Background and Motivation

Chapter 1: Introduction

1.1. Background and Motivation

The distribution system is a vital component of any electric power system. It constitutes the final linkage between bulk power source and end customers. However, distribution is also one of the most susceptible to failures within the power system (Brown, 2008a). Therefore, power quality and continuity have become among the most important objectives that distribution utilities have concentrated significant efforts on in order to satisfy system load and energy requirements as economically as possible.

Distribution system reliability can be improved by reducing the frequency of occurrence of faults and by reducing the repair time by means of maintenance strategies (Zheng et al., 2011).

The addition of switches along the distribution network contributes to reduce the number and duration of interruptions; however, this involves investment costs. The two aspects of obtaining high level of reliability at a relatively low cost are often in direct conflict due to the fact that providing a higher reliability will cost utilities more capital.

The above statement drives a motivation to emphasize on the multi-objective optimization of utility investment costs and reliability benefits, the result of which will be a set of trade-off solutions that optimize both objectives so that the decision-maker can choose from.

Two types of line switches are normally installed along the distribution feeders: sectionalizing switch (normally closed switch) and tie-point switch (normally open switch). The former is a device that isolates a faulted section from the system so that the healthy sections upstream can

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still be electrically supplied. The latter is a device that restores power to the disconnected loads downstream the failure by transferring them to a neighbor distribution feeder without violating operational and engineering constraints.

Whenever a fault has been identified at any point of a network, acting as soon as possible may result in a minimum affected area. The process of restoring a feeder from a fault, (Bernardon et al., 2011), can be stated in the following steps:

x Identify the exact fault position,

x Isolate the faulted section by opening normally closed switches,

x Restore power supply to customers upstream and downstream of the isolated block, x Correct the problem,

x Re-operate the switches to get back to normal network status.

Automation of distribution systems significantly contributes to reduce the time to perform the service restoration procedure and utterly minimize the impact of power interruptions. With the installation of automatic or remote-controlled line switches in the network, we can experience a faster response to isolate the fault without maintenance personnel even having to physically be at the location. New regulation policies have allowed automatic sectionalizing switches to operate faster, more efficient and reliable than traditional manual switches (Romero, Wesz da Silva, &

Mantovani, 2011). Automatic switches have also shown to be an economically viable solution due to the emergence of a large number of automation equipment suppliers and new communication technologies.

A frequent topic currently discussed is how the electric power distribution systems of the future will be. In this sense the term “smart grid” has arisen to describe how the new distribution

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systems will behave, this is in a “smart” or “intelligent” manner. A deeper analysis about Smart Grid will be presented in Chapter 2, but as an introduction we can mention that among the features of the Smart Grid are the ability to carry out maneuvers in automatic mode (self-reconfiguration) and high reliability, all with low operation and maintenance costs.

The selection of an efficient methodology to determine the optimum location and number of automatic line switches is essential for utilities, since that procedure is closely related to the restoration time and consequently associated to the system reliability indices. The optimization methodology constitutes not an easy task because it is a combinatorial¹ constrained problem described by a nonlinear and nondifferentiable objective function and its solution can be challenging to solve (Tippachon & Rerkpreedapong, 2009).

Different approaches have proposed solutions for the problem of switch placement in distribution networks. Some studies develop optimization methodologies for a single objective function (mono-objective) such as minimizing economic cost or reliability indices (Chen et al., 2006), (Bernardon, et al., 2011). Other researches are focused on covering the impact of automatic switches, without considering its optimal allocation (Zheng, et al., 2011). Finally, some important studies about multi-objective allocation in distribution networks do not consider automatic switches after all (Tippachon & Rerkpreedapong, 2009), (Ferreira, Bretas, & Cardoso, 2010). The multi-criteria methodology for optimal placement of automatic line switches has not been included.

The multi-objective optimal placement of switches in distribution networks allows better operation and improvement on the reliability of the system (Ferreira, et al., 2010). Moreover, the

1 Combinatorial optimization consists, in a sentence, on finding the optimal solution among a finite set of solutions (Schrijver, 2003).

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reliability indices most commonly used to quantify the quality of the utilities services are related to sustained interruptions (interruptions longer than 5 minutes): System Average Interruption Frequency Index (SAIFI), and System Average Interruption Duration Index (SAIDI). These two indices highly depend on network topology and location of automatic switching devices.

Therefore, our optimization task will be driven to design a methodology for optimal placement of automatic line switches in distribution networks that simultaneously minimizes cost expenditures and maximizes system reliability (by minimizing SAIFI and SAIDI).

As more study on this new trend of power distribution technologies has extended around the world, Taiwan is also taking steps to become a major force in Smart Grid. According to MOEA’s Bureau of Energy, the Taiwanese government plans to invest an additional US$4.6 billion in smart power grid infrastructure starting from first quarter 2012 (Wu, 2011). This amount includes NT$123.7 billion for improvement of power grid efficiency, NT$10.1 billion for the promotion of smart grid industry and NT$ 6.1 billion for technological research and development.

It is expected that this project will create an output value of NT$1 trillion (Wu, 2011) in smart grid industry by 2030, making Taiwan an output country for global smart grid industry and equipment manufacturing.

Taiwan has a long-term experience in the ICT (Information and Communications Technology) industry which represents a solid foundation for developing the smart grid industry. However, the expertise with individual components will have to lead to research on abilities for system integration. That constitutes another of the motivations for developing the present research topic, giving the need of research in terms of network automation that will allow self-regulation, including automatic reconfiguration in the event of failures, threats, or disturbances.

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