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In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides Microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimization (MOO) and decision analysis is put forward to address this model. First, a powerful heuristic optimization algorithm, called the θ-dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. And thereby, the best compromise solutions (BCSs) are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Background: Melanoma cells invasion through the dermis directly correlates with death, defining migration as critical. Results: ACTN4 down-regulation limits aggressive melanoma cells to a mesenchymal phenotype that retards collagen I matrix invasiveness. Conclusion: Amoeboidal morphology necessary for melanoma invasion requires ACTN4. Significance: This finding provides for a role of ACTN4 in melanoma invasion and implicates a linkage between actin cytoskeleton and melanoma progression.

Summary The extended black‐start strategy is new exploration for black‐start restoration of power systems, in which more than one non–black‐start unit can be restored simultaneously during the black‐start stage. This paper presents a multiobjective optimization method coordinating unit restarting with load restoration for extended black‐start decision making. The objective functions of the black‐start restoration optimization are defined as restoring non–black‐start units and unserved loads as much as possible under steady‐state and transient system operation constraints. A hybrid algorithm combining the lexicographic method with the improved bacterial foraging algorithm is used to solve the defined optimization model. The proposed method has been tested on the IEEE 118‐bus system and the southern Hebei power system of China, and the test results verify the effectiveness of the proposed decision‐making method.

Power system restoration after a major blackout is a complex process, in which selection of energising paths is a key issue to realize unit and load restoration safely and efficiently. In general, the energising path scheme made beforehand may not be executed successfully due to the possible faults on the related lines under the extreme system condition, so it is necessary to provide alternative path schemes for system restoration. In view of this, the energising path optimisation based on the minimum cost flow model is investigated, then an iterative searching method for alternative path schemes based on mixed integer linear programming is proposed. The iterative method for alternative path schemes could determine more than one scheme with minimal charging reactive power efficiently. In order to make a comprehensive evaluation of the alternative schemes, an evaluation index set is established, and the method based on similarity to ideal grey relational projection is introduced to achieve the final evaluation. The New England 10-unit 39-bus system and the southern Hebei power system of China are employed to demonstrate the effectiveness of the proposed method. The proposed method can provide more efficient and comprehensive decision support for the dispatchers to select reasonable energising paths.