With the advent of the electric power big data era, semantic interoperability and interconnection of power data have received extensive attention. Knowledge graph technology is a new method describing the complex relationships between concepts and entities in the objective world, which is widely concerned because of its robust knowledge inference ability. Especially with the proliferation of measurement devices and exponential growth of electric power data empowers, electric power knowledge graph provides new opportunities to solve the contradictions between the massive power resources and the continuously increasing demands for intelligent applications. In an attempt to fulfil the potential of knowledge graph and deal with the various challenges faced, as well as to obtain insights to achieve business applications of smart grids, this work first presents a holistic study of knowledge-driven intelligent application integration. Specifically, a detailed overview of electric power knowledge mining is provided. Then, the overview of the knowledge graph in smart grids is introduced. Moreover, the architecture of the big knowledge graph platform for smart grids and critical technologies are described. Furthermore, this paper comprehensively elaborates on the application prospects leveraged by knowledge graph oriented to smart grids, power consumer service, decision-making in dispatching, and operation and maintenance of power equipment. Finally, issues and challenges are summarised.

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This paper considers the problem of end-to-end security enhancement by resorting to deliberate noise injected in ciphertexts. The main goal is to generate a degraded wiretap channel in the application layer over which Wyner-type secrecy encoding is invoked to deliver additional secure information. More specifically, we study secrecy enhancement of the Data Encryption Standard (DES) block cipher working in cipher feedback model (CFB) when adjustable noise is introduced into the encrypted data in an application layer. A verification strategy in the exhaustive search step of the linear attack is designed to allow Eve to mount a successful attack in the noisy environment. Thus, a controllable wiretap channel is created over multiple frames by taking advantage of errors in Eve's cryptanalysis, whose secrecy capacity is found for the case of known channel states at receivers. As a result, additional secure information can be delivered by performing Wyner type secrecy encoding over superframes ahead of encryption. These secrecy bits could be taken as symmetric keys for upcoming frames. Numerical results indicate that a sufficiently large secrecy rate can be achieved by selective noise addition.

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With the rapid development of wind power generation and photovoltaic power generation, the phenomenon of wind and solar abandoning becomes more and more serious in the operation of power systems, and the microgrid is a new operating mode of power systems which provides a new consumption mode for wind power generation. With the increasingly close connection among energy resources and people's increasing awareness of environmental protection, this paper establishes a microgrid optimal scheduling model with a combined heat and power system, in consideration of environmental costs. This model aims at the lowest comprehensive cost, at the same time taking into account the emission reductions of SO 2 and NO x , considering the cost of power generated by the micro-generator, environmental cost, the related cost of battery, operation and maintenance cost of wind power, and photovoltaic power generation. The related constraints of thermal balance and power balance are also considered during microgrid system operation. The established model is solved with an improved particle swarm algorithm. At last, taking a microgrid system as an example, the validity and reliability of the proposed model are verified.Energies 2018, 11, 2493 2 of 23 microgrid system with wind and light storage [11,12], to achieve the goal of reducing the total operating costs and SO 2 and NO x emissions, has become an urgent problem to be solved.In recent years, the related research on microgrids has achieved certain results. In [13], Mao et al. comprehensively considered the operating cost, pollutant discharge, and operational risk, and established a multi-objective optimization model based on microgrids. It considered the impact of distributed power output volatility on microgrid operation, which can effectively improve the operation and management level of microgrids. In [14], Wu et al., based on the model of each power source in the microgrid, established the scheduling model when grid-connected, and proposed the mixed integer programming method applied to the optimal scheduling of the microgrid, which proves that this method has strong advantages in both computation time and calculation accuracy, and can provide fast and accurate scheduling information for short-term and ultra-short-term energy management of microgrids. In [15], Fubara et al. comprehensively considered the power balance and heat balance in a microgrid, and took the lowest operation cost as target, while considering the energy utilization rate, and two different operational strategies were proposed, which were applied to three different models. Through calculation, the operating costs under each power generation strategy were compared and verified. This contributed to the improvement of the energy efficiency of the microgrid. However, in [14,15], the investment of renewable energy, such as wind power and photovoltaics, is not taken into account, which can reduce the emission of pollutants to a certain degree. In [16], Thompson et al. established a multi-objective economic scheduling...