ارزیابی جریان انرژی احتمالی
ترجمه نشده

ارزیابی جریان انرژی احتمالی

عنوان فارسی مقاله: ارزیابی جریان انرژی احتمالی و ممکن ترکیبی برای سیستم های حامل چند انرژی
عنوان انگلیسی مقاله: Hybrid Possibilistic-Probabilistic Energy Flow Assessment for Multi-Energy Carrier Systems
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی انرژی
گرایش های تحصیلی مرتبط: سیستم های انرژی
کلمات کلیدی فارسی: حامل چند انرژی، عدم قطعیت ممکن، عدم قطعیت احتمالی، جریان انرژی نامعلوم
کلمات کلیدی انگلیسی: Multi-energy carrier, possibilistic uncertainty, probabilistic uncertainty, uncertain energy flow
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2943998
دانشگاه: College of Information Science and Engineering, Northeastern University, Shenyang 110004, China
صفحات مقاله انگلیسی: 12
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: دارد
کد محصول: E14086
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

ABSTRACT

I. INTRODUCTION

II. SYSTEM MODELING

III. UNCERTAINTY IN MULTI-ENERGY FLOW PROBLEM

IV. HYBRID POSSIBILISTIC-PROBABILISTIC UNCERTAINTY ALGORITHM

V. CASE STUDIES

VI. CONCLUSION

REFERENCES

بخشی از مقاله (انگلیسی)

ABSTRACT

The uncertainty is a pivotal problem in Multi-Energy Carrier (MEC) systems, which leads to the strong demand of reasonable tools to evaluate uncertainties. When both possibilistic and probabilistic uncertainties exist in the real MEC systems, traditional possibilistic or probabilistic methods are no more suitable to be applied. Therefore, this paper proposes a hybrid possibilistic-probabilistic energy flow assessment method to evaluate these uncertainties. Firstly, to build a more precise uncertain model, the probabilistic and possibilistic uncertainties are respectively modeled by considering different uncertainties of sources, networks and loads of MEC systems, and the correlations among wind generation and energy loads. Then, the product t-norms of the extension principle plus α-cut method is firstly implemented in processing fuzzy energy flow, which can reduce overestimation compared with the sole α-cut method. Next, on the basis of Dempster-Shafer evidence theory, the hybrid possibilistic-probabilistic energy flow assessment approach is presented. Finally, two cases are carried out to verify the effectiveness and practicability of the proposed method.

INTRODUCTION

Currently, with increasingly global energy crisis and intricate interactions among electricity, gas and heat networks, the development of Multi-Energy Carrier (MEC) systems draws extensive attention worldwide. Meanwhile, Renewable Energy Resources (RESs), such as wind power and photovoltaics, predominate in the sustainable transformation of energy systems, which also devotes to establishing complementary utilization of multiple energy carriers [1], [2]. In the numerous investigation about MEC systems, the uncertainty assessment is a critical issue. As there are various uncertainties (e,g., the variability and intermittency of the RESs [3], [4], stochastic fluctuations in energy loads [5]) in MEC systems, a reasonable tool to evaluate the uncertainties is indispensable to quantify and control the operational and planning risks of MEC systems. Deterministic energy flow calculation provides available measures for uncertain energy flow calculation, and it lays the foundation for planning analysis and optimal operation of MEC systems. The steady-state energy flow of electrical, gas and heat network is firstly investigated on the basis of Newton-Raphson technique considering interactions among different networks [6]. Due to the sensitivity of Newton method to initial guesses, a fast decomposing strategy is proposed to solve energy flow in large scale MEC systems [7].