發(fā)布時間：2018-03-09 06:06

  本文選題：電梯群控　切入點：不確定交通流　出處：《湖北工業(yè)大學》2017年碩士論文　論文類型：學位論文

【摘要】：隨著工業(yè)現(xiàn)代化不斷擴大和人們生活水平不斷提高,電梯節(jié)能及電梯群控系統(tǒng)技術(shù)逐漸成為建筑節(jié)能降耗的重要部分。保證乘客的基本乘梯指標的同時降低整體能耗已經(jīng)成為電梯群控技術(shù)重要方向。本文的主要內(nèi)容是解決在裝有電能回饋設備的電梯機房中及不確定交通流條件下,實現(xiàn)面向節(jié)能的電梯群控調(diào)度問題。論文以電梯能耗代價和時間代價為分析基礎,以不確定交通流自動識別和轉(zhuǎn)換為核心。具體在如下幾方面開展研究:一、針對不確定交通流條件下乘客到達率未知的問題,本文從電梯功率、電梯能量回饋功率與轎廂內(nèi)人數(shù)關(guān)系入手,利用統(tǒng)計學規(guī)律分析和確定交通流。同時分析單臺電梯實際運行狀態(tài),從中獲取電梯群能耗代價的組成部分,并推導出在裝有電能回饋設備的條件下電梯群的能耗代價函數(shù)。最后在考慮電梯能耗代價的同時,給出電梯時間代價問題和做相關(guān)的分析。二、在確定交通流模式下論文分析并提出一種基于蟻群算法的電梯群調(diào)度策略。首先給出蟻群優(yōu)化算法的基本概念和根據(jù)概率統(tǒng)計方法得到的電梯群調(diào)度模型,然后結(jié)合兩者給出相應的調(diào)度算法并給出模型約束條件,在保證有序、優(yōu)先級調(diào)度和穩(wěn)定的前提下,給出相應的仿真模型并對算法進行仿真驗證。三、針對不確定交通流模式下的面向電梯群控調(diào)度問題,利用電梯能量回饋器參數(shù)、電梯參數(shù)和樓層參數(shù)等信息,構(gòu)建了一個新的電梯群控調(diào)度模型。介紹了基本粒子群算法和大雁-粒子群算法的基本概念,之后給出在不確定交通流模式下的電梯群控調(diào)度模型,并且針對電梯群控系統(tǒng)能耗代價和時間代價耦合的問題,提出新的解耦方案,最終通過仿真測試。四、根據(jù)本文中的理論和模型數(shù)據(jù),搭建了一個面向節(jié)能的電梯群控系統(tǒng)仿真測試平臺,并對文章提出的算法的性能進行了相關(guān)的驗證和測試。同時利用實際的電梯能力回饋器、電梯傳感器產(chǎn)生的數(shù)據(jù),設計不同群控調(diào)度算法程序,并通過了相關(guān)的測試,對未來設計實際可行的群控策略提供有效的支持。
[Abstract]:With the continuous expansion of industrial modernization and the continuous improvement of people's living standards, The technology of elevator energy saving and elevator group control system has gradually become an important part of building energy saving and consumption reduction. It has become an important direction of elevator group control technology to ensure the passenger's basic ladder index and reduce the overall energy consumption. Capacity is solved in the elevator room equipped with electric energy feedback equipment and under the condition of uncertain traffic flow, Based on the analysis of elevator energy cost and time cost, this paper focuses on the automatic identification and conversion of uncertain traffic flow. The following aspects of the research are carried out: 1. In order to solve the problem of unknown passenger arrival rate under uncertain traffic flow, this paper starts with the relationship between elevator power, elevator energy feedback power and the number of people in the car. The traffic flow is analyzed and determined by statistical law, and the actual running state of a single elevator is analyzed, from which the components of the energy consumption cost of the elevator group are obtained. The energy cost function of elevator group under the condition of electric energy feedback equipment is deduced. Finally, the time cost of elevator is given and the related analysis is made. This paper analyzes and proposes an elevator colony scheduling strategy based on ant colony algorithm under determined traffic flow mode. Firstly, the basic concept of ant colony optimization algorithm and the elevator colony scheduling model based on probability and statistics method are given. Then, the corresponding scheduling algorithms are given and the model constraints are given. On the premise of ensuring order, priority scheduling and stability, the corresponding simulation model is given and the algorithm is verified by simulation. In view of the elevator group control scheduling problem in uncertain traffic flow mode, the elevator energy feedback parameters, elevator parameters and floor parameters are used. In this paper, a new elevator group control scheduling model is constructed, and the basic concepts of the basic particle swarm optimization algorithm and the goose particle swarm optimization algorithm are introduced, and then the elevator group control scheduling model under the uncertain traffic flow mode is given. And aiming at the coupling of energy cost and time cost of elevator group control system, a new decoupling scheme is proposed, which finally passes the simulation test. Fourthly, according to the theory and model data in this paper, A simulation test platform for energy saving elevator group control system is built, and the performance of the algorithm proposed in this paper is verified and tested. At the same time, using the actual elevator capability feedback device, the data generated by elevator sensor are used. Different group control scheduling algorithms are designed, and relevant tests are carried out to provide effective support for the design of practical and feasible group control strategies in the future.
【學位授予單位】：湖北工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP18;TU857

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