Providing Strategic Algorithms in order to Optimize and Manage the Lighting Network based on the Balanced Scorecard Using GIS Software; Case Study: Electricity Distribution Company of Kermanshah

Introduction
Daylighting is so essential in our lives that causes to improve security and life quality in our societies. So, meeting this need is very important which requires data about the number of lights and lighting systems installed, replacement period of each lamp and other costs associated. In order to achieve that, we record lighting network as location-based data in a data-base. With recording the data in geodatabase, the useful information could be driven from row data. As a matter of fact, the information mentioned before can predict costs and replace operation budgeting instead of traditional budgeting.
Research Methodology Since 1388, Kermanshah Power Distribution Company (KPDC) has begun to gather the attribute and location based data of distribution network elements, such as number of lighting pole and lighting lamps in order to create GIS database. In this study, first, the road lighting network data including: region area, number of subscribers, number of lights, the suggested lights power, the length of low power lines, lights per consumer, light per region area and light per the length of low power line were driven from GIS database. Secondly, this information was analysed based on financial factors. Finally, the novel algorithm was introduced based on Balanced Scorecard (BSc), which has been introduced by Kaplan in 1990 (Figure 1), to optimize lighting consume management. This method evaluates lighting consume management based on financial performance, internal process, customers and growth and learning.
Figure 1: a four-way Balanced Scorecard to achieve the vision and goals of the company In the BSc approach, organizations can be divided into four different funds, these funds are:
- Financial
The formulas 1, 2 and 3 were designed to estimate the cost of repair and maintenance of street lighting in Kermanshah city using statistical information which have obtained from, KPDC GIS database. The distribution of lighting in the southern part of Kermanshah city was illustrate in Figure 2.
Formula 1:
The cost of replacing a 100-watt incandescent lamp
lamp cost1=(HL/L*PL)*SL+PU/4
Formula 2:
The cost of gas and mercury lamps
lamp cost2=(HL/L*PL)*SL+PU/4+1/3 OCOV+1/2 OCH
Formula 3:
The cost of sodium lamps
lamp cost3=(HL/L*PL)*SL+PU/4+1/3 OCOV+1/2 OCH+1/2 OIG
Figure 2: distribution of lighting in the southern part of Kermanshah city
- Customer
The KPDC uses an annual questionnaire to measure customer satisfaction of lighting. Customer Survey is being used to check BSc.
- Internal business processes
In this section, BSc analyses the KPDC data by some indicators to evaluate lightening that shows the lightening qualities and quantities. Based on these reports, the actions can be planned to improve and develop lighting network for achieving customer satisfaction.
- Learning and development
Also, in learning and development section the amount of short course efficiency was measured by evaluating 12 factors and the amount of manager’s satisfaction of each employee was scored between 0 and 100. Then, by analysing the average scores of the efficiency of each course the usage of them can be shown.
Conclusion
To conclude, by combination of the BSc and the GIS reports, an algorithm was created for Performance-based budgeting in KPDC. This algorithm was suggested to improve management in different parts of the company. Finally, operating budgeting and programmability was recommended to achieve longterm goals in the lighting network in the city of Kermanshah.
Figure 3: algorithm for optimization strategic management of lighting