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The aim of this paper is to review the current situation and existing problem, establish investment benefits evaluation indicator system and introduce synthetic approach degree containing Hamming approach degree, Euclid approach degree and gray correlation degree to improve the shortage of Euclidean distance in traditional TOPSIS method, and the evaluation result is strengthened by multiplication rule. This paper aims to solve the distribution network investment decision-making problem and construct a comprehensive distribution network investment benefit indicator system, which is more suitable for China distribution network characteristics.

This study develops improved TOPSIS methods for decision maker in the power distribution network market and uses an example to prove its effectiveness and superiority in practice which can realize the combination of theory and practice.

The research shows that the investment evaluation indicator system built in present paper covers more investment benefit influencing factors (such as qualified rate of trunk cross-section, pass rate of N-1 lines), and the evaluation result obtained by improved TOPSIS method is more efficient and persuasive.

The study can help investors evaluate distribution network project more efficient, and make contribution to the choice of distribution cases with similar investment benefits.

There are thousands of areas excluded from using electrical energy in China. It is mainly because that these places, which are away from towns, have the characteristics of scattered living and low-power consumption and are difficult to construct the power grid. The utilization of energy in remote areas could improve the level of education and quality of life for people living in there, which has great social significance. However, how to choose the optimal power generation model quantitatively according to local energy advantages is a difficult problem.

To carry out a better assessment of the energy benefits of Chinese rural areas to assist the decision-making of energy utilization project, this paper takes Sunan Yugu Autonomous County in Gansu Province as an example. Four feasible energy utilization scenarios are proposed by analyzing its geographical conditions and re-source advantage, respectively, are photovoltaic power generation, biomass power generation, wind power generation and power grid extension. Based on the above scenarios, the evaluation index system of comprehensive utilization of energy in remote areas is constructed, and the comprehensive benefit of each model is evaluated by adopting entropy-based fuzzy comprehensive evaluation model.

Evaluation results show that the comprehensive benefits of photovoltaic power generation is the best, followed by power grid extension. Thus, preference should be given to the two models in the energy utilization in Sunan County. This evaluation model can provide a scientific reference for the selection decision-making of energy utilization project, which is helpful to provide the feasibility and efficiency of the construction of energy utilization project.

The authors construct the comprehensive benefit evaluation index system and evaluate the comprehensive benefits of different scenarios are by using entropy - fuzzy comprehensive evaluation model. Then the qualitative problem can be analyzed quantitatively. The purpose of this study is to support the decision-making of energy investment. Simultaneously, the paper also has some practical significance in improving the credibility of the government and the quality of local people’s life.

To improve power system peak dispatching ability, connecting energy-storage device such as electric vehicle (EV) and regenerative electric heater (REH) to power grid is a good choice.

This paper establishes a multi-energy combined peak dispatching system MCPDS which includes EV, REH and wind power. The matter-element extension model based on improved variable weight theory is applied to evaluate MCPDS synthetic benefit.

The research shows that the MCPDS established in this paper performs excellently in security benefit, economic benefit, social benefit and environmental benefit.

With the assistance of energy storage devices such as EV and REH, the electrical system peak dispatching ability and power system operation efficiency has improved. More devices with energy-storage ability should be introduced into electrical power system to improve its synthetic benefit.

To combine the forecasting by single method using influence information fully, other than regular combined methods only focusing on historical forecasting errors.

To combine the single methods based on the analysis of improved gray correlation, with more related information being considered to enhance the price forecasting precision, such as the trend of the prices, the historical forecasting errors, and the temporal influence factors on prices.

A case of PJM market of USA shows that the proposed method has better performance than any other combined methods, and all single models as well.

The combined performance depends on the forecasting precision of single methods, and the correlation between the single methods, as well as the number of single method that to be combined.

It is a novel idea for combined method to forecasting the time series data, such as electricity prices, electric power loads.

The proposed method considers all the following factors: the similarity between the trends of the single forecasting, the errors of the single models and the temporal influence.

The purpose of this paper is to improve the accuracy of short time load forecasting to ensure the economical and safe operation of power systems. The traditional neural network applied in time series like load forecasting, easily plunges into local optimum and has a complicated learning process, leading to relatively slow calculating speed. On the basis of existing literature, the authors carried out studies in an effort to optimize a new recurrent neural network by wavelet analysis to solve the previous problems.

The main technique the authors applied is referred to as echo state network (ESN). Detailed information has been acquired by the authors using wavelet analysis. After obtaining more information from original time series, different reservoirs can be built for each subsequence. The proposed method is tested by using hourly electricity load data from a southern city in China. In addition, some traditional methods are also applied for the same task, as contrast.

The experiment has led the authors to believe that the optimized model is encouraging and performs better. Compared with standard ESN, BP network and SVM, the experimental results indicate that WS‐ESN improves the prediction accuracy and has less computing consumption.

The paper develops a new method for short time load forecasting. Wavelet decomposition is employed to pre‐process the original load data. The approximate part associated with low frequencies and several detailed parts associated with high frequencies components give expression to different information from original data. According to this, suitable ESN is chosen for each sub‐sequence, respectively. Therefore, the model combining the advantages of both ESN and wavelet analysis improves the result for short time load forecasting, and can be applied to other time series problem.

Technology innovation capability is a main driver in improving a country’s industrial competitiveness. Development prospects and development speed are strongly dependent on industry innovation capability. Therefore, how to effectively and correctly evaluate the innovation capability of industry is of great importance. On the basis of previous research, this paper establishes an index system for evaluating the technology innovation capability of China’s high-tech industries. The index is characterized by the objective evaluation of objects with measurable indexes. The fuzzy Borda method uses precise digital methods to handle fuzzy evaluation objects; therefore, more scientific and pragmatic quantitative criteria are obtained with qualitative and quantitative evaluation results. This paper is the first attempt to apply the fuzzy Borda combination method to high-tech industry innovation capability evaluation. We establish a fuzzy Borda combination model based on four kinds of single evaluation models. By making a combination evaluation, the disadvantages of a single evaluation method are avoided. In the end, based on the fuzzy Borda combination evaluation model, the real technology innovation data of 2013 is analyzed and the innovation capability of individual industry is ranked, which will provide useful guidance for decision-making administrators.