برنامه¬ریزی و مدیریت بهینه انرژی منابع تولید پراکنده و ذخیره¬ساز باتری در ریزشبکه هوشمند با هدف کاهش هزینه بهره¬برداری توسط الگوریتم جستجوی فاخته
محورهای موضوعی : مهندسی برق- قدرت
اسماعیل خلیل زاده
1
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احمد قالیبافان
2
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آیدا کشاورز
3
1 - دانشکده مهندسی برق و کامپیوتر، واحد ارسنجان، دانشگاه آزاد اسلامی، ارسنجان، ایران
2 - دانشکده مهندسی برق و کامپیوتر، واحد بندرعباس، دانشگاه آزاد اسلامی، بندرعباس، ایران
3 - گروه اتاق عمل، واحد ارسنجان، دانشگاه آزاد اسلامی، ارسنجان، ایران
کلید واژه: الگوریتم جستجوی فاخته, ذخیره¬ساز باتری, ریزشبکه هوشمند, کاهش هزینه, مدیریت انرژی,
چکیده مقاله :
مدیریت بهینه منابع تولید پراکنده و ذخیرهسازها در ریزشبکههای قدرت با اهداف مختلفی همچون کاهش هزینه بهرهبرداری، کاهش آلودگی محیط زیست، بهبود کیفیت توان شبکه و همچنین اصلاح شاخصهای قابلیت اطمینان انجام میپذیرد. برای آنکه هر یک از اهداف اشاره شده حاصل گردد، باید بهرهبردار سیستم قدرت به صورت دقیقی تمامی اجزای شبکه همچون بارها و منابع تولید توان و همچنین توپولوژی شبکه را بشناسد. روشهای گوناگون ابتکاری و فرا ابتکاری برای ارائه برنامه مدیریت انرژی پیشنهاد شده است که در سالهای اخیر، استفاده از الگوریتمهای هوشمند بیش از سایر روشها مورد استفاده قرار گرفته است. دقت بالا و عدم نیاز به تخمین نقطه اولیه دقیق، سبب شده است که الگوریتمهای هوشمند برای حل مسئله مدیریت انرژی ریزشبکه مناسب باشند. در این مقاله، از الگوریتم جستجوی فاخته (CSA) برای مدیریت انرژی منابع تجدیدپذیر فتوولتائیک و بادی به همراه منابع تجدیدناپذیر پیل سوختی و میکروتوربین در کنار ذخیرهساز باتری در یک ریزشبکه استاندارد استفاده شده است. عملکرد روش پیشنهادی به ازای شرایط مختلف بار و شدت تابش خورشید در سناریوهای مختلف مورد ارزیابی قرار گرفت. نتایج شبیهسازی در چهار شرایط بهرهبرداری مختلف و با هدف کاهش هزینه انجام پذیرفت و با نتایج الگوریتمهای ژنتیک (GA)، ازدحام ذرات (PSA)، زنبور عسل (BA)، اصلاح شده خفاش (MBA) و جستجوی صاعقه (LSA) مورد مقایسه قرار گرفت و مشخص شد که الگوریتم جستجوی فاخته عملکرد مناسبی در تمامی شرایط بهرهبرداری در کاهش تابع هدف داشته است.
The optimal management distributed generation resources and storage devices in power microgrids is done with various goals such as reducing operating costs, reducing environmental pollution, improving the quality of network power, and also improving reliability indicators. In order to achieve each of the mentioned goals, The operator of the power system must know precisely all the components of the network, such as loads and sources of power generation, as well as the topology of the network. Various innovative and ultra-innovative methods have been proposed to provide energy management program, and in recent years, the use of intelligent algorithms has been used more than other methods. High accuracy and no need to estimate the exact initial point have made smart algorithms suitable for solving the problem of microgrid energy management. In this research, the cuckoo search algorithm is used for the energy management of renewable photovoltaic and wind resources along with non-renewable resources of fuel cell and microturbine along with battery storage in a standard microgrid. The performance of the proposed method was evaluated for different load conditions and solar radiation intensity in different scenarios. The simulation results were carried out in four different operating conditions with the aim of reducing the cost and were compared with the results of genetic algorithms, particle swarm optimization, bee, modified bat, and lightning search. The proposed algorithm of this research That is, the cuckoo search algorithm has performed better in all operating conditions in reducing the objective function.
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