Search

In consideration of the fuzziness and the uncertainty in decision information, this paper proposes a three-parameter interval grey linguistic variable decision-making method based on projection model and prospect theory. First, some properties are defined, such as the concepts and the relational calculation rules of grey additive linguistic variables. Second, considering the decision maker’s subjective information and the attribute’s objective information, a mathematical model is constructed to obtain the attribute weights. Third, based on the new definitions of the prospect values, the comprehensive prospect values are calculated viewing dynamic alternatives as the reference point, and a ranking of alternatives is obtained. At last, an illustrative example is taken in the present study to make the proposed method comprehensible.

In consideration of the interaction among attributes and the uncertainty in the decision information, this paper proposes an intuitionistic trapezoidal fuzzy random decision making method based on Mahalanobis-Taguchi Gram-Schmidt and evidence theory. Firstly, by the acquired intuitionistic trapezoidal fuzzy samples in different periods of the decision making process, the unknown parameters of entire intuitionistic trapezoidal fuzzy populations with known distribution pattern are estimated, and then an intuitionistic trapezoidal fuzzy random matrix is obtained. Secondly, an intuitionistic fuzzy decision matrix with expectation and variance is established, and then a new score function is defined to transform a normalized expectation intuitionistic fuzzy number matrix into a score function matrix. Finally, Mahalanobis-Taguchi Gram-Schmidt and improved evidence theory are combined to deal with the score function matrix, and a ranking of alternatives is obtained according to the belief function value. An illustrative example is taken in the present study to make the proposed method comprehensible.

This paper presents the concept of three-parameter interval grey linguistic variable, which combines three-parameter interval grey numbers with grey linguistic variables. Firstly, basic definitions and new laws are given. Secondly, considering the attributes interdependency, this paper utilises the fuzzy integral theory to construct a grey fuzzy integral correlation degree decision-making model under three-parameter interval grey linguistic variable environment. To solve this model, the Mobius transformation coefficients based on weights and interaction degrees are defined to calculate two-order additive fuzzy measures. Then the maximum projection models are used to calculate the weights, and the interaction relations and interaction degrees are determined by decision makers. Subsequently, the grey fuzzy integral correlation degrees of alternatives are calculated by precise function transformation, grey correlation degree and fuzzy measures. At last, an illustrative example has been taken to demonstrate the validity and feasibility of the proposed method.

With rapid speed on electricity using and increasing in renewable energy, more and more research pay attention on distribution grid planning. For the drawbacks of existing research, this paper proposes a new risky group decision-making method for distribution grid planning. Firstly, a mixing index system with qualitative and quantitative indices is built. On the basis of considering the fuzziness of language evaluation, choose cloud model to realize “quantitative to qualitative” transformation and construct interval numbers decision matrices according to the “3En” principle. An m-dimensional interval numbers decision vector is regarded as super cuboids in m-dimensional attributes space, using two-level orthogonal experiment to arrange points uniformly and dispersedly. The numbers of points are assured by testing numbers of two-level orthogonal arrays and these points compose of distribution points set to stand for decision-making project. In order to eliminate the influence of correlation among indices, Mahalanobis distance is used to calculate the distance from each solutions to others which means that dynamic solutions are viewed as the reference. Secondly, due to the decision-maker’s attitude can affect the results, this paper defines the prospect value function based on SNR which is from Mahalanobis-Taguchi system and attains the comprehensive prospect value of each program as well as the order. At last, the validity and reliability of this method is illustrated by examples which prove the method is more valuable and superiority than the other.

Based on association rules, this article proposed a method for intelligent recommendation of power supply mode, which helps decision-makers in the selection of many schemes. Firstly, a history database which includes the forecasting models and correlative factors was first built and association rule mining was conducted; then combined with the correlative factors in the designated area, the criteria matching in the rules mined were carried out with CBR technique; finally automatic recommendation of the power supply modes was achieved under the given conditions. By application of an example, it is demonstrated that the proposed method can not only automatically analyze the applicability of power supply modes and the intrinsic relationship between correlative factors but also provide, to some extent, theoretical basis for selection of power supply modes and practical utility for urban distribution network planning.

Energy structure reform is the common choice of all countries to deal with climate change and environmental problems. Pumped-storage power station (PPS) will play an important role in the green and low-carbon energy era of “source-grid-load-storage” synergy and multi-energy complementary optimization. In this context, this paper puts forward a PPS selection evaluation index system and combination evaluation model for energy internet. First of all, on the basis of the construction conditions of traditional PPS, considering the multi-energy complementary demand of energy internet, a three-dimensional evaluation index system of “hydrology & geological conditions”, “construction conditions” and “energy structure demand” has been established. Secondly, concepts such as degree of center cohesion, similarity threshold and core method set are introduced to construct a cycle elimination mechanism and eliminate the edge single evaluation method (SEM) to improve the scientificity of combination evaluation. Site selection combination evaluation of PPS based on cycle elimination is constructed, and effectiveness measure test of site selection combination evaluation method is defined. Finally, PPS in North China is taken as an example to verify the effectiveness of the model and the sensitivity analysis is carried out. The research shows that the effectiveness of the combination evaluation method is not only determined by the mechanism of the method itself, but also affected by the consistency of the SEM set, and the cycle elimination mechanism can improve the effectiveness of the combination evaluation method. The evaluation index system, site selection model based on cycle elimination and effectiveness measure are constructed in this paper has high feasibility. The classification characteristics of PPS sites are proposed for the first time, and PPS sites are divided into seven types according to three index dimensions: it provides the basis for differentiated decision making of PPS site selection.

The cost of materials is the largest proportion of a construction project’s total budget. If the materials cannot be delivered to the construction site on time, completely and with acceptable quality, the project’s duration and cost will be greatly affected. Based on the generalized project risk element transmission theory and system dynamics, a system dynamics model was developed to capture dynamics of procurement risk elements transmission during construction projects and how various procurement risk elements affect the project’s duration and cost by simulation. In this paper, procurement risk element is considered as the uncertain factors in procurement. Based on these results, it is concluded that the developed model can provide important information for risk managers and project managers addressing procurement risk.

Advanced grid technology represented by smart grid and energy internet is the core feature of the next-generation power grid. The next-generation power grid will be a large-scale cyber-physical system (CPS), which will have a higher level of risk management due to its flexibility in sensing and control. This paper explains the methods and results of a study on grid CPS’s behavior after risk. Firstly, a behavior model based on hybrid automata is built to simulate grid CPS’s risk decisions. Then, a GCPS risk transfer model based on cooperative game theory is built. The model allows decisions to ignore complex network structures. On this basis, a modified applicant-proposing algorithm to achieve risk optimum is proposed. The risk management model proposed in this paper can provide references for power generation and transmission decision after risk as well as risk aversion, an empirical study in north China verifies its validity.

With the rapid development of the energy internet and the deepening of the electric power reform, the traditional marketing mode of electric power does not apply to most of electric power enterprises, so must seek a breakthrough, however, in the face of increasingly complex marketing information, how to make a quick, reasonable transformation, makes the electric power marketing competitiveness assessment more accurate and objective becomes a big problem. In this paper, cloud model and TOPSIS method is proposed. Firstly, build the electric power marketing competitiveness evaluation index system. Then utilize the cloud model to transform the qualitative evaluation of the marketing data into quantitative values and use the entropy weight method to weaken the subjective factors of evaluation index weight. Finally, by TOPSIS method the closeness degrees of alternatives are obtained. This method provides a novel solution for the electric power marketing competitiveness evaluation. Through the case analysis the effectiveness and feasibility of this model are verified.