دانلود مقاله الگوریتم نورودینامیک برای زمانبندی انرژی در شبکه توزیع ریزشبکه
چکیده
مقدمه
نمادها و مقدمات
مدلسازی ریاضی
بازی برنامه ریزی انرژی برای شبکه توزیع ریزشبکه
مثال شبیه سازی
نتیجه گیری
منابع
Abstract
Introduction
Notations and Preliminaries
Mathmatic Modelling
Energy Scheduling Game for the Microgrid Distribution Network
Simulation Example
Conclusion
References
چکیده
در این مقاله، یک بازی استراتژی زمانبندی انرژی رقابتی ریزشبکه‌های N (MGs) در داخل یک شبکه توزیع شده در نظر گرفته شده است. هدف هر ریزشبکه (MG) به حداکثر رساندن سود خود در چارچوب بازی غیرهمکاری است. استراتژی‌سازی هر MG به محدودیت‌های تجهیزات آن، منابع انرژی کل همه MGها و تعادل انرژی عرضه‌ها و تقاضاها بستگی دارد. برای حل مسئله مورد بحث در بالا، یک بازی غیرهمکاری با محدودیت های جفت شده خطی و یک الگوریتم نورودینامیک توزیع شده برای جستجوی تعادل نش تعمیم یافته (GNE) پیشنهاد شده است. علاوه بر این، درستی و همگرایی الگوریتم پیشنهادی به تفصیل تحلیل می‌شود. اثربخشی و امکان سنجی روش پیشنهادی نیز از طریق مثال شبیه سازی نشان داده شده است.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
In this paper, a competitive energy scheduling strategy game of N-microgrids (MGs) inside a distributed network is considered. Each microgrid (MG) aims to maximize its profit under the noncooperative game frame. The strategy-making of each MG depends on its equipment constraints, the aggregate energy supplies of all MGs, and the energy balance of supplies and demands. To solve above discussed problem, a noncooperative game with linear coupled constraints and a distributed neurodynamic algorithm are proposed to seek the generalized Nash equilibrium (GNE). Besides, the correctness and convergence of the proposed algorithm are analyzed in detail. The effectiveness and feasibility of the proposed method are also illustrated via the simulation example.
Introduction
Though the advance of industry forces rapid economic development, it also brings many challenges to the environment and resources. To improve the energy scheduling between traditional and renewable energy, the construction of the MG becomes vitally significant [1]. It is crucial to develop a safe, stable and efficient modern power system, in which the stability, flexibility, and the balance of the supply and demand side are guaranteed [2].
Recently, energy management has been investigated widespreadly to allocate energy optimally and construct a safe and stable power grid. A smart energy management system (EMS) coordinates the working of distributed generators and energy storage system (ESS and achieves the maximum benefits of the MG system [3,4]. Typically, the control mode of EMS is mainly centralized control. To minimize the emission cost of greenhouse gases, energy costs, and maximize the output of renewable power, a centralized method has been used to coordinate the energy management between the MG and the main power grid [5]. However, the centralized control can not provide a formidable computing ability to deal with a volume of data and suffers from single-point fault and privacy disclosure.
Conclusion
In this paper, we considered a microgrid distribution network under the noncooperative game frame, which is an N-MGs competitive game. To maximize its profits, each MG should not only consider its strategy constraint but also the aggregate energy supplies of all MGs and the given energy demand of the users. Hence, the game with linear coupled constraints and distributed neurodynamic algorithm were proposed to seek the GNE. The correctness and convergence of the proposed algorithm were analyzed and the simulation example illustrated the effectiveness and feasibility of the proposed method.