Abstract
Due to the rapidly increasing share of electric vehicles (EVs) worldwide, the abundance of EV parking lots (with charging capabilities) is becoming necessary to provide for charging needs in addition to attempting to fully utilize EVs for the benefit of future smart grids. Unmanaged charging of EVs can jeopardize stability and reliability of power systems. Hence, well-operated EV parking lots can be a good solution to enhance system stability. Equipping parking lots with rooftop photovoltaics (PVs) has been gaining interest as a good approach for their design and operation. During the day, when EVs are stationed in the parking lot and particularly in more commercial neighborhoods of cities, the EVs can be charged directly through solar generation, so that minimal stress on the distribution system occurs. This work aims to conduct a comparative study investigating the optimal strategies for the operation of PV-equipped EV parking lots. Multiple parameters are taken into consideration including weather conditions, uncertainty of EV owners' schedules, and EV models. This analysis will result in finding the optimal strategy for the operation of the parking lot from the owner/operator point of view in order to minimize costs and maximize services provided to the grid.

Abstract
In this paper, we propose an active fault tolerant control (FTC) to regulate the active and reactive output powers of a voltage source converter (VSC) in the case of actuator failure. The active fault tolerant controller of the VSC which connects a distributed energy resource to the distribution power grid is achieved through the fault diagnostic and controller reconfiguration units. The diagnostic unit reveals the actuator failure by comparing the known inputs and measured outputs of VSC with those of the faultless model of the system and testing their consistency. In the case of actuator failure, the reconfiguration unit adapts the controller to the faulty system which enables the VSC to track the desired active and reactive output powers. The reconfiguration unit is designed using the virtual actuator which does not interfere with the regular controller of the VSC. The effectiveness of the proposed active FTC is evaluated by the numerical simulation of a VSC connected to the AC distribution grid.

Abstract
As a result of Demand Response (DR) programs implementation in the industrial sector, varying electricity prices based on Time-of-Use (ToU) rates are becoming more common, replacing traditional flate-rates per unit of energy consumption. On the other hand, increased automation of industrial facilities is gaining interest due to their reliability, flexibility, and robustness. However, it is necessary to determine a suitable task schedule in order to ensure their cost-efficiency and maximize profits. In this study, a Market-Based approach is considered to solve the Multi-Agent Task Allocation (MATA) problem for a group of homogeneous agents and tasks. While most previous studies model the problem considering flate-rates for electricity consumption, the main contribution of this study is accounting for the implementation of a DR program with varying ToU rates. The effects of optimizing the task allocation process on the costs incurred are investigated and compared to the effects of random assignment. Four different case studies are analyzed considering different-sized maps and number of tasks. The results show the computational efficiency of the proposed algorithm and its ability to massively decrease the electrical charging costs.

Abstract
In this paper, a risk-constrained optimal scheduling framework is proposed for an economic and reliable operation of microgrids. The framework is developed based on a scenario-based optimization technique, to schedule the microgrid operation both in normal and islanding modes. The prevailing uncertainties of islanding duration as well as prediction errors of loads, market prices and renewable power generation are addressed in the scheduling problem. The effect of participation of customers in demand response (DR) programs is investigated on economic-reliable operating solutions. Also, the uncertainties associated with wind power, loads and electricity prices as well as the uncertainties of islanding duration events of the microgrid are modeled, properly. The optimal scheduling carried out through a unit commitment algorithm and an AC power flow procedure by considering system's objectives and constraints. Moreover, to adequately handle the uncertainties of the problem, conditional value-at-risk (CVaR) metric is incorporated into the optimization model to evaluate the profit risk associated with operator's decisions in different conditions. With the proposed model, the impacts of DR actions, in terms of economy and reliability, are investigated with a 400 V microgrid system.

Abstract
In this work, a generalized mathematical formulation is proposed to model a generic public transport system, and a mixed-integer linear programming (MILP) optimization is used to determine the optimal design of the system in terms of charging infrastructure deployment (with on-route and off-route charging), battery sizing, and charging schedules for each route in the network. Three case studies are used to validate the proposed model while demonstrating its universal applicability. First, the design of three individual routes with different characteristics is demonstrated. Then, a large-scale generic transport system with 180 routes, consisting of urban and suburban routes with varying characteristics is considered and the optimal design is obtained. Afterwards, the use of the proposed model for a long-term transport system planning problem is demonstrated by adapting the system to a 2030 scenario based on forecasted technological advancements. The proposed formulation is shown to be highly versatile in modeling a wide variety of components in an electric bus (EB) transport system and in achieving an optimal design with minimal TOC.

Abstract
A highly versatile optimal task scheduling algorithm is proposed, inspired by Dijkstra's shortest path algorithm. The proposed algorithm is named "Dijkstra Optimal Tasking" (DOT) and is implemented in a generic manner allowing it to be applicable on a plethora of tasking problems In this study, the application of the proposed DOT algorithm is demonstrated for industrial setting in which a set of tasks must be performed by a mobile agent transiting between charging stations. The DOT algorithm is demonstrated by determining the optimal task schedule for the mobile agent which maximizes the speed of task achievement while minimizing the movement, and thereby energy consumption, cost. A discussion into the anticipated plethora of applications of this algorithm in different sectors is examined.