THE ROLE OF FRAMES IN ANALYZING METAPHORIC LANGUAGE LANGUAGE

The selection of automation resources to be used and allocation of these resources is very important. The methods or criterion used for the selection of automation resources determines the extent to which the reliability of the feeder will be improved, as well as the methods used in deciding where to position switches on the feeder.

These two factors are the most influential factors or FA planning, as they also influence the investment decision to be made for FA. For example:

Two automated and manual operated switches positioned X distance and XY distance respectively will result to certain SAIDI improvement and cost a certain amount.

Therefore there is a need to investigate methods that have been used to select and allocate automation resources. In this section we will review the theory relating to methods used in placement of switches and selection of resources.

OPTIMAL PLACEMENT OF LINE SWITCHES FOR DA SYSTEMS USING IMMUNE ALGORITHM

Abstract: “To enhance the cost effectiveness of the distribution automation system. This paper proposes the Immune Algorithm (IA) to derive the optimal placement of switching devices by minimizing the total cost of customer service outage and investment cost of line switches. The reliability index of each service zone defined by boundary switches is derived to solve the expected energy not served due to fault contingency, and the customer interruption cost is then determined according to the customer type and power consumption within the service zone. To demonstrate the effectiveness of proposed IA methodology to solve the optimal placement of line switches, a practical distribution system is selected for computer simulation.” [19] Cha-Shun Chen & Chia-Hung Li, Pg. 1209

With the complexity of distribution feeders, the placement of line switches becomes very difficult and tedious problem to be solved by the conventional optimization techniques because of voluminous combinations to be investigated.

Several approaches have been proposed to solve the problem of switch placement for distribution systems. To mention a few:

1. A decomposition approach. [20]

2. A reliability cost/worth approach. [21]

3. A value based method. [22]

However most of these efforts deal with the manual line switch placement by considering the customer interruption cost or system reliability enhancement. [19]

The author proposes the An Immune Algorithm (IA) based decision making method, to find existing manual operated switches to be automated on the network and determine optimal placement of automatic/manual switches. [19]

The IA method enables the planner to consider the placement of both manual and automatic switches. From this paper the author states that “the effectiveness of the immune algorithm to solve involved optimization problem has been illustrated in many case studies and always showed to be the best method.” [19] Cha-Shun Chen & Chia-Hung Li, Pg. 1210.

However the approach on this paper is from an economical point of view, so economic functions are used. The IA method is also used to determine automatic/manual switches.

From this paper IA seem to give more advantages. These advantages are also discussed in this paper and results of the IA are compared to Genetic Algorithm (GA). [19]

IMMUNE ALGORITHYM

The IA uses the same principle as the human immune systems, to solve problems. Its capability to recognize and memorize patterns gives it a strong competitive background to deal with optimization, compared to other methods. [19]

“The objective function and limit constraints are represented as antigen inputs, while the solution process is simulated by antibody production in the feasible space through the genetic operation mechanism. The calculation of affinity between antibodies is embedded within the algorithm to determine the promotion or suppression of antibody production. From the IA computations the antibody that most fits the antigen is considered as the solution for optimization problem.” [19] Cha-Shun Chen & Chia-Hung Li, Pg. 1211

“The population of memory cells is a collection of the antibodies (feasible solutions) accessible toward the optimality, which is the key factor to archive fast convergence for global optimization. The genetic coding structure for the IA is adopted. Diversity and affinity of the antibodies are calculated during the decision making process to find the optimal switching placement.” [19] Cha-Shun Chen & Chia-Hung Li, Pg. 1211

The IA method is explicitly defined and explained in this research paper and for further reading the references on the research paper can be used. Though on this paper the author also defines a reliability assessment method, it looks at all reliability aspects and data required for implementing IA. That is outage rates, outage duration, feeder topology &

switching locations, customer load patterns load percentage of each customer class. All of this data is used to calculate the customer interruption cost and the cost of reliability.

This information is used as input data to IA, hence then will compute and determine number of switches to be automated and position of switches.

Results Obtained

The Tai-Power distribution system before feeder automation with 11 feeders 92 segments 90 load points shared between residential, commercial and several key customers in the switches reduces to 21, tie switches remains as 6 and 16 automatic switches are introduced.

The results shows that networks SAIFI has improved from 0.231 to 0.157 interruption/yr.

and SAID has reduced from 32.233 to 20.872 min/yr. Furthermore it is noted that adding the number of automated switches and re-positioning improves the reliability of the network. [19]

Due to adoption of FDIR application using IA, the total cost of reliability has been reduced from $ 460257/yr. to $ 207754/yr., the customer interruption cost decreased from $ 454063/yr. to $193438/yr. and the investment cost of line switch changes from $ 6194 to $ 14326. [19]

Conclusion

From the conducted test in examining the IA method, results were obtained, from these results it can be concluded that the SAIDI & SAIFI of the system has improved. The customer interruption cost is reduced. This shows the effectiveness of the immune algorithm in determining the best switch placement.

In essence the importance of finding ideal position for switches and determining the mode of operation is shown by the results of the power system before and after automation process.

A RELIABILITY COST/WORTH APPROACH TO DETERMINE OPTIMUM SWITCHING PLACEMENT IN DISTRIBUTION SYSTEMS

Abstract: “Nowadays automation in distribution systems is growing largely. Automated and remote controlled switches play prominent rules in automated distribution systems. By opening and closing the remote controlled switches in emergency states when a fault has occurred we can manage faults and restoration process in order to minimize interruption time and costs.

In normal states feeder load management and power loss minimization can be controlled by these remote controlled switches. Finding optimum numbers and optimum locations for installing these switches is the main concern of this paper.

Up to now a number of algorithms have been developed for optimum switch placement. In this paper a reliability based approach is presented to determine optimum number of switches. The cost of switches versus the worth (benefit) of implementing them are considered in this analysis. The best locations of switches are determined by powerful heuristic algorithm.” [21] A. Moradi, M. Fotuhi-Firuzabad pg.1

In this context the main reason for automatic switches devices is to improve system reliability i.e. improvement of availability of feeder or MV network during faults or maintenance. [21]

“The determination of optimal number of switches and locations is a very complex problem, because of a large number of variables involved in decision making and mathematical complexity of algorithm used.” [21] A. Moradi, M. Fotuhi-Firuzabad pg.1

This problem has received quite a lot of attention and a lot of methods have been developed and tested. The complexity of these methods still remains a problem to solve.

[23], [24].

The author in this paper they separate or treat the number determination of switches as one problem and determination of the positions for these switches as another. [21]

The simulated Annealing algorithm is used to determine best positions to place sectionalising on distribution feeder. The determination of the number of switches is

Optimum Number of Switches:

The main objective of optimum number of switches is to have least switches for optimum reliability and cost.

“System expected outage cost to customers due to supply outage (ECOST) is used as an objective function that should be minimised by Simulated Annealing Algorithm.

ECOST takes into account consideration the system topology, interruption duration, load variations, random failures and also recognizes the various customer types.” [23] R. Billinton and S. Jonnavithula Pg. 1647

A brief demonstration of algorithm in determining the optimum number of switches is shown on a figure below.

Case Study and Results:

In order to determine the effectiveness of the method proposed for determining number of switches, two case studies are conducted:

Case 1: Breakers and sectionalizing switches without loop switches (tie switches).

Case 2: Breakers and sectionalizing switches with loop switches and alternative paths.

It is shown from the results obtained in this research paper that the system reliability increases when loop switches are included, and this is so because the isolated sections can be energized through alternative paths. Secondly the number of switches in the second case is more that of the first case. [21]

“The total cost of sectionalising switches is determined over a period of 15yrs and annual cost is also determined for the 1^st case, were number of switches is 9 loss of worth is $ 1540.6 which is greater than $ 1355.8 the cost associated with one switch.” [21] A. Moradi, M.

Fotuhi-Firuzabad Pg. 4

Conclusion:

FEEDER SWITCH RELOCATION FOR CUSTOMER INTERRUPTION COST MINIMAZATION

Abstract: “Most electricity services interruptions are due to failures in the distribution networks. In a competitive market, service quality and reliability have become an essential part of the business. In order to enhance the reliability in the distribution systems a value based method is proposed in this paper to take load distribution changes into account and search for new locations of feeder sectionalizes such that the customer interruption cost can be reduced. Two stages are involved in search. Using local information, the first stage determines the search direction and the second stage decides whether a crossover of the load point is beneficial.

To avoid being trapped in a local minimum a mutation technique is also applied to look for global optimum. Actual feeders here were used in conducting a test for the method, and tests result show that with a proper adjustment of the feeder Sectionilizers, service reliability can be improved and the customer outage costs are reduced.” [22] J.H. Teng and C.N. Lu Pg. 254

Sectionilizers are mostly used to divide a feeder into sections in order to improve service reliability. Though a certain number of these sectionalizing switches need to be known as well as their position on the feeder needs to be known.

Therefore a planning method of these switches is to be determined. While there are many methods to determine switch operation for loss minimization and service restoration. There are only a few that addresses the number required and position of the switches. [26], [30]

To mention a few that some are already been reviewed in this document:

• Four rules to help locate protective devices. [28]

• A genetic algorithm based sectionalizer planning method. [29]

• A simulated annealing algorithm for optimal switching device placement in radial distribution systems. [27]

•

The selection of the number of switches and their position is not an easy task as it involves a lot of combinatorial methods that are nonlinear and not differential. [22]

“In feeder switch planning, the size, number, and locations of the Sectionilizers are determined on some estimations of the feeder load growth and distribution. Since the feeder configuration and land usage will evolve, after a long term service, the spatial distribution feeder loads may be different from that used in the original design.

Thus the locations of feeder Sectionilizers have to adapt to the changes in order to achieve the best results.” [22] J.H. Teng and C.N. Lu, Pg. 254

Solution Algorithm:

To determine new positions for sectionalising switches, a two stage method is used, each involving a heuristic rule.

Using feeder information the 1^st heuristic rule determines the search directions and the 2^nd one decides whether a crossover of the load point is beneficial. [22]

For a better and clear explanation on these search rules and the method used more and detail reading can be done from. [22]

Case Study and Results:

After the application of the proposed method it is seen that the reduction of CIC is archived not only by rearrangement of switches for better section lengths and loads but also by load composition in each section.

Therefore it is very important to consider the load composition of each section in a feeder.

From the test carried out the CIC of the used feeder was $ 2219796 and after location and re-arrangement of 4 out of 6 switches, the CIC was reduced to $ 2029044.55. Therefore

Conclusion:

The value based method that is proposed reveals that indeed the CIC can be reduced by re-arranging or determining new positions and new number for the sectionalising switches, though the art behind this reduction is better understanding of load composition on the feeder I.e. knowing the type and position of loads on a feeder.

2.5 C

The chapter is commenced by discussing the application of DA and operating ideology of FA and explaining the FLIR functions of feeder automation technology. A diagram is presented showing how the FLIR functions operate in locating a fault and restoring power to the healthy sections of the feeder.

We defined restoration service restoration under the concept of FA. The literature demonstrate that restoration can be done in different ways depending on reliability improvement targets of a feeder, different levels of automation can be set, that is a network planner can decide on how a feeder should be automated.

The value based reliability method was discussed as FA is aimed at improving the SAIDI of a feeder. The SAIFI and SAIDI indexes were detailed and formulae were therefore discussed. The literature will comprise the reliability section of the method.

Research papers pertaining formulation and definition of methods for selection and positioning of sectionalising and automation are discussed. We have realized that there are many methods that can be used, and they all give different results.

This literature forms the essential part of the research, due to the reading that’s been done so far it perceived that the method for selection and positioning of sectionalising switches is the very important in archiving success from FA. Therefore as the load will change in the future and feeder configuration will also change, the switches will be re-arranged hence knowing how to determining the position of the switches on feeder is crucial.

In this chapter we have looked at the literature guiding this study, in preparation to define the planning method for FA, as discussed in the Chapter 1. We have covered existing theories pertaining the study no new hypothesises were defined, as these theories will not

3 CHAPTER 3: THE PROPOSED METHOD

“Reliability Based Planning Methodology for Distribution Feeder Automation.”

3.1 I

A

O

Extensive research on Feeder Automation has been done, with interest of improving the reliability of distribution network. Most utilities throughout the world have embarked on FA pilot projects, strategies of implementing and validating the cost/benefit of FA.

From a network planning perspective informed decisions on solutions that will improve the reliability status of the network has to be made. Decision is based on technically sound, cost effective, and sustainable solutions that address a need. Ensuring that the solution to be implemented will reduce customer exposure to network faults and thereby improving the performance of network. In this regard there are methods and guideline that guides a planner toward the best solution.

Therefore a method intended at assisting a planner to know how to plan for FA i.e. best investigate the feeder for optimum application of FA technology, thereby motivating for selecting FA as the best applicable reliability solution, has to be developed.

The main aim of the method is to bring to the planner all the aspects of FA, which a planner should consider when planning for FA, i.e. which fine points of the network and FA technology a planner should consider in coming to conclusion on how FA will improve the reliability of the network.

From the gathered literature, it can be somewhat concluded that a planning method must address, how a network planner will implement FA looking at half or full implementation of FLIR functions of FA, i.e. upstream restoration or downstream restoration. Secondly it should address how to decide on the number and positioning of sectionalising and Auto reclosing switches. Thirdly it should somehow address the voltage and overloading problems, that how can restoration be done without coursing disturbances relating to voltage deeps and

In this chapter we will define the method and discuss in a high level the functions of the building blocks of the proposed method. Furthermore we will explain in a flow diagram how each building block comes to part in formulating a method. This chapter will look at questions that were raised in chapter 1, and also look at how the literature discussed in chapter 2 comes to play in defining the method.