本文選題：峰谷分時(shí)電價(jià) + 多時(shí)段響應(yīng)�。� 參考：《重慶大學(xué)》2014年碩士論文

【摘要】：立足于需求響應(yīng)的初衷—提高系統(tǒng)可靠性與降低市場(chǎng)交易風(fēng)險(xiǎn)，研究計(jì)及系統(tǒng)可靠性與收益風(fēng)險(xiǎn)的峰谷分時(shí)電價(jià)模型，對(duì)于切實(shí)保證電力系統(tǒng)的供電可靠性和電網(wǎng)經(jīng)營(yíng)企業(yè)的收益，并提高社會(huì)經(jīng)濟(jì)效益具有重要的現(xiàn)實(shí)意義。本文對(duì)峰谷分時(shí)電價(jià)制定的基礎(chǔ)、計(jì)及因素與定價(jià)優(yōu)化模型進(jìn)行如下研究： ①用戶的電價(jià)響應(yīng)評(píng)估與峰谷時(shí)段劃分是峰谷分時(shí)電價(jià)制定的基礎(chǔ)。目前，鮮有文獻(xiàn)給出電量電價(jià)彈性矩陣的解析求解方法，且現(xiàn)有的統(tǒng)計(jì)方法難以體現(xiàn)不同負(fù)荷水平下彈性需求的差異與時(shí)段之間的相互影響。為此，，本文基于電力供給與電力彈性需求的平衡關(guān)系及用戶的多時(shí)段電價(jià)響應(yīng)，推導(dǎo)峰谷分時(shí)電價(jià)下電量電價(jià)彈性矩陣及解析求解方法，準(zhǔn)確、全面地刻畫用戶對(duì)電價(jià)變化的響應(yīng)過程，并在算例中分析自彈性系數(shù)與交叉彈性系數(shù)的數(shù)字特征。根據(jù)半梯形隸屬函數(shù)，采用基于F等價(jià)矩陣模糊聚類進(jìn)行峰谷時(shí)段劃分，并依據(jù)電價(jià)施行的需要進(jìn)行時(shí)段修正。通過算例對(duì)比，表明該方法簡(jiǎn)單，且能較好地反映各負(fù)荷點(diǎn)的峰谷特性。 ②電網(wǎng)經(jīng)營(yíng)企業(yè)的收益風(fēng)險(xiǎn)與系統(tǒng)可靠性是峰谷分時(shí)電價(jià)制定須計(jì)及的重要因素。采用多時(shí)段潮流計(jì)算線路損耗及根據(jù)我國(guó)“廠網(wǎng)分開”的市場(chǎng)背景，確定電網(wǎng)經(jīng)營(yíng)企業(yè)需承擔(dān)的線損成本；通過電力市場(chǎng)風(fēng)險(xiǎn)分析，基于現(xiàn)貨市場(chǎng)電價(jià)與負(fù)荷的函數(shù)關(guān)系，提出計(jì)及線損成本與購(gòu)電風(fēng)險(xiǎn)的電網(wǎng)經(jīng)營(yíng)企業(yè)收益模型。算例中分析了線損成本與購(gòu)電風(fēng)險(xiǎn)對(duì)電網(wǎng)經(jīng)營(yíng)企業(yè)收益的影響，表明電價(jià)的制定應(yīng)充分考慮線損成本與購(gòu)電風(fēng)險(xiǎn)。大電網(wǎng)可靠性評(píng)估非常復(fù)雜、耗時(shí)，采用三次樣條插值建立系統(tǒng)可靠性隨負(fù)荷變化的函數(shù)關(guān)系模型，簡(jiǎn)化峰谷分時(shí)電價(jià)定價(jià)優(yōu)化模型的求解過程。 ③立足需求響應(yīng)的初衷，從提高系統(tǒng)可靠性與降低市場(chǎng)交易風(fēng)險(xiǎn)出發(fā)，以計(jì)及線損成本與購(gòu)電風(fēng)險(xiǎn)的電網(wǎng)經(jīng)營(yíng)企業(yè)收益最大化為目標(biāo)函數(shù)，考慮可靠性約束、用戶利益及其電量調(diào)整能力等，建立峰谷分時(shí)電價(jià)的定價(jià)優(yōu)化模型，并采用基于系統(tǒng)可靠性與負(fù)荷的三次樣條函數(shù)關(guān)系的自適應(yīng)遺傳算法求解模型。算例表明，該電價(jià)模型通過激勵(lì)用戶積極參與電價(jià)響應(yīng)，采用電價(jià)調(diào)節(jié)即可達(dá)到提高供電可靠性、減少用戶停電損失以及降低企業(yè)收益風(fēng)險(xiǎn)的目的。此外，不同的可靠性的約束條件會(huì)影響模型的優(yōu)化結(jié)果，并隨著用戶需求彈性的減小，電價(jià)的調(diào)整力度逐漸增大，才能保證用戶所期望的供電可靠性。
[Abstract]:Based on the original intention of demand response-to improve system reliability and reduce market transaction risk, the peak-valley time-sharing pricing model considering system reliability and revenue risk is studied. It is of great practical significance to ensure the reliability of power supply and the income of power grid management enterprises, and to improve the social and economic benefits. In this paper, the basis, factors and pricing optimization model of peak-valley time-sharing pricing are studied as follows: The pricing response evaluation and peak-valley time division are the basis of peak-valley time-sharing pricing. At present, there are few literatures on the analytical solution of the electricity price elasticity matrix, and the existing statistical methods are difficult to reflect the interaction between the elastic demand and the period of time under different load levels. Therefore, based on the balance between power supply and elastic demand of power and the price response of customers in multiple time periods, the elastic matrix and analytical solution of electricity price under time-sharing price of peak and valley are derived, and the method is accurate. The response process of the user to the change of electricity price is described comprehensively, and the numerical characteristics of the self-elastic coefficient and the cross-elastic coefficient are analyzed in a numerical example. According to the semi-trapezoidal membership function, the peak-valley period is divided by fuzzy clustering based on F equivalent matrix, and the time period is modified according to the demand of electricity price implementation. The comparison of examples shows that the method is simple and can well reflect the peak and valley characteristics of each load point. The profit risk and system reliability of power grid management enterprises are the important factors to be taken into account in the pricing of peak and valley time-sharing electricity. This paper adopts multi-period power flow to calculate line loss and according to the market background of "separation of power plant and power network" in our country, determines the line loss cost to be borne by power network management enterprises, and through power market risk analysis, based on the functional relationship between electricity price and load in spot market, This paper presents a revenue model of power grid enterprises considering the cost of line loss and the risk of purchasing electricity. The influence of line loss cost and power purchase risk on the income of power grid management enterprises is analyzed, which indicates that the line loss cost and power purchase risk should be fully taken into account in the formulation of electricity price. The reliability evaluation of large power grid is very complex and time-consuming. The cubic spline interpolation is used to establish the functional model of system reliability varying with load, which simplifies the solution process of peak-valley time-sharing pricing optimization model. (3) based on the original intention of demand response, starting from improving system reliability and reducing market transaction risk, taking line loss cost and power purchase risk as objective function, considering reliability constraint. The pricing optimization model of peak-valley time-sharing price is established, and the adaptive genetic algorithm based on cubic spline function relationship between system reliability and load is used to solve the model. The example shows that the electricity price model can improve the reliability of power supply, reduce the loss of power outage and reduce the risk of enterprise income by encouraging users to actively participate in the price response. In addition, different reliability constraints will affect the optimization results of the model, and with the decrease of demand elasticity, the adjustment of electricity price will gradually increase, which can ensure the reliability of power supply expected by users.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F426.61;F726

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