电网技术
電網技術
전망기술
POWER SYSTEM TECHNOLOGY
2013年
10期
2788-2795
,共8页
测量不确定度%直流潮流%电量估计%细菌群体趋药性
測量不確定度%直流潮流%電量估計%細菌群體趨藥性
측량불학정도%직류조류%전량고계%세균군체추약성
measurement uncertainty%DC power flow%power energy estimation%bacterial colony chemotaxis (BCC)
随着智能电网的发展,电力企业对关口日电量及基于关口日电量的各种统计数据的准确性要求不断提高,为保证电能计量系统日电量的正确性,快速定位错误数据,提出一种基于测量不确定度理论,使用优化算法来对日电量进行估计的方法。首先,介绍了测量不确定度理论及其在电力系统中的应用,分析其用于电力系统的估计辨识的优势;其次,在给出的直流电量潮流计算模型和测量不确定度理论基础上确定了日电量的估计思路;最后,给出基于测量不确定度的日电量的评价函数,从而建立了基于测量不确定度的电量优化估计模型,给出了使用细菌群体趋药性(bacterial colony chemotaxis,BCC)优化算法对日电量进行估计的步骤。通过IEEE39和IEEE118节点系统仿真算例验证了所提方法的有效性和可行性。
隨著智能電網的髮展,電力企業對關口日電量及基于關口日電量的各種統計數據的準確性要求不斷提高,為保證電能計量繫統日電量的正確性,快速定位錯誤數據,提齣一種基于測量不確定度理論,使用優化算法來對日電量進行估計的方法。首先,介紹瞭測量不確定度理論及其在電力繫統中的應用,分析其用于電力繫統的估計辨識的優勢;其次,在給齣的直流電量潮流計算模型和測量不確定度理論基礎上確定瞭日電量的估計思路;最後,給齣基于測量不確定度的日電量的評價函數,從而建立瞭基于測量不確定度的電量優化估計模型,給齣瞭使用細菌群體趨藥性(bacterial colony chemotaxis,BCC)優化算法對日電量進行估計的步驟。通過IEEE39和IEEE118節點繫統倣真算例驗證瞭所提方法的有效性和可行性。
수착지능전망적발전,전력기업대관구일전량급기우관구일전량적각충통계수거적준학성요구불단제고,위보증전능계량계통일전량적정학성,쾌속정위착오수거,제출일충기우측량불학정도이론,사용우화산법래대일전량진행고계적방법。수선,개소료측량불학정도이론급기재전력계통중적응용,분석기용우전력계통적고계변식적우세;기차,재급출적직류전량조류계산모형화측량불학정도이론기출상학정료일전량적고계사로;최후,급출기우측량불학정도적일전량적평개함수,종이건립료기우측량불학정도적전량우화고계모형,급출료사용세균군체추약성(bacterial colony chemotaxis,BCC)우화산법대일전량진행고계적보취。통과IEEE39화IEEE118절점계통방진산례험증료소제방법적유효성화가행성。
With the development of smart grids the requirements of electric power enterprises to the accuracy of daily gateway electricity quantity and that of various statistical data based on daily gateway electricity quantity are ever-enhanced. To ensure the correctness of daily electricity quantity measured by electric energy metering system and rapidly locate the wrong data, based on the theory of measurement uncertainty a method to estimate daily electricity quantity by optimization algorithm is proposed. Firstly, the theory of measurement uncertainty and its application in power grids are presented, and the superiority of applying it to power grid estimation and identification is analyzed;secondly, based on the given calculation model for DC electricity quantity flow and the theory of measurement uncertainty the thinking to estimate the daily electricity quantity is decided;finally, the measurement uncertainty based evaluation function of daily electricity quantity is given, thus a measurement uncertainty based electricity quantity optimization model is built and the procedures of estimating daily electricity quantity by bacterial colony chemotaxis (BCC) optimization algorithm are given. The validity and feasibility of the proposed method are verified by simulation results of IEEE 39-bus system and IEEE 118-bus system.