Optimal relay coordination of an adaptive protection scheme using modified PSO algorithm.

Recently, future smart grids are described by a dominantly fluctuating character due to the power consumption change from peak to off-peak loading conditions, the operation of micro-grids in grid-connected or islanded mode and other possible network topologies resulting in an effective change in network impedances and short circuit current level. Therefore, the situation from protection sensitivity, selectivity and speed may become more and more challenging. In this paper, Adaptive protection scheme is proposed to respond to structural variations occurred in interconnected power systems. A designed software based on Modified Particle Swarm Optimization (MPSO) algorithm is suggested to solve the relay coordination problem in modern distribution networks. In this study, the 14 IEEE bus system is tested via three power system scenarios showing the effect of adding and disconnecting of DG units and the occurrence of sudden line outages on the system. The obtained results show that the proposed algorithm has achieved optimum relay settings for each existing network topology

Survey on Ten Years of Multi-Depot Vehicle Routing Problems: Mathematical Models, Solution Methods and Real-Life Applications

A crucial practical issue encountered in logistics management is the circulation of final products from depots to end-user customers. When routing and scheduling systems are improved, they will not only improve customer satisfaction but also increase the capacity to serve a large number of customers minimizing time. On the assumption that there is only one depot, the key issue of distribution is generally identified and formulated as VRP standing for Vehicle Routing Problem. In case, a company having more than one depot, the suggested VRP is most unlikely to work out. In view of resolving this limitation and proposing alternatives, VRP with multiple depots and multi-depot MDVRP have been a focus of this paper. Carrying out a comprehensive analytical literature survey of past ten years on cost-effective Multi-Depot Vehicle Routing is the main aim of this research. Therefore, the current status of the MDVRP along with its future developments is reviewed at length in the paper

Hybrid Genetic Algorithm for Multi-Period Vehicle Routing Problem with Mixed Pickup and Delivery with Time Window, Heterogeneous Fleet, Duration Time and Rest Area

Most logistics industries are improving their technology and innovation in competitive markets in order to serve the various needs of customers more efficiently. However, logistics management costs are one of the factors that entrepreneurs inevitably need to reduce, so that goods and services are distributed to a number of customers in different locations effectively and efficiently. In this research, we consider the multi-period vehicle routing problem with mixed pickup and delivery with time windows, heterogeneous fleet, duration time and rest area (MVRPMPDDR). In the special case that occurs in this research, it is the rest area for resting the vehicle after working long hours of the day during transportation over multiple periods, for which with confidence no research has studied previously. We present a mixed integer linear programming model to give an optimal solution, and a meta-heuristic approach using a hybrid genetic algorithm with variable neighborhood search algorithm (GAVNS) has been developed to solve large-sized problems. The objective is to maximize profits obtained from revenue after deducting fuel cost, the cost of using a vehicle, driver wage cost, penalty cost and overtime cost. We prepared two algorithms, including a genetic algorithm (GA) and variable neighborhood search algorithm (VNS), to compare the performance of our proposed algorithm. The VNS is specially applied instead of the mutation operator in GA, because it can reduce duplicate solutions of the algorithms that increase the difficulty and are time-consuming. The numerical results show the hybrid genetic algorithm with variable neighborhood search algorithm outperforms all other proposed algorithms. This demonstrates that the proposed meta-heuristic is efficient, with reasonable computational time, and is useful not only for increasing profits, but also for efficient management of the outbound transportation logistics system

Optimal protective relaying scheme of distributed generation connected distribution network using particle swarm optimization-gravitational search algorithm technique

This paper develops particle swarm optimization integrated with gravitational search algorithm (PSO-GSA) to coordinate the relays in a distribution system with distributed generation (DG) connectivity. This algorithm combines PSO and GSA to improve the performance of the relay protection system. To prevent relay malfunctions following DG penetration, a suitable primary and backup relay is chosen. The PSO-GSA is coded using MATLAB software and tested on an IEEE 4-bus system simulated in Simulink. Results indicate that, when compared to using regular PSO and GSA procedures individually, the PSO-GSA technique reduces the operating time of the relay significantly

A Comparative Study of the PSO and GA for the m-MDPDPTW

The m-MDPDPTW is the multi-vehicles, multi-depots pick-up and delivery problem with time windows. It is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers for the purpose of satisfying precedence, capacity and time constraints. This problem is a very important class of operational research, which is part of the category of NP-hard problems. Its resolution therefore requires the use of evolutionary algorithms such as Genetic Algorithms (GA) or Particle Swarm Optimization (PSO). We present, in this sense, a comparative study between two approaches based respectively on the GA and the PSO for the optimization of m-MDPDPTW. We propose, in this paper, a literature review of the Vehicle Routing Problem (VRP) and the Pick-up and Delivery Problem with Time Windows (PDPTW), present our approaches, whose objective is to give a satisfying solution to the m-MDPDPTW minimizing the total distance travelled. The performance of both approaches is evaluated using various sets instances from [10] PDPTW benchmark data problems. From our study, in the case of m-MDPDPTW problem, the proposed GA reached to better results compared with the PSO algorithm and can be considered the most appropriate model to solve our m-MDPDPTW problem

Revisión del estado del arte del problema de ruteo de vehículos con recogida y entrega (VRPPD)

This paper presents a literature review of the state of the art vehicle routing problem with deliveries and collections (VRPPD: Vehicle Routing Problem with pickups and deliveries). Is performed a classification of the different variants of the problem, and the work and conducted research on the subject according to its authors, according to the models and the solution methods used. Also are analyzed future trends in modeling and solution techniques. The VRPPD is a problem of type MILP (Mixed Integer Linear Programming) involving whole and continuous quantities, and that turns out to be NP-Hard problems with a medium or large number of customers. The research does emphasis on variants of the problem involving variables associated with the environment, and in particular reducing the impact of greenhouse gases. The review notes that published until 2016.En este trabajo se realiza una revisión bibliográfica del estado del arte del problema de ruteo de vehículos con entregas y recogidas (VRPPD: Vehicle routing problem with pickups and deliveries). Se presenta una clasificación de las diferentes variantes del problema, y de los trabajos e investigaciones realizados sobre el tema según sus autores, los modelos utilizados y los métodos de solución usados. También se analizan las tendencias futuras en modelamiento y técnicas de solución. El VRPPD es un problema del tipo MILP (programación lineal entera mixta) que involucra cantidades enteras y continuas, y que resulta ser NP-Hard en problemas con un número mediano o grande de clientes. En la búsqueda se hace énfasis en las variantes del problema que involucran variables asociadas al medio ambiente, y en particular con la reducción del impacto de gases de efecto invernadero. La revisión observa lo publicado hasta el año 2016