1,163 research outputs found

    An Improved ABC Algorithm for Energy Management of Microgrid

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    Microgrids are an ideal way of electricity generation, distribution, and regulation for customers by means of distributed energy resources on the community level. However, due to the randomness of photovoltaic and wind power generation, it is a crucial and difficult problem to achieve optimal economic dispatch in microgrids. In this paper, we present an optimal economic dispatch solution for a microgrid by the improved artificial bee colony (ABC) optimization, with the aim of satisfying load and balance demand while minimizing the cost of power generation and gas emission. Firstly, we construct a mathematical model according to different characteristics of distributed generation units and loads, and improve the performance of global convergence for ABC in order to fit such model. Secondly, we explore how to solve the optimal economic dispatch problem by the improved ABC and give the essential steps. Thirdly, we carry out several simulations and the results illustrate the benefits and effectiveness of the proposed approach for optimal economic dispatch in microgrid

    Islanded microgrid congestion control by load prioritization and shedding using ABC algorithm

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    The continued growth in load demand and the gradual change of generation sources to smaller distributed plants utilizing renewable energy sources (RESs), which supply power intermittently, is likely to strain existing power systems and cause congestion. Congestion management still remains a challenging issue in open access transmission and distribution systems. Conventionally, this is achieved by load shedding and generator rescheduling. In this study, the control of the system congestion on an islanded micro grid (MG) supplied by RESs is analyzed using artificial bee colony (ABC) algorithm. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time during islanding mode operation. This is to ensure as minimal load as possible is shed during a contingency that leads to loss of mains and ensure a congestion free microgrid operation. This is tested and verified on a modified IEEE 30-bus distribution systems on MATLAB platform. The results are compared with other algorithms to prove the applicability of this approach

    Multi-Objective Optimal Dispatching and Operation Control of a Grid Connected Microgrid Considering Power Loss of Conversion Devices

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    This paper proposes a novel daily energy management system for optimization dispatch and operation control of a typical microgrid power system. The multi-objective optimization dispatch problem is formulated to simultaneously minimize the operating cost, pollutant emission level as well as the power loss of conversion devices. While satisfying the system load and technical constraints, ensure high penetration of renewable energy and optimal scheduling of charging/discharging of battery storage system based on a fuzzy logic approach. The weighted sum method is adopted to obtain Pareto optimal solutions, then a fuzzy set theory is employed to find the best compromise solution. Ant lion optimizer method is considered to solve the formulated problem. To prove the efficacy and robustness of the proposed algorithm, a comparison of the performance of ant lion optimizer algorithm with other known heuristic optimization techniques has been investigated. The results obtained show that the proposed algorithm outperforms the other heuristic techniques in solving the multi-objective optimization dispatch problem. They also reveal that a better compromise between the considered contradictory objective functions is achieved when priority is given to the generation of the internal microgrid’s sources with an equivalent contribution rate of 68.45% of generated power from both fuel cell and micro-turbine, whereas the contribution rate of external grid is limited to 11.72%

    Local and Central Controllers for Microgrids

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    The main objective of this thesis is to serve as a guide, so readers are able to learn about microgrids and to design simple controllers for different AC microgrid applications. In addition, this thesis has the objective to provide examples of simulation cases for the hierarchical structure of a basic AC microgrid which can be used as a foundation to build upon, and achieve more complex microgrid structures as well as more sophisticated power-converter control techniques. To achieve these objectives, the modeling of voltage source converters and control design in the z-domain are presented. Moreover, the implementation and transient analysis of the power-converter operating modes are executed through MATLAB/SimulinkTM simulations. Then, an energy management case for the central controller of the AC microgrid is performed utilizing real-time simulation tools, Typhoon HIL software and hardware devices in addition to Texas instruments digital signal processors as local controllers

    Microgrid cost optimization: a case study on Abu Dhabi

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    This paper presents a microgrid cost optimization study specifically focused on the United Arab Emirates (UAE) based on the Genetic and Ant-Bee Colony algorithms. The main objective of the paper is to identify size and amount of power supply sources in Microgrids that result in minimum cost. Specific parameters pertaining to the UAE were employed within the new objective function and constraints. Two different scenarios were tested, and their results have been discussed. During this study, it was evident that solar-PV systems were the second most cost-effective way to reduce cost of microgrids preceded by micro-turbines
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