Multi-population-based differential evolution algorithm for optimization problems

A differential evolution (DE) algorithm is an evolutionary algorithm for optimization problems over a continuous domain. To solve high dimensional global optimization problems, this work investigates the performance of differential evolution algorithms under a multi-population strategy. The original DE algorithm generates an initial set of suitable solutions. The multi-population strategy divides the set into several subsets. These subsets evolve independently and connect with each other according to the DE algorithm. This helps in preserving the diversity of the initial set. Furthermore, a comparison of combination of different mutation techniques on several optimization algorithms is studied to verify their performance. Finally, the computational results on the arbitrarily generated experiments, reveal some interesting relationship between the number of subpopulations and performance of the DE. Centralized charging of electric vehicles (EVs) based on battery swapping is a promising strategy for their large-scale utilization in power systems. In this problem, the above algorithm is designed to minimize total charging cost, as well as to reduce power loss and voltage deviation of power networks. The resulting algorithm and several others are executed on an IEEE 30-bus test system, and the results suggest that the proposed algorithm is one of effective and promising methods for optimal EV centralized charging

Galacticus: A Semi-Analytic Model of Galaxy Formation

We describe a new, free and open source semi-analytic model of galaxy formation, Galacticus. The Galacticus model was designed to be highly modular to facilitate expansion and the exploration of alternative descriptions of key physical ingredients. We detail the Galacticus engine for evolving galaxies through a merging hierarchy of dark matter halos and give details of the specific implementations of physics currently available in Galacticus. Finally, we show results from an example model that is in reasonably good agreement with several observational datasets. We use this model to explore numerical convergence and to demonstrate the types of information which can be extracted from Galacticus.Comment: 35 pages, submitted to New Astronom

Coordinated Volt-Var control in multiple smart inverters in Smart Distribution Networks for Voltage Regulation.

The inevitable growing demand for electrical power, depleting sources of conventional power generation, and world wide concern about global warming are major factors to boost the trend of renewable integration in grids. This rising trend is causing many technical and operational challenges where one of the most prominent problem is the overvoltage caused by distributed generation units, interfaced at the consumer end, and power injections at random nodes. This in contrast with predefined power flows of conventional grids gives rise to bidirectional power flows that demand for modern, coordinated and robust voltage regulation scheme with minimal communication infrastructure. A centralized, coordinated, differential evolution based Volt/VAR regulation scheme is proposed to eliminate the voltage deviations caused by excessive photovoltaic integration in distribution systems. Time step simulation utilizing OpenDSS interfaced with MATLAB on standard IEEE-123 feeder are implemented to test the effectiveness of the proposed scheme

A Hierarchical Game with Strategy Evolution for Mobile Sponsored Content and Service Markets

In sponsored content and service markets, the content and service providers are able to subsidize their target mobile users through directly paying the mobile network operator, to lower the price of the data/service access charged by the network operator to the mobile users. The sponsoring mechanism leads to a surge in mobile data and service demand, which in return compensates for the sponsoring cost and benefits the content/service providers. In this paper, we study the interactions among the three parties in the market, namely, the mobile users, the content/service providers and the network operator, as a two-level game with multiple Stackelberg (i.e., leader) players. Our study is featured by the consideration of global network effects owning to consumers' grouping. Since the mobile users may have bounded rationality, we model the service-selection process among them as an evolutionary-population follower sub-game. Meanwhile, we model the pricing-then-sponsoring process between the content/service providers and the network operator as a non-cooperative equilibrium searching problem. By investigating the structure of the proposed game, we reveal a few important properties regarding the equilibrium existence, and propose a distributed, projection-based algorithm for iterative equilibrium searching. Simulation results validate the convergence of the proposed algorithm, and demonstrate how sponsoring helps improve both the providers' profits and the users' experience