Daniel Pinheiro Bernardon

Multicriteria Distribution Network Reconfiguration Considering Subtransmission Analysis

Topological reconfiguration is an important tool for the planning and operation of electric power distribution systems. The amount of time that an algorithm spends on obtaining an alternative topological status for the system is not a primary concern, since the main goals of distribution operation planning are the reduction of power losses, the enhancement of the voltage profile, and the increase of reliability levels. The utility can use multiple criteria regarding the observation of regulation policies and public awareness to drive the topological reconfiguration. Several researchers are looking for new optimization methods, as the complexity of this combinatorial issue is high in large systems and the classic optimization methods are failing to address the problem reasonably. Therefore, we propose a new fuzzy multicriteria decision making algorithm and software to distribution network reconfiguration also including the power losses analysis of subtransmission systems. The effectiveness of the proposed algorithm is demonstrated with case studies involving actual systems.

AHP Decision-Making Algorithm to Allocate Remotely Controlled Switches in Distribution Networks

Continuity in power supply for the consumers is a permanent concern from the utilities, pursued with the development of technological solutions in order to improve the performance of network restoration conditions. Using remotely controlled switches corresponds to one possible approach to reach such an improvement and gives some convenient remote resources, such as the fault detect, isolation, and transfer loads. This paper presents a methodology implemented in a computer programming language for allocation of these devices in electric distribution systems based on the analytic hierarchical process (AHP) method. The main contributions focus on considering the impact of installing remotely controlled switches in the reliability indices and the AHP decision-making algorithm for the switches allocation. The effectiveness of the proposed algorithm is demonstrated with case studies involving actual systems of the AES Sul utility located in Southern Brazil.

Software for Automatic Coordination of Protection Devices in Distribution System

Among the several components of distribution systems, protection devices present a fundamental importance, since they aim at keeping the physical integrity not only of the system equipment, but also of the electricians team and the population in general. The existing tools today in the market that carry out the making of protection studies basically draw curves, and need direct users interference for the protection devices adjustment and coordination analyses of selectivity, being susceptible to the users mistakes and not always considering the best technical and economical application. In Brazil, the correct application of the protection devices demand a high amount of time, being extremely laborious due to the great number of devices (around 200 devices), besides the very dynamic behavior of distribution networks and the need for constant system expansion. This paper presents a computational tool developed with the objective of automatically determining the adjustments of all protection devices in the distribution networks to obtain the best technical application, optimizing its performance and making easier protection studies.

Automatic Restoration of Power Supply in Distribution Systems by Computer-Aided Technologies

The need to improve quality and reliability of Power Systems has contributed to the advancement of research on Smart Grids and related topics. Some challenges that motivate the deployment of such researches include the increasing in energy consumption, environmental aspects, the integration of distributed and renewable generation, and new advances in computer aided technologies and automation. Smart Grids are characterized by a series of integrated technologies, methodologies and procedures for planning and operation of electrical networks. A survey of the main projects and researches related to Smart Grid is presented in (Brown, 2008).

Experimental Platform for Operational Analysis of Distribution Networks

The benefits provided by changes of topology are essentials to better use of all electrical system elements. In some situations, it can be observed that the load transfer results in an instant decrease of losses along of network, providing the balancing of voltage levels, becoming the network more robust. Thus, this paper presents an analysis of the applicability of optimization methods of networks using an experimental platform, developed and tested in a controlled environment.

Multi‐Objective Real‐Time Dispatching Problem in Electric Utilities: An Application to Emergency Service Routing

This chapter presents a novel application of real‐time dispatching problem to electric utilities when multi‐objective is involved. It is described how the problem related to emergency services in electric utilities is considered, with an aggregated objective function developed to handle the minimization of the waiting time, the total distance traveled, the sum of all delays related to already assigned orders, and the cost of non‐ assigned emergency orders. After that, actual cases have shown the effectiveness of the proposed model to be adopted in real‐world applications either as a search for optimal solution or by applying a heuristic‐based algorithm developed.

Control Strategies for Smart Charging and Discharging of Plug- In Electric Vehicles

This chapter aims to provide an overview of the plug-in electric vehicle (PEV) charging and discharging strategies in the electric power system and the smart cities, as well as an application benefiting both consumers and power utility. The electric vehicle technology will be introduced. Then, the main impacts, benefits and challenges related to this technology will be discussed. Following, the role of the vehicles in smart cities will be presented. Next, the major methods and strategies for charging and discharging of plug-in electric vehicles available in the literature will be described. Finally, a new strategy for the intelligent charging and discharging of electric vehicles will be presented, which aims to benefit the consumer and the power utility.

Multi-Criteria Approach For Emergency Service Orders In Electric Utilities.

This paper proposes a multi-criteria approach to handle emergency orders under real-time conditions in electric power distribution utilities. It is described how the problem related to serve work orders in electric utilities is considered, with an aggregated objective function developed to handle the minimization of the waiting time for emergency services, the total distance travelled and the sum of all delays related to already assigned orders. After that, actual cases have shown the effectiveness of the proposed model to be adopted in real world applications. INTRODUCTION Electric power distribution utilities are charged of managing customer attendance and maintenance procedures in their network. The consideration of emergency scenarios makes the problem harder especially by assuming resource constraints (human and material) and strict regulation policies that establish targets and indices related to this context. Considering that maintenance crews help to maintain the network under normal conditions, i.e., all the customers with power supply and non-technical problems associated with the electric network, emergency orders are normally related to equipment failures, overload conditions and interrupted conductors. From this context, the most relevant aspect to be considered refers to the waiting time associated with the emergency orders, since the level of injury or danger of death imposes immediate response from the network operations center (NOC). The decision-making problem involves a considerable amount of data and several aspects and criteria, all of them related to network and equipment operation procedures. This context is close to that one described by (Ribeiro et al. 1995): “decision making is a process of selecting ‘sufficiently good’ alternatives or course of actions in a set of available possibilities, to attain one or several goals”. Such a decision making process when referring to emergency services in electric utility generally involves not only the waiting time for emergency orders but also two even important aspects: the total distance traveled and the sum of all delays related to already assigned orders. The former sounds really intuitive, because the minimization of the total distance traveled by all crews improves their productivity by aggregating more time in their workday to complete the assigned orders. The latter aspect is that one associated with one contribution of this paper: the consideration of multitasked maintenance crews. They are always charged of preestablished routes that include orders known a priori when a set or emergency orders come up. This criterion of minimizing the sum of all delays represents the desired trade-off between the planning and actual scenarios, in such a way that they could be as similar as possible. This paper proposes a multi-criteria mathematical model to handle emergency orders under real-time conditions. It comprises three criteria related to this problem: the minimization of the waiting time for emergency services, the total distance travelled and the sum of all delays related to already assigned orders. This paper is organized as follows: first the emergency work order dispatch problem is described, followed by the corresponding mathematical model. After that, the heuristic approach, preliminary results and final remarks are presented. PROBLEM DEFINITION The emergency work order dispatch problem (EWODP) is carried out within 24 hours a day, 7 days a week, corresponding to a main task of the electric NOC. Assuming this non-stop period and the critical issues involved, a real time system may be suitable to assign a repair crew to each remaining emergency work order (EWO). When developing a system able to assign one order to a given repair crew, the following goals must be assumed: • Reducing the dispatch time; • Improving network security on operation and maintenance procedures; • Standardization of dispatch criteria in such a way they could be closely related to business process. Proceedings 28th European Conference on Modelling and Simulation ©ECMS Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani (Editors) ISBN: 978-0-9564944-8-1 / ISBN: 978-0-9564944-9-8 (CD) The main issue involved is the aim of reducing the average service time, which is defined as the sum of the waiting time, the travel time and of the order execution time. In this work we consider the decision problem of assigning an EWO to a given maintenance crew available, mainly focusing on the waiting time. The challenge comes from the business process usually adopted by utilities: they have multitasked repair crew generally in charge of commercial services (customer demand orders) when an EWO comes up. From this assumption follows specific characteristics that make the whole optimization problem some orders of magnitude greater in the sense of the complexity involved. In this work it is described a problem that emerge from specific characteristics of route construction to meet customer demand in the context of an electric power distribution utility in Brazil, specifically with concern to the occurrence of EWO. The main inspiration for the analysis carried out to represent and solve the EWODP track its origin from the well-known traveling salesman problem (Lawler et. al. 1985) and its famous generalization: the vehicle routing problem (Toth and Vigo 2001). In the considered utility, maintenance crews must execute a set of service orders, what remounts the construction of multiple routes. These crews have their start point in a depot that can be distinguished from each other and they do not need to return to their start point when the last service is completed. The fundamental aspect that must be considered refers to the definition of several kinds of service orders, with high importance to the ones that are not known a priori. Two different sets can be defined: those orders known a priori and related to commercial services requested by customers and those orders that have their inherently aspect of emergency, which may occur at any moment. Every maintenance crew is able to execute these two kinds of orders. When a maintenance crew begins its journey, its corresponding route to execute only those commercial orders known a priori is available. The occurrence of emergency scenarios imposes the most appropriate treatment in order to consider these EWOs that are coming up and have precedence over the commercial orders. Following the number and their corresponding geographical location of EWOs, one or more maintenance crews will be considered to complete these services and, as consequence, they will have their routes modified. The problem that arises from this context is related to the need of restructuring the existing routes only populated by commercial orders, now including the pending EWOs in the beginning of each existing route. From this perspective, two scenarios may be assumed: (1) reprogramming the set of remaining commercial services of all maintenance crews; and (2) only inserting the pending EWOs in the beginning of each route while maintaining unchanged the route related to commercial services. The first option has strict technological constraints since each maintenance crew receives a batch of orders to be executed when its journey starts and the communication to reprogram the route during the day may be a bottleneck by the existing status quo of telecommunication services in Brazil. One important definition is related to the main goal of the problem. There are several objectives that can be assumed, including those conflicting ones. One of these is reducing the waiting time to execute emergency services, exactly by the risks associated with security of the electric power network. Another objective, this one related to economical aspect, is reducing the total cost of routes, corresponding to the total time to complete all designed routes. In this case, both commercial and emergency are considered when calculating the cost. Even in this case it is already possible to note a conflict between cost and precedence of emergency services: the higher is the importance of emergency services, the greater will be the cost. The third and last aspect to be considered refers to minimizing the sum of all delays related to the previously assigned services, in order to maintain the desired trade-off between the planning and actual scenarios. Following these concepts and definitions, a mathematical model was developed as depicted below. The mathematical model developed The first assumption is that there is a given set of crews with their corresponding a priori routes, which include services called commercial orders. Given an instant of time in that a certain number of emergency orders come up, it is assumed that they will be assigned to the given crews in such a way that previous routes will not be changed. This fact will cause insertion of emergency services in the previous known routes, involving a decision of which subset will be assigned to each crew and in which position on the route. On the following mathematical model, three criteria are used to integrate the objective function: the first, weighted by W1, corresponds to the latency cost of all emergency orders; the second, weighted by W2, includes the cost of all routes; the third, weighted by W3, aims to reduce the delay when considering the time when a commercial order i is completed and the end time of each route. The following parameters are considered: 0 : dummy order to define the final destination point of every crew; Ve : set of emergency orders; Vc : set of commercial orders; Vs : set of start points, which represent the initial position of each crew; V : } 0 { ∪ ∪ ∪ = s c e V V V V R : set of routes / crews; t0 : initial time for every crew; T : end time for every crew’s workday; suc(i) : the successor point of i in the a priori route, c V i ∈ ; pre(i) : the antecessor point of i in the a priori route, c V i