In the last decade, a great technological revolution began in the world scenario of electricity distribution with the introduction of smart grids, also known as Smart Grid. In Brazil, this scenario began with electronic metering, whose operational impacts range from changes in the volume of services to the types of vehicles and tools used, due to reduced readings, remote cutting, fewer inspections, among others, impacts that are still poorly studied and quantified.
Two needs then arise: knowing such impacts and seeking solutions to adapt to the new scenario. For this, it was necessary to build a specialized system to implement the operational solutions resulting from this research, bringing benefits in the quality of service through the reduction of the service time of the field teams; in economic efficiency, with the reduction of transportation costs of the units; and the environment, with the reduction of CO emissions2 in the atmosphere from the reduction of the distances traveled.
In this way, the main objective of the study was the definition of the new logistics network of bases and construction sites with a view to the development of new electronic measurement technologies (Ampla Chip and Smart Grid) capable of meeting the distributor's service strategy for the coming years through an integrated logistics chain. In addition, the research sought to test new operational parameters in order to understand how changes in the network contribute from the point of view of costs, services and the environment. And to measure these impacts, an optimization tool was developed, whose objective is also to facilitate the process of planning the logistics network.
The construction of the tool, which does not exist on the market, required studies in the area of applied mathematics, electronic measurement, smart grid, logistics and the environment.
THE TOOL
In order to represent the energy distribution support operation and simulate future scenarios optimizing costs, CO emission2 and service time, a linear programming model was built. The software chosen to carry out such programming was Aimms due to its technical qualities and the friendly way it can be built for the user. Currently there are several important models of linear programming, however, this one was created exclusively to represent the operation to support the distribution of electric energy and to analyze the impact of new technologies on the distribution network.
The use of the model, called Model Efficient Operating Bases, as a planning tool, it allows several scenarios to be tested to represent the future operation. And the combination of a set of possibilities, such as variations in specific parameters, configuration of facilities available for model selection or even assumptions about the operation, generates countless scenarios. Consequently, a flexible and user-friendly system was needed.
The optimization model considered all relevant trade-offs for defining the best logistic configuration and aimed to minimize the operational and/or environmental costs of the energy distribution support operation, not forgetting the desired level of service. And, to meet the sector's demand, the model was developed to serve three different objective functions:
- Minimize Logistic Cost
- Minimize Environmental Cost
- Minimize Logistics + Environmental Cost
The logistical cost corresponds to the sum of the structure, backoffice and operating costs, the first two consisting of a fixed portion, which depends only on the opening of the location, and another variable portion, depending on the volume of services performed by the base or contractor. The operating cost is directly related to the productivity of the teams, and therefore depends on the number of teams needed to meet the demand for different types of service.
The environmental cost refers to the emission of CO2 equivalent in two different situations in the operation of Ampla: in the displacement of the teams between the location and the municipality, that is, between the base or contractor and the first service point (and consequent return of the team) and in the displacement carried out by the teams between execution of services, that is, between service points in the same municipality. The CO emission cost2 equivalent used in the project, BRL 8,00/ ton CO2, refers to the planting of two trees, in addition to maintaining the planted area.
Thus, based on these objectives, results were obtained such as: the location of the bases, location of the construction sites, the volume handled in each of the facilities, the service flows, the service time, the emission of CO2 equivalent and the costs of the operation.
In addition, the model has several input parameters that can be sensitized to assess the impacts on the operation, such as: demand for each type of service provided, capacity to service the facilities, capacity to provide the service of the teams, service times, location facilities potential, structure costs, personnel costs, operating costs, distances and CO2 emission coefficients.
Figure 1 shows the interface screen of the optimization model in the AIMMS software. Through this screen, the user can execute the main procedures related to the model. The Model interface in Aimms has some user interaction buttons, with the objective of facilitating the relationship with the database and the generation of scenarios.
Figure 1 – Interface of the operational impact assessment tool applied at the Ampla distributor
Source: Project ILOS/Ampla 2011
The tool presents strategic level decisions with an annual planning horizon and outputs of quantity, size and location of the new logistics network. And it reaches a tactical level, through the outputs of time and service region of each of the proposed bases and construction sites.
This tool was applied in Ampla's operations, however, the fact that the model is parameterizable allows it to be used for different concession areas, or even different energy distribution concessionaires. The application in another distribution company depends only on the survey of operational parameters for input in the tool. Mathematical and computational modeling is prepared to evaluate operations with or without Smart Grid and Wide Chip technologies. It is even possible to assess the impacts on the logistics network, both in the location of bases, construction sites and other technological changes, as long as the impacts of these changes on operational parameters are known.
RESULTS
Ampla's logistics operation covers more than 60 municipalities in the State of Rio de Janeiro, 17 service bases (Ampla) and 13 construction sites (Partners). Massive billing activities, new connections, collection, losses, maintenance (including tree pruning), works and emergency and new technologies were analyzed. Several scenarios were tested, run and analyzed throughout the study and the Ampla Chip, Intelligent Network and Environmental scenarios were detailed in this article.
NEW TECHNOLOGIES SCENARIO WITH BROAD CHIP INCREASE
The Ampla Chip is an electronic measurement technology that was developed by Ampla and, in the beginning, it was a relationship program with electronically billed customers based on the instantaneous availability of consumption information, which generated a significant reduction in energy losses and improvements in the fundraiser. There are many benefits of the Ampla Chip: a) operational benefits: reduced reading costs, reduced estimated readings, improved quality of emergency service, improved meter accuracy, reduced load analysis costs, and lower cut and reconnection costs; B) Better electrical planning: lower investments in generation, transmission and distribution assets, greater effectiveness in the application of “load smoothing” programs and savings in load projection; w) new recipes: load information services for customers and measurement for other distributors (water, gas).
To build this scenario, growth in Ampla Chip and expansion to other regions were considered, according to the percentage of loss in each region. An increase in Ampla Chip was estimated for all regions with a percentage of losses greater than 20%.
The increase in Ampla Chip affects several activities, for example: when the number of Ampla Chip customers grows, the amount of immediate reading service and cuts decreases, as well as increases activities in the wide network and deliveries. Figure 2 shows the loss percentage and the increase or decrease of each activity with the entry of the Ampla Chip.
Figure 2 – Percentage of losses in energy distribution and impact with increased technology
of the Ampla Chip
Source: Project ILOS/Ampla 2011
Several Ampla Chip growth scenarios were carried out, and the optimal result brought financial gains and modified Ampla's service network with the closure of two bases and two existing construction sites, as well as the opening of five new construction sites. That is, it remained with 15 bases, out of the 17 existing ones, and the construction sites went from 13 to 16 locations.
NEW TECHNOLOGIES SCENARIO WITH SMART NETWORKS
In this scenario, an increase in Smart Grid demand was analyzed. The smart grid is an energy project for the cities of a sustainable, rational and efficient future. It is a flexible electrical network, more reliable, highly automated and fully integrated in terms of centralized control, diagnosis, repair and remote management of meters.
There are several benefits, among them: early identification of network outages and, therefore, their minimization; reduction of energy losses, including the famous “cats”; real-time presentation of consumption, the tariff charged by the operator at that time and the volume of energy sold to the system throughout the month. The consumer, on the other hand, has a more transparent system and can manage his expenses. Currently, the rate is the same throughout the day. With the new model, it must be differentiated by time, as with telephones.
To build this scenario, an increase in the use of Smart Grid technology was considered for the 15 municipalities with the highest per capita income (Source IBGE) among those served by Ampla. The use of technology proportionally impacts the demand for other services. The increase in the smart grid affects several activities, for example: with the expansion of the smart grid number, the amount of immediate reading service and cuts decreases, as well as increases the activities of works and maintenance. Figure 3 shows the selected municipalities and the increase or decrease of each activity with the entry of the Smart Grid.
For each of the 15 municipalities, a growing demand for Smart Grid was considered. Ampla currently has a pilot project in Búzios that serves around 10.363 Customers: 13 industrial, 1.518 commercial and public services and 8.832 residential.
Figure 3 – Potential municipalities and impact with the increase in Smart Grid technology
Source: Project ILOS/Ampla 2011
Smart Grid growth sensitivities were performed. And, the optimal result for this scenario also generated financial gains and modified Ampla's service network with the closure of two existing construction sites and the opening of five new construction sites. That is, there was no change in the number of bases, remaining with the existing 17, and the beds increased from 13 to 16 locations.
ENVIRONMENTAL SCENARIO
The environmental optimization scenario used the environmental cost exclusively as the objective function.
To calculate the emission, it was identified which type of vehicle each operational team of Ampla uses to respond to calls. Next, together with Ampla, information on the greenhouse gas control report on the emission rate of light and heavy vehicles was collected. For light vehicles, a CO ton factor was considered.2 per liter of fuel of 0,00217 (ton CO2/L) and an average consumption of 11 Km/L. This generated a CO emission coefficient2 per km driven from 0,0001973 (ton CO2/KM). As for heavy vehicles, the CO factor2 per liter of fuel was 0,00266 (ton CO2/L) and the average consumption was 8 km/L, reaching a CO emission coefficient2 per km traveled from 0,0003331 (ton CO2/KM).
In this way, the optimal result for this scenario saw a large increase in the number of installations, from 17 to 21 operational bases, and the construction sites increased from 13 to 23. With a gain of more than 9% in CO emission2 as seen in Figure 4. However, there was an increase in operating costs. This scenario shows the greatest environmental gain, however, other scenarios were generated bringing in addition to CO reduction2 (about 7%), financial gains.
Figure 4 - Result of CO2 emissions in the environmental optimization scenario
Source: Project ILOS/Ampla 2011
CONCLUSION
The Efficient Operational Bases Model considers all relevant factors and existing restrictions to simulate the energy distribution support operation and generate future scenarios. The built tool is parameterizable and has a friendly interface, so new scenarios can be easily generated and it can be used in other companies in the sector. The tool is applicable in annual strategic analyzes for budget discussion and operation strategy with a focus on the logistics network. As the tool has a multi-objective character, it can be used to help decisions to change the logistics network with a focus on cost reduction, reduction of CO emission2 or in the reduction of service attendance times.
Electronic metering technologies generate a significant reduction in energy losses and improvements in collection, which is why the Ampla Chip and Smart Grid scenarios are operationally viable and profitable. In addition, it is necessary to evaluate the necessary investments for the implementation of these new technologies, and for Ampla, the electronic measurement Ampla Chip is well known and currently used and Smart City is a new technology with a pilot project in Brazil located in Búzios, Rio of January.
In addition to financial savings, the scenarios can generate environmental gains with the reduction of CO2 issued and gains in the level of service with the reduction in service times.
BIBLIOGRAPHY
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