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The contamination of outliers severely damages the data quality, resulting in the inaccurate data-driven optimisation model. This study proposes a data quality aware chance-constrained model for the direct current optimal power flow (DC-OPF) problem under uncertainties. Under the framework of Bayesian statistics, the variational Bayesian Gaussian mixture model (VBGMM) is employed to extract the probabilistic information from the available historical data, i.e. realisations of random variables. VBGMM can identify the outliers by capturing their probability characteristics, in which way improving the data quality. Notably, VBGMM automatically determines the number of components, which is a remarkable difference from the conventional Gaussian mixture model. In addition, based on the affine policy, a method integrating VBGMM with chance-constrained programming is proposed to make VBGMM scalable. The proposed method is firstly tested on a 6-bus system for an illustrative purpose, and then on a 118-bus system for validating the potential practical application. Comparative studies verify the effectiveness of the proposed method.

In modern distribution system, the distribution system operator (DSO) acts as a market facilitator and data manager as well as an energy supplier and operation controller. In this circumstance, the DSO should comprehensively consider the diversified participants of the modern distribution system when making investment decisions of distributed generation (DG). This paper proposes a DG planning model considering the behavior of the diversified participants, which are motivated to cooperate with distributed renewable energy resources to promote their integration, and to achieve the optimal DG investment plan. The optimization model takes a centralized structure but fully considers the preferences, profits and comfort levels of the aggregators and consumers. The model is linearized into a mixed-integer linear programming (MILP) problem and is solved by CPLEX. Results of the case study show that when the DSO spares subsidies to the aggregators and consumers to encourage their participation in demand response (DR) programs, it earns more compared with providing no subsidies for DR participation. It is also demonstrated that the overall profit increases as the subsidies increase within a certain range, but decreases when the subsidies exceed this range. Therefore, the DSO needs to carefully choose the subsidization level to achieve the optimal utilization of renewable energy and demand flexibility. The optimal subsidization level is derived from the model proposed in this paper. Therefore, this paper puts forward a new pattern to utilize the distributed renewable energy sources, and provides guidance in policy making and DR program implementation.

Flavin derivatives (FLs) are the building blocks and functional groups within many enzymes that absorb strongly in the visible light region and are redox cofactors in a large number of biological p...

The integration of demand flexibility in distributed generation (DG) planning either lacks accuracy or ignores the potential of the behaviour of consumers in promoting the integration of renewables. This study proposes a DG planning model coordinating demand flexibility, in which the DG expansion plan and the behaviour of consumers in demand response (DR) programmes are co-optimised for the highest social welfare and the optimal utilisation of renewable generation. Consequently, the supply cost is reduced by utilising higher renewable generation instead of buying electricity from the grid. A share of the cost savings is allocated to the consumers to encourage their participation in DR programmes. Simulation results show that the expansion capacity of renewable generation is increased by 7.4% compared with no demand flexibility incorporation, and the social welfare is increased by up to 13.5% compared with no DG installation and 3.1% compared with no demand flexibility incorporation. Besides, the DR programmes carried out in the distribution system interact with the DG expansion plan, and higher subsidy rates in DR programmes could further promote the integration of renewables.

© 2010-2012 IEEE. Blockchain is the key technology of Bitcoin and other cryptocurrencies, and it is one of the most exciting technologies changing the world as of late. Targeting at big industrial energy users, this paper first presents a new market structure (i.e., transaction rules) under existing blockchain-based electricity transaction platforms to cover popular types of markets such as contract, day-ahead, adjustment and balancing markets; and then focuses on the optimal load management problem for a particular industrial user. The proof-of-work cost from blockchain is also modeled. A key feature of this load management problem is that the user has direct control on its own load. The obtained load control model is much more accurate than existing approaches in which system operators or demand aggregators cannot control load directly and have to rely on inaccurate estimations. As a case study, the pumping load of a water supply plant is investigated to illustrate how the demand load is managed under this blockchain-based market. From the case study, it is found that 18.9% of total cost can be saved under this new market structure.

The emission properties of a series of flavin (FL) decorated Ru (II) polyimine complexes were investigated by extensive time-dependent (TD) density functional theory (DFT) and DFT based calculations. We attributed the moderate emission properties of FL decorated Ru(II) polyimine complex (Ru-1), such as triplet lifetime and luminescence quantum yield, to the dominant fast nonradiative decay due to the small adiabatic energy gap between the ground state and the lowest lying triplet state (Δ E

Renewable energy generation plays an important role in exploiting renewable energy towards green economy. The electricity market should be not only reevaluated with the coming of renewable energy, but also modified for maintaining market fairness and better utilization of renewable energy. Based on a Stackelberg game model, this paper puts forward a closed-form analysis on wind power producer’s (WPP’s) behavior in the electricity market involving large scale wind power. The WPP acts as a price-maker in DA market and a deviator in RT balancing market. The analytical expression of WPP’s behavior indicates how a WPP takes an action under various market regulations and statuses, including bidding regulations, deviation settlements, demand elasticity, market capacity, and renewable subsidy. Furthermore, the two-part compound bidding mode is verified and recommended for restraining WPP’s market power when considering ramping constraints of conventional units. The presented models are validated using real-world data based on the IEEE 118-bus test system. Conclusions provide beneficial references for policy formulation of electricity market involving large scale wind power.

A bipyridine ruthenium(II) complex (Ru-1) with a flavin moiety connected to one of the bipyridine ligands via an acetylene bond was designed and synthesized, and its photophysical properties were investigated. Compared with the tris(bipyridine) Ru(II) complex (Ru-0), which has an extinction coefficient e = 1.36 × 104 M−1 cm−1 at 453 nm, the introduction of the flavin moiety endows Ru-1 with strong absorption in the visible range (e = 2.34 × 104 M−1 cm−1 at 456 nm). Furthermore, Ru-1 exhibits phosphorescence (λem = 643 nm, ΦP = 1%, τP = 1.32 μs at 293 K and 4.53 μs at 77 K). We propose that the emission of Ru-1 originates from the low lying triplet excited state of 3IL according to the time-resolved transient difference absorption spectra, the calculated T1 spin density and the T1 thermo-vibration modes localized on the flavin-decorated bipyridine ligand. This is the first time that the phosphorescence of flavin was observed within Ru(II) complexes. Consequently, Ru-1 was used for triplet–triplet annihilation upconversion, showing a reasonable quantum yield of 0.7% with respect to the phosphorescence quantum yield of 1%. These findings pave the way for the rational design of phosphorescence transition metal complexes. Also, further approaches that may improve the performance of flavin-decorated Ru(II) bipyridine complexes are proposed.

The wind model based on Markov process was proposed to determine the best installed capacity of wind farm. Firstly, piecewise probability distribution model based on Markov process was proposed to establish the scheduling multiple state probability distribution of wind power. Secondly, the probability production simulation method using the sequential convolution and non-sequential convolution was proposed to calculate the evaluation index which includes annual utilization hours of wind farm, wind curtailment, cost of traditional units and benefit of wind farm. Then the best installed capacity of wind farm could be calculated according to the above evaluation index with the aim to minimize the cost of the system. A case study was employed to illustrate the effectiveness of the proposed approach.

There are various incentive policies promoting the integration of renewable energy in power system planning. This paper proposes an entropy based matter-element model for incentive policy evaluation. A comprehensive evaluation system is established, which includes evaluation indexes concerning the cost, reliability, environmental effects and operational flexibility of the planning result. On this basis, entropy method is applied to objectively assess the weight of the evaluation indexes in varying criteria. Moreover, with coordinate transformation introduced into the matter-element model, the incentive policies are distinguished by more balanced and dispersed grades. Case study based on a real-world power system shows that the proposed matter-element model better distinguishes different incentive policies than the conventional model, with more reasonable, flexible and objective conclusion. This model can also be used to further analyze the role that future power system plays in energy revolution.

This paper proposes a novel risky bilateral contract for trading distributed wind energy with flexible load in smart microgrid. Due to the randomness of wind energy production, wind energy can barely be traded at a pre-determined quantity. While in smart grid, load demand of electricity consumer can be easily adjusted (reduced or shifted) without decreasing its satisfaction, which can be utilized for integration of distributed wind energy. As a result, the wind power producer benefits from fewer penalties caused by less deviation between real-time traded quantity and pre-offered one. The electricity consumer, on the other hand, benefits from a decreased electricity bills without reducing its satisfaction. We take into account distributed wind energy, three categories of household appliances, and batteries. The Nash bargaining theory is used to determine the price of risky bilateral contract. Case studies are then conducted to demonstrate the efficiency of the risky bilateral contract.

Economic and safe operation of the power industry is a critical foundation to support socio-economic development. In order to accurately assess the economic and operation efficiency for the power transmission system, the influential factors were analyzed in this paper, which used to establish the index system that consisted by critical indexes of power. What's more, the influence of grid-connected intermittent generations was considered. Firstly, the evaluation model was proposed based on the understanding of the key indicators of economic and operation efficiency of the regional power, considering intermittent generations. Secondly, the economic effectiveness and operational efficiency were set as two sub-goals, and comprehensive weights of various indexes were set by analytic hierarchy process based on the expert scoring method. Thirdly, the comprehensive economic and operation efficiency was assessed and identified by the multi-object multi-level fuzzy methods. Finally, through case analysis, the index system and method can effectively measure rank of economic and operation efficiency of the transmission system, and provide guidance of the development of regional power transmission system.

Heat pump water heaters (HPWHs) have a high energy transformation efficiency, which contributes to their wide utilization in public buildings and residences. This paper proposes the electrical model of HPWHs, which describes the heating function, electricity utilization, user comfort requirements and physical constraints of HPWHs. A novel control method using the heat demand as control criterion is then proposed. The purpose of controlling HPWHs is to make good use of their energy storage ability. For a distribution grid with massive HPWHs installed, properly controlled HPWHs can modify the load curve, thus promoting the integration of renewables. A case study based on a real-world distribution system demonstrates that the electrical model of HPWHs well represents their characteristics, and the control method is effective in promoting renewable integration with HPWHs. The impacts of massive HPWHs on the load curve are also investigated.

In this paper, a novel electric power source structure optimization (EPSSO) scheme is proposed to achieve the sustainable development objectives of economic growth, electricity demand and environmental protection. Different from power generation expansion planning (PGEP), the proposed EPSSO method evaluates the optimal investment scheme for a long-term power generation expansion from the viewpoints of macro-economy. By adjusting the proportion of renewable power generating units at a more appropriate time, it can promote the efficiency of national capital with the constraint of CO2 emissions. The basic idea of this method is to combine the conventional objective function with the capital efficiency which is often used as a repressor of economic growth. At last, the genetic algorithm (GA) is used to solve the highly nonlinear combinatorial problem of EPSSO and a numerical case is present to demonstrate the feasibility of this scheme based on the background of China.

A clustering method based on k nearest neighbor is proposed for the dynamic equivalent of wind farm in this paper. After dimension reduction, this method can detect boundary points (BPs) of clustering parameters of wind turbines along the border of it. So the training samples and store space are reduced significantly. Initial clustering result is obtained according to the sequence of BPs. Final clustering result with pre-defined number of clusters or accuracy can be obtained by simply modifying the initial result. Consequently, the efficiency of clustering is enhanced greatly. The method is demonstrated on a wind farm consisting of 133 wind turbines. Dynamic responses of equivalent model of the wind farm are compared against the responses of the detail model. Simulation results demonstrate the efficiency of the method.

Generation expansion planning (GEP) is becoming more complicated with the integration of renewable energy sources (RES). Using the decomposition-coordination technique, the nonlinear optimization problem of GEP is decomposed into sub-problems, whose results are coordinated to obtain the optimal GEP scheme by iteration. However, using the conventional iterative method to solve GEP is becoming more difficult with the integration of RES. In this paper, the iterative method is improved to solve GEP when RES are incorporated. By adaptively inheriting the iterated variables and searching for the optimal iterative direction, this method obtains more satisfactory GEP scheme with less computation time, and avoids entrapment in local optima. The effectiveness of the improved iterative method is proved in comparison with the conventional iterative method in case studies.

Shinohara, Akio, Kawada, Shin-ichiro, Son, Nguyen Truong, Can, Dang Ngoc, Sakamoto, Shinsuke H., Koshimoto, Chihiro (2015): Molecular phylogenetic relationships and intra-species diversities of three Euroscaptor spp. (Talpidae: Lipotyphla: Mammalia) from Vietnam. Raffles Bulletin of Zoology 63: 366-375, {"references":["Lunde DP, Musser GG & Ziegler T (2004) Description of a new species of Crocidura (Soricomorpha: Soricidae, Crocidurinae) from Ke Go Nature Reserve, Vietnam. Mammal Study, 29: 27-36.","Matzke NJ (2014) Model selection in historical biogeography reveals that founder-event speciation is a crucial process in island clades. Systematic Biology, 63: 951-970.","Moribe J & Yokohata Y (2011) Mixed distribution of Mogera imaizumii and Mogera wogura in the Tedori alluvial fan in Ishikawa prefecture, Japan. 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Economic sustainable development is an inherent requirement of the regional economic development. The purpose of this article is to correctly understand the capacity of sustainable economic development in Henan Province, then for promoting better sustainable development in the future. Instead of using subjective evaluation index system, this paper used the method of Social & Ecological Accounting Matrix, the framework based on social accounting matrix, additional resources accounts, environmental accounts and other elements. Through comparative analyses of some relevant economic data of Henan Province from 2001 to 2009, including growth rate of GDP, high energy consumption and high pollution industry, energy production and energy consumption, the results shows the capacity of economic sustainable development in Henan Province gradually increases capacity in recent years, but still is in the weakness of the range.

As Peter Johnson would say, “ for every syndrome of unknown aetiology, there is always an immunological theory.” First, it is my contention that immune events optimize and perhaps at some stage insure the success of pregnancy. Models of immune abortion do exist in animals and a subset of such probably exists in humans; immunological events are also likely involved in labor and threatened preterm delivery. However, it is not my contention that labor is an solely immune event, as maintained by some. Second, what is true for rodents does not necessarily hold for humans. Third, the reagents used in studies need to be of exquisite specificity and the patient series large. Unfortunately, these precautions are not always taken, and hence false conclusions are drawn.

The evolution of Leydig cells in Macaca fascicularis fetuses was followed throughout gestation (50-150 d) by morphometric procedures (volume densities of: cells, SER, mitochondria and lipid droplets). Testosterone from umbilical artery plasma was radioimmunoassayed starting on day 57. After predifferentiation and differentiation phases, Leydig cells entered the maturity phase (57-66 d), they occupied 19% of testicular volume, SER and lipid droplets represented 19% and 5% respectively of cytoplasmic volume. Then Leydig cells regressed dramatically (involution phase I: 66-83 d), their volume density decreased to 8%, that of SER to 12% whereas lipids doubled. Leydig cell volume density diminished to 5% during the second half of gestation (involution phase II), but their ultrastructure was not significantly altered. High plasma testosterone level (2.4 ng/ml) was observed during the maturity phase of Leydig cells, decline of testosterone occurred during involution phases I and II (1.13 and 0.58 ng/ml respectively). Its was shown that from day 57 to the end of fetal development the evolution of the plasma testosterone level correlated with the Leydig cell volume density and the SER volume density.