A Methodology for Transforming an Existing Distribution Network Into a Sustainable Autonomous Micro-Grid

Kirthiga, M. Venkata; Daniel, S. Arul; Gurunathan, Selvakumar

doi:10.1109/tste.2012.2196771

Cited by 128 publications

(70 citation statements)

References 27 publications

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“…In addition, the summation of consumed power by these customers should be equal to the summation of EGP during a daily operation system as shown mathematically in Eq. (19).…”

Section: B Mg Mathematical Modelingmentioning

confidence: 99%

“…On the other hand, these problems can be solved with the non-deterministic polynomial-hard (NP-hard) problem. Heuristic algorithms such as genetic algorithm [16], particle swarm optimization [17], ant colony optimization [18] and bee colony optimization [19] are some optimization methods used for unit commitment within MGs [14]. Some algorithms give a better solution for some particular problems than others.…”

mentioning

confidence: 99%

See 1 more Smart Citation

An Optimal Energy Management System for Islanded Microgrids Based on Multiperiod Artificial Bee Colony Combined With Markov Chain

Marzband

Azarinejadian

Savaghebi

et al. 2017

IEEE Systems Journal

226

123

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“…In addition, the summation of consumed power by these customers should be equal to the summation of EGP during a daily operation system as shown mathematically in Eq. (19).…”

Section: B Mg Mathematical Modelingmentioning

confidence: 99%

mentioning

confidence: 99%

An Optimal Energy Management System for Islanded Microgrids Based on Multiperiod Artificial Bee Colony Combined With Markov Chain

Marzband

Azarinejadian

Savaghebi

et al. 2017

IEEE Systems Journal

226

123

View full text Add to dashboard Cite

“…Suppose the ith parent particle X(i) and the jth parent particle X(j) are chosen to perform the horizontal crossover operation at the dth dimension, their offspring, namely the moderation solution, can be reproduced through the equations as shown in Equation (12).…”

Section: Horizontal Crossovermentioning

confidence: 99%

“…In the process of the horizontal crossover, all particles of CSO are randomly divided into M/2 pairs. Each pair of particles reproduces two moderation solutions according to Equation (12). Through the horizontal crossover operator, new solutions can be searched in a hypercube space with a larger probability while in the periphery of each hypercube with a decreasing probability, which had been proved in [26].…”

Section: Horizontal Crossovermentioning

confidence: 99%

Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem

Peng

Zheng

et al. 2015

Energies

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Distributed generation (DG) systems are integral parts in future distribution networks. In this paper, a novel approach integrating crisscross optimization algorithm and Monte Carlo simulation (CSO-MCS) is implemented to solve the optimal DG allocation (ODGA) problem. The feature of applying CSO to address the ODGA problem lies in three interacting operators, namely horizontal crossover, vertical crossover and competitive operator. The horizontal crossover can search new solutions in a hypercube space with a larger probability while in the periphery of each hypercube with a decreasing probability. The vertical crossover can effectively facilitate those stagnant dimensions of a population to escape from premature convergence. The competitive operator allows the crisscross search to always maintain in a historical best position to quicken the converge rate. It is the combination of the double search strategies and competitive mechanism that enables CSO significant advantage in convergence speed and accuracy. Moreover, to deal with system uncertainties such as the output power of wind turbine and photovoltaic generators, an MCS-based method is adopted to solve the probabilistic power flow. The effectiveness of the CSO-MCS method is validated on the typical 33-bus and 69-bus test system, and results substantiate the suitability of CSO-MCS for multi-objective ODGA problem.

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“…As a systematic integration of DGs system, a micro-grid can offer many technical advantages in terms of power quality and energy management [7,8]. The basic requirements of micro-grids are the high quality point of common coupling (PCC) voltage in both grid-tied and stand-alone operations in terms of stable voltage amplitude and frequency.…”

Section: Introductionmentioning

confidence: 99%

Coordinated Control and Fault Protection Investigation of a Renewable Energy Integration Facility with Solar PVs and a Micro-Turbine

2017

Energies

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Abstract:In this paper, a renewable energy integration facility (REIF) with photovoltaic (PV) distributed generation resources for micro-grid applications is studied. In grid-tied operation, the PV system together with the grid supply the power to the local loads while the surplus energy is fed back to the grid. In stand-alone mode, a gas micro-turbine is operated as a master to establish the common AC bus voltage to which the PV inverters can synchronize The experimental results demonstrate the stable operation of the REIF under various generation and load conditions. The power quality can meet the IEEE Standard 1547. Furthermore, the responses of the REIF under different fault conditions are investigated. Relevant protection mechanisms are then developed, providing insights into the fault protection for the future grid.

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A Methodology for Transforming an Existing Distribution Network Into a Sustainable Autonomous Micro-Grid

Cited by 128 publications

References 27 publications

An Optimal Energy Management System for Islanded Microgrids Based on Multiperiod Artificial Bee Colony Combined With Markov Chain

An Optimal Energy Management System for Islanded Microgrids Based on Multiperiod Artificial Bee Colony Combined With Markov Chain

Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem

Coordinated Control and Fault Protection Investigation of a Renewable Energy Integration Facility with Solar PVs and a Micro-Turbine

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