能源管理系統中用電排程最佳化

Optimal Energy Consumption Scheduling in Energy Management System

林聖凱(Sheng-Kai Lin)

指導教授 ： 陳昭榮

國立臺北科技大學/電資學院/電機工程系所/碩士(2014年)

摘要

配合智慧型電網之建置來推行需量反應計畫，可以減少尖峰負載量、輸電線之壅塞，進而減緩新建電廠與輸電線之壓力，也因為尖峰負載量下降，可以維持系統之供電品質與可靠度。
在需量反應計畫中，用戶可以決定住宅中彈性用電的使用時機，利用能源管理系統(Energy Management System)，及配電公司提供的即時電價資訊(Real-Time Pricing)，來做最佳用電排程使總購電支出最小化。
本文提出一個運用於能源管理系統控制器(Energy Management System Controller)的最佳化演算法，顧客可以決定每個家電的起始與中止時間，以此為限制來做用電最佳排程，目標是達到最小電費支出，可減少顧客因手動排程的不方便與減少等待時間的雙重目標。
本文在系統中加入了電池組，利用低電價時充電；高電價時放電，得到使總電費支出最小化，本文以宿舍用電為案例做系統分析，分析結果可證明，本文提出的田口-基因演算法，可用較基因演算法少的世代數，並得到總購電支出更低的排程，在案例中也顯示，電池與太陽能在系統中確實達到可以節省電費的效果。

關鍵字

需量反應 ； 需量端管理 ； 能源控制器 ； 田口-基因演算法

並列摘要

After the construction of smart grid, implement demand response programs reduce peak loads, congestion in the transmission line, therefore it can alleviate the pressure of new power plants and new power lines. Besides, the reduction of electricity load in the peak time enhance the reliability of the system.
In the demand response program, the residential user can decide the timing of elastic electricity use. Real time pricing information is provided through smart meter by utility company, the user can use it to optimal energy scheduling so that minimize total electricity purchase expenses.
This paper presents an optimize algorithm used in energy controller, if user do not using the automatic energy management controller, The residential user usually using appliance at relatively low price timing, but this decision is penalized by customers electricity contract, make electricity at a higher unit price.
In this paper, the battery pack is added to system that ease the uncertainty of solar power, charge and discharge can also be used to do get lower electricity costs, this paper use dormitory energy consumption as case, results can be proved, proposed Taguchi - genetic algorithms can be used to find the lower total purchase electricity expenditures in fewer generations schedule is also displayed in case, battery and solar energy in the system can indeed achieve electricity savings effect.

並列關鍵字

Demand Response ； Demand-side Management ； Energy Management System ； Hybrid Taguchi-Genetic Algorithm

參考文獻

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