Abstract
Dynamic distribution system reconfiguration (DDSR) is the process of dynamically changing the network's topology during the operational periods of the system. This process together with the integration of distributed renewable energy sources (DRES) and other enabling technologies allow a more efficient operation of such systems in technical and economic terms, facilitating a seamless integration of DRES in larger quantities. When performing such an optimization process, the stochastic nature of DRES (both variability and uncertainty) needs to be taken into consideration. In this paper, an improved dynamic system reconfiguration model is presented where the goal is to minimize the total cost in the system while satisfying various technical constraints so as to maintain the reliability and stability of the system at required levels. The computational tool is tested in a real system encompassing the distribution system of Lagoa (in Sao Miguel Island, Azores), and its effectiveness is properly validated. The numerical results demonstrate great benefits in economic terms, such as reduced losses and improved system reliability.

Abstract
Electrical distribution systems are facing new challenges mainly due to the growing penetration of distributed generation of mainly intermittent nature such as wind and solar PV. As a result, these systems need to undergo massive transformations in terms of operational scheme. In other words, new operational strategies, which increase the flexibility of distribution systems, have to be put in place. This is highly required if distribution systems are to support large quantities of variable RES power. One plausible strategy worth considering relates to the meshed operation of such systems. The main topic of this paper revolves around the prospects of operating distribution grids in a meshed manner. The benefits are quantified in terms of added flexibility to the system, and vRES utilization levels. A mixed integer linear programming model is employed to perform the required analysis, and a 119-bus distribution system is used for this purpose. The analysis of the results generally shows the strong viability of the new operation strategy in terms of adding flexibility and scaling up the utilization level of variable RES power in the considered system. This strategy can be considered as a viable flexibility option that enables further integration of intermittent power sources.

Abstract
Power system restoration (PSR) is a very important procedure to ensure the consumer supply. In this paper, a decentralized multi-agent system (MAS) for dealing with the microgrid restoration procedure is proposed. In this method, each agent is associated with a consumer or microsource (MS) and these communicate with each other to reach a common decision. The agents solve a 0/1 knapsack problem to determine the best load connection sequence during the microgrid restoration procedure and then the proposed MAS is tested in one specific scenario where the microgrid is subjected to a blackout that occurred. This means that all the resources and loads are disconnected. This work is developed in Matlab/Simulink environment and the results show its feasibility and effectiveness in the microgrid restoration procedure.

Abstract
Demand response (DR) provides enormous opportunities to distribution system operators so as to conduct the power system in a sustainable manner. Due to the increasing penetration of electric vehicles (EV) in the power system, the necessity of enhancing flexibility has gained importance in the charging operation process. With the aid of the smart grid concept and DR programs, more flexible grid operations are provided. In this study, an optimal day-ahead EV charging strategy through electric vehicle parking lots (EVPL) aggregators is intended for the purpose of maximizing the load factor during daily operation. Furthermore, the behavioral uncertainty of EVs and peak load limitation based DR programs are also taken into account in the devised model. In order to reveal the effectiveness of the proposed EVPL aggregator energy management strategy, various case studies are performed, and credible results are reported.

Abstract
The uncertainty and variability as a consequence of modern utilization of wind power in the electrical system besides unpredicted contingencies of the system components can impose crucial challenges on the Independent System Operator's (ISO) performance. In such a situation, increasing operational flexibility is the main way to cover wind power unpredictability and to enable secure operation of the power system. To this end, this paper proposes a flexible security-constrained program to schedule supply-side and demand-side via an optimal pricing and incentive scheme. The considered demand response (DR) programs include time of use (TOU), real-time pricing (RTP), critical peak pricing (CPP), as well as emergency demand response program (EDRP). The study aims to find the most effective DR scheme among a set of DR programs to improve the efficiency of electricity markets while guaranteeing the security and environmental restrictions through minimization of two objective functions, the ISO's operational cost and pollutant emissions from generation units.

Abstract
The power demand uncertainties and intrinsic intermittent characteristics of wind and photovoltaic (PV) distributed energy resources (DERs) make the conventional load flow methods inefficient in active distribution networks (ADNs) and microgrids. Some statistical tools such as Monte Carlo simulation (MCS) are always a reliable solution. However, statistical tools are time-consuming and rather useless in large power systems. In this paper, a new method is proposed for robust probabilistic load flow (PLF) in microgrids and ADNs, including renewable energy resources (RERs), based on singular value decomposition (SVD) unscented Kalman filtering. The probability density functions (PDFs) and cumulative distribution functions (CDFs) for some of the ADN variables are compared with the other reported PLF methods for different test systems and the results validate the robustness, efficiency and accuracy of the proposed method.