical constraints of voltage and branch current carrying capacity are included in the assessment of the objective function. The proposed method has been tested on IEEE 33-bus and 69-bus radial distribution systems with various load models at different load levels to demonstrate the performance and effectiveness of the technique.

Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization

Pumping of water requires excessive energy for its operation by consuming a massive amount of diesel, gasoline, electric power etc. The more promising alternative energies to perform the same operation without any energy cost are solar photovoltaic (PV) and wind. These fastest growing renewable energies are more reliable and well suitable for remote villages where there is no possibility of extending transmission lines. Furthermore, these systems are optimal for conditions like only small amount of water needed to be pumped for a particular time. Unlike conventional energy sources of electric power, the renewable energy sources are not dispatchable its power output cannot be controlled. In that case, it involves power conversion stages so that it would necessitate to design an advanced control strategy technique. Those control strategies greatly avoid and protects the system from detrimental operating conditions by monitoring input voltage, water flow, torque, power, pressure, speed and motor vibration etc. Henceforth the use of efficient control strategy not only increase the performance of system it also helps to increase the number of operational hours of solar PV and wind energy systems. In this manuscript, the research work of various control strategies carried out in solar PV and wind energy-based water pumping systems are presented. Additionally, this paper intends to discuss the energy management strategies applied for renewable energy fed water pumping system when the system assisted with third energy system (battery bank, fuel cell, etc). These benefited systems ensure good design, guarantees the control speed required for the motor, regulates the flow of water, assuring accurate operation for all conversion and finally, it maintains precise balance in between the renewable energy generated and power required by the load (pump).

Control and energy management strategies applied for solar photovoltaic and wind energy fed water pumping system: A review

This paper presents a new combined technique for minimizing the power loss in distribution system by optimal Distributed Generation (DG) installation together with capacitor placement. Sensitivity analysis is used to identify the optimal candidate locations of DGs and capacitor placement. Bacterial Foraging Optimization Algorithm (BFOA) is applied to find the optimal size of DGs and capacitors. BFOA is a swarm intelligence technique which models the individual and group foraging policies of the E. coli bacteria as a distributed optimization process. The technical constraints of voltage and branch current carrying capacity are included in the assessment of the objective function. Different cases of DG and capacitor placement are considered to assess the performance of the proposed method. Proposed method has been tested on IEEE 33-bus radial distribution system and the results obtained are encouraging.

M. Kowsalya

Papers

A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks

A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using Fireworks Algorithm

Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization

Control and energy management strategies applied for solar photovoltaic and wind energy fed water pumping system: A review

Optimal Distributed Generation and capacitor placement in power distribution networks for power loss minimization