EV Charging in Case of Limited Power Resource

In the case of the widespread adoption of electric vehicles (EV), it is well known that their use and charging could affect the network distribution system, with possible repercussions including line overload and transformer saturation. In consequence, during periods of peak energy demand, the number of EVs that can be simultaneously charged, or their individual power consumption, should be controlled, particularly if the production of energy relies solely on renewable sources. This requires the adoption of adaptive and/or intelligent charging strategies. This paper focuses on public charging stations and proposes methods of attribution of charging priority based on the level of charge required and premiums. The proposed solution is based on model predictive control (MPC), which maintains total current/power within limits (which can change with time) and imparts real-time priority charge scheduling of multiple charging bays. The priority is defined in the diagonal entry of the quadratic form matrix of the cost function. In all simulations, the order of EV charging operation matched the attributed priorities for the cases of ten cars within the available power. If two or more EVs possess similar or equal diagonal entry values, then the car with the smallest battery capacitance starts to charge its battery first. The method is also shown to readily allow participation in Demand Side Response (DSR) schemes by reducing the current temporarily during the charging operation.

Singular matrix conjugacy problem with rapidly oscillating off-diagonal entries. Asymptotics of the solution in the case when a diagonal entry vanishes at a stationary point

The ( 2 × 2 ) (2\times 2) matrix conjugacy problem (the Riemann–Hilbert problem) with rapidly oscillating off-diagonal entries and quadratic phase function is considered, specifically, the case when one of the diagonal entries vanishes at a stationary point. For solutions of this problem, the leading term of the asymptotics is found. However, the method allows us to construct complete expansions in power orders. These asymptotics can be used, for example, to construct the asymptotics of solutions of the Cauchy problem for the nonlinear Schrödinger equation for large times in the case of the so-called collisionless shock region.

Investigation of Alardinskaya mine coal bumps causes using computer simulation of rock massif stress conditionals

The purpose of the paper was to identify the causes of rock bumps that occurred at the Alardinskaya mine (Russia) in 2011. The research was carried out using the finite element method. The developed three-dimensional model of the rock mass included a coal seam, rocks bedding above and below, goaf, and a system of local preparatory workings. The situation that arose immediately before the first rock burst was modeled during the research - when the longwall crossed a diagonal entry. The performed investigations enabled the authors to make a conclusion about a high danger of using technological schemes for the development of seams by longwalls leaving pillars that have a width less than the length of the support pressure zone, especially due to diagonal entries. As a safe technology for the longwall development of seams prone to rock bursts, it is recommended to apply a technological scheme with the abandonment of wide barrier pillars and four preparatory workings in each section, which has proven itself in the processing of rock bump hazardous seams in the state of Utah (USA).

An Eigenvalue Inclusion Set for Matrices with a Constant Main Diagonal Entry

A set to locate all eigenvalues for matrices with a constant main diagonal entry is given, and it is proved that this set is tighter than the well-known Geršgorin set, the Brauer set and the set proposed in (Linear and Multilinear Algebra, 60:189-199, 2012). Furthermore, by applying this result to Toeplitz matrices as a subclass of matrices with a constant main diagonal, we obtain a set including all eigenvalues of Toeplitz matrices.

Toward a Model-Based Experimental Approach to Assessing Collective Systems Design

This work presents a conceptual model of collective decision-making processes in engineering systems design to understand the tradeoffs, risks, and dynamics between autonomous but interacting design actors. The proposed approach combines value-driven design, game theory, and simulation experimentation to study how technical and social factors of a design decision-making process facilitate or inhibit collective action. The collective systems design model considers two levels of decision-making: 1) lower-level design value exploration; and 2) upper-level design strategy selection. At the first level, the actors concurrently explore two strategy-specific value spaces with coupled design decision variables. Each collective decision is mapped to an individual scalar measure of preference (design value) that each actor seeks to maximize. At the second level, each of the actor’s design values from the two lower-level design exploration tasks is assigned to one diagonal entry of a normalform game, with off-diagonal elements calculated in function of the “sucker’s” and “temptation-to-defect” payoffs in a classical strategy game scenario. The model helps generate synthetic design problems with specific strategy dynamics between autonomous actors. Results from a preliminary multi-agent simulation study assess the validity of proposed design spaces and generate hypotheses for subsequent studies using human subjects.

Rank relations between a {0, 1}-matrix and its complement

Let A be a {0, 1}-matrix and r(A) denotes its rank. The complement matrix of A is defined and denoted by Ac = J − A, where J is the matrix with each entry being 1. In particular, when A is a square {0, 1}-matrix with each diagonal entry being 0, another kind of complement matrix of A is defined and denoted by A = J − I − A, where I is the identity matrix. We determine the possible values of r(A) ± r(Ac) and r(A) ± r(A) in the general case and in the symmetric case. Our proof is constructive.