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IEEE Access
Article . 2022 . Peer-reviewed
License: CC BY
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IEEE Access
Article . 2022
Data sources: DOAJ
https://dx.doi.org/10.60692/y9...
Other literature type . 2022
Data sources: Datacite
https://dx.doi.org/10.60692/6j...
Other literature type . 2022
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An Adjustable Robust Economic Energy and Reserve Dispatch Problem Incorporating Large-Scale Wind Farms

مشكلة إرسال طاقة اقتصادية واحتياطية قوية قابلة للتعديل تتضمن مزارع رياح واسعة النطاق
Authors: Hossein Khorramdel; Mohsen Gitizadeh; C. Y. Chung; Muhammad Murtadha Othman; Hassan Haes Alhelou;

An Adjustable Robust Economic Energy and Reserve Dispatch Problem Incorporating Large-Scale Wind Farms

Abstract

L'intégration de parcs éoliens à grande échelle crée une incertitude importante et des défis techniques remarquables pour les systèmes électriques en raison de leur intermittence. Une modélisation complète de la structure de dépendance à l'énergie éolienne est essentielle pour la gestion de l'incertitude dans le fonctionnement optimal des systèmes électriques modernes avec de nombreux parcs éoliens. Cet article présente un cadre d'optimisation robuste et ajustable efficace par lequel la structure de dépendance complexe des parcs éoliens peut être modélisée dans les problèmes de répartition de l'énergie et des réserves. Une modélisation efficace de la structure de dépendance et son intégration dans la génération de vent et la planification de l'expédition des réserves peuvent éviter les incidents de réduction du vent et de délestage. L'approche proposée utilise une copule de vigne canonique comme modèle statistique flexible et approprié pour considérer à la fois les distributions conjointes et conditionnelles de n'importe quel nombre de parcs éoliens. Les résultats de la modélisation de la structure de dépendance canonique suggérée basée sur la copule de la vigne sont ensuite utilisés comme entrées efficaces pour le problème de répartition de l'énergie et des réserves économiques robustes et ajustables présenté. L'approche suggérée est examinée sur le système IEEE 118-bus, et les résultats de simulation démontrent que la méthodologie proposée par une modélisation efficace de la structure de dépendance est efficace et montrent également l'effet du niveau de corrélation de l'énergie éolienne sur le coût total.

La integración de parques eólicos a gran escala crea una incertidumbre significativa y desafíos técnicos notables para los sistemas de energía debido a su intermitencia. El modelado integral de la estructura de dependencia de la energía eólica es esencial para la gestión de la incertidumbre en el funcionamiento óptimo de los sistemas de energía modernos con muchos parques eólicos. Este documento presenta un marco de optimización robusto y ajustable eficiente mediante el cual se puede modelar la compleja estructura de dependencia de los parques eólicos en problemas de despacho de energía y reservas. El modelado eficiente de la estructura de dependencia y su incorporación en la generación eólica y la programación de despachos de reserva pueden evitar incidentes de reducción de viento y de desprendimiento de carga. El enfoque propuesto utiliza una cópula canónica de la vid como un modelo estadístico flexible y apropiado para considerar las distribuciones conjuntas y condicionales de cualquier número de parques eólicos. Los resultados del modelo de estructura de dependencia basado en cópula de vid canónica sugerido se utilizan como insumos eficientes para el problema de despacho de reserva y energía económica robusta ajustable presentado. El enfoque sugerido se examina en el sistema IEEE 118-bus, y los resultados de la simulación demuestran que la metodología propuesta mediante el modelado eficiente de la estructura de dependencia es efectiva y también muestra el efecto del nivel de correlación de la energía eólica en el costo total.

The integration of large-scale wind farms creates significant uncertainty and remarkable technical challenges for power systems due to their intermittency. Comprehensive wind power dependence structure modeling is essential for uncertainty management in the optimal operation of modern power systems with many wind farms. This paper presents an efficient adjustable robust optimization framework by which the complex dependence structure of wind farms can be modeled in energy and reserve dispatch problems. Efficient dependence structure modeling and its incorporation in wind generation and reserve dispatch scheduling can avoid wind curtailment and load shedding incidents. The proposed approach utilizes a canonical vine copula as a flexible and appropriate statistical model to consider both the joint and conditional distributions of any number of wind farms. The results of the suggested canonical vine copula-based dependence structure modeling are then utilized as efficient inputs for the presented adjustable robust economic energy and reserve dispatch problem. The suggested approach is examined on the IEEE 118-bus system, and simulation results demonstrate that the proposed methodology by efficient dependence structure modeling is effective and also show the effect of the wind power correlation level on the total cost.

يخلق تكامل مزارع الرياح واسعة النطاق حالة كبيرة من عدم اليقين وتحديات تقنية ملحوظة لأنظمة الطاقة بسبب تقطعها. تعد النمذجة الشاملة لهيكل الاعتماد على طاقة الرياح ضرورية لإدارة عدم اليقين في التشغيل الأمثل لأنظمة الطاقة الحديثة مع العديد من مزارع الرياح. تقدم هذه الورقة إطار تحسين قوي فعال قابل للتعديل يمكن من خلاله نمذجة هيكل الاعتماد المعقد لمزارع الرياح في مشاكل إرسال الطاقة والاحتياطيات. يمكن لنمذجة هيكل الاعتماد الفعال وإدماجه في توليد الرياح وجدولة إرسال الاحتياطيات تجنب حوادث تقليص الرياح وسفك الأحمال. يستخدم النهج المقترح حبة الكرمة الكنسية كنموذج إحصائي مرن ومناسب للنظر في كل من التوزيعات المشتركة والمشروطة لأي عدد من مزارع الرياح. ثم يتم استخدام نتائج نمذجة هيكل الاعتماد القائم على الكرمة الكنسية المقترحة كمدخلات فعالة لمشكلة الطاقة الاقتصادية القوية القابلة للتعديل وإرسال الاحتياطي. يتم فحص النهج المقترح على نظام IEEE 118 - bus، وتظهر نتائج المحاكاة أن المنهجية المقترحة من خلال نمذجة هيكل الاعتماد الفعال فعالة وتظهر أيضًا تأثير مستوى ارتباط طاقة الرياح على التكلفة الإجمالية.

Keywords

Economic dispatch, Electricity Price and Load Forecasting Methods, robust optimization, FOS: Mechanical engineering, Composite Reliability, Wind Power Generation, Quantum mechanics, Electric power system, Reliability engineering, Canonical vine copula, FOS: Economics and business, Engineering, wind power uncertainty, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Intermittency, Copula (linguistics), Econometrics, Electrical and Electronic Engineering, renewable energy sources, Safety, Risk, Reliability and Quality, Vine copula, Physics, Mathematical optimization, Load Forecasting, Electricity Market Operation and Optimization, Power (physics), Computer science, Mechanical engineering, TK1-9971, Turbulence, Reliability Assessment of Wind Power Generation Systems, Electrical engineering, Physical Sciences, Wind Power Forecasting, Thermodynamics, Electrical engineering. Electronics. Nuclear engineering, Wind power, Robust optimization, Scheduling (production processes), Mathematics, Turbine

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
gold