大城区增量配电业务投资利益分配考量与探析
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摘要
为提高大城区增量配电业务投资利益分配能力,促进利益分配均衡,提出一种基于双线性均衡博弈控制的大城区增量配电业务投资利益分配模型,采用Hausman检验方法进行大城区增量配电业务投资利益分配控制,结合内部控制约束方法进行配电业务投资的流产资产和流动负债的相关性分析。结合T检验方法进行配电业务投资利益的显著性特征分析,在演化博弈视角下实现大城区增量配电业务投资利益分配,实现业务投资利益分配均衡。实证分析结果表明,采用该模型进行大城区增量配电业务投资利益分配的稳健性较好。
In order to improve the investment benefit distribution ability of incremental distribution service in urban area and promote benefit distribution equilibrium,a model of investment benefit distribution for incremental distribution service in urban area based on bilinear equilibrium game control is proposed.The Hausman test method is used to control the distribution benefit distribution of incremental distribution business in urban district,and the correlation analysis of abortive assets and current liabilities of distribution business investment is carried out in combination with the internal control constraint method.Based on the analysis of the significant characteristics of investment benefits of distribution business by T-test method,the distribution of investment benefits of incremental distribution services in urban area is realized under the perspective of evolutionary game theory,and the distribution of investment benefits of business investment is balanced.The results of empirical analysis show that the model is more robust for investment benefit allocation of incremental distribution services in urban areas.
In order to improve the investment benefit distribution ability of incremental distribution service in urban area and promote benefit distribution equilibrium,a model of investment benefit distribution for incremental distribution service in urban area based on bilinear equilibrium game control is proposed.The Hausman test method is used to control the distribution benefit distribution of incremental distribution business in urban district,and the correlation analysis of abortive assets and current liabilities of distribution business investment is carried out in combination with the internal control constraint method.Based on the analysis of the significant characteristics of investment benefits of distribution business by T-test method,the distribution of investment benefits of incremental distribution services in urban area is realized under the perspective of evolutionary game theory,and the distribution of investment benefits of business investment is balanced.The results of empirical analysis show that the model is more robust for investment benefit allocation of incremental distribution services in urban areas.
引文
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[2] 侯佳,吴志力,崔凯.放开增量配电投资业务关键问题研究综述[J].电力建设,2017,38(9):127-131.
[3] 马倩,王琛,李扬,等.增量配电业务放开下电网企业投资风险分析[J].电力建设,2017,38(9):139-144.
[4] 任曦骏,王绪利,赵锋.增量配电业务投资风险分析及风险评估模型[J].安徽电力,2018,35(01):58-62.
[5] GOVONI M A,LI H,KOSINSKI J A.Range-Doppler resolution of the linear-FM noise radar waveform[J].IEEE Transactions on Aerospace and Electronic Systems,2013,49(1):658-664.
[6] 张建华,曾博,张玉莹,等.主动配电网规划关键问题与研究展望[J].电工技术学报,2014,29(2):13-23.
[7] RAHMAN A,MUHAMMAH H,SUNGYOUNG L,et al.Rough set-based approaches for discretization:a compact reviews[J].Artificial Intelligence Review,2015,44(2):235-263.
[8] QIAN Y H,ZHANG H,SANG Y,et al.Multigranulation decision-theoretic rough sets[J].International Journal of Approximate Reasoning,2014,55(1):225-237.
[9] SHEN L,SUN G,HUANG Q,et al.Multi-level discriminative dictionary learning with application to large scale image classification[J].IEEE Transactions on Image Processing,2015,24(10):3109-3123.
[10] THIAGARAJAN J J,RAMAMURTHY K N,and SPANIAS A.Learning stable multilevel dictionaries for space representations[J].IEEE Transactions on Neural Networks & Learning Systems,2015,26(9):1913-1926.
[11] JIANG Junzheng,ZHOU Fang.Iterative design of two-dimensional critically sampled MDFT modulated filter banks[J].Signal Processing,2013,93(11):3124-3132.
[12] RAJAPAKAHA N,MADANAYAKE A,and BRUTON LT.2D space-time wave-digital multi-fan filter banks for signals consisting of multiple plane waves[J].Multidimensional Systems and Signal Processing,2014,25(1):17-39.
[13] MAHBOUBI H,MOEZZI K,AGHDAM A G,et al.Distributed deployment algorithms for improved coverage in a network of wireless mobile sensors[J].IEEE Transactions on Industrial Informatics,2014,10(1):163-174.
[14] MAHBOUBI H.Distributed deployment algorithms for efficient coverage in a network of mobile sensors with nonidentical sensing Capabilities[J].IEEE Transactions on Vehicular Technology,2014,63(8):3998-4016.
[15] LIN T Y,SANTOSO H A,and WU K R.Global sensor deployment and local coverage-aware recovery schemes for smart environments[J].IEEE Transactions on Mobile Computing,2015,14(7):1382-1396.