Creg Uploaded by. Alexandra Rico. Loading Preview. Sorry, preview is currently unavailable. You can download the paper by clicking the button. resolucion creg de pdf merge. Quote. Postby Just» Tue Aug 28, am. Looking for resolucion creg de pdf merge. Will be grateful. This CREG Regulation establishes the following articles: The connection to to the network backup: CREG Resolution / – Energy supply: through a.
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The location of the estimated value of ITAD in the reliability incentives model involves certain economic impacts for the electric utility that must be quantified and analyzed.
The demand model for the load points consists of hourly active and reactive power curves, therefore, the demand for each load point in the test system was adjusted to the behavior of the typical Colombian hourly demand curve. This is because the application of the incentives and compensations scheme would cause some increases in the electricity bill of passive customers, which would be higher than the reductions in the bill due to the CU dg in most of the technologies is lower than the RC.
Considering an n-1 contingency level and assuming that the system is operating normally, it is generated for each system components a random number between 0 and 1 from a uniform distribution for that range. Finally, each operation scheme for the DG interconnection which it is desired to evaluate is simulated.
These results allow through a balance between performance and costs, contribute to feasibility studies for DG interconnection in customer installations. Rewards for good reliability can be implemented in a similar way. A repair time Tr is assigned for the faulty component, following the same procedure described in step 2. The simulation procedure described above is presented on a flowchart in Figure 2.
How to cite this article. This shows that the use of these generation sources allow to solve problems of deficiencies in the reliability supplied by utilities.
The simulation will advance from the reference moment to the Tf of the faulty component. Methodology Considerations The DG units are installed directly by customers and these units operate as backup plants, so that when the distribution system is in normal operating conditions, the DG exclusively supplies to the customer owns the plant.
This is because, despite the CU dg allows a greater variation in the bill behavior of passive customers, the application period is very short, because the DG units operate as backup plants to fault conditions in the system.
This is mainly due to the CUdg is higher or lower than the RC respectively. The problem is formulated as an optimization model of multiobjective non-linear integer type, which considers investment and operating costs, and the benefit of the concept of assets to be recognized by usage charges as stipulated in Resolution Cfeg of The main contribution of this paper is the development of a methodology orientated towards estimating and analyzing the technical impacts, on topics of reliability, and the economic impacts that imply the Cfeg interconnection, with the possibility of islanding operation, by customers of the distribution system.
In OMS, the network map is geographically visualized. It shows the High, Medium and Low Voltage grid and the base map, mapping the circuits with colors and to identify de-energized lines. Taking a given reference date and hourthe study time is initialized to zero.
SPARD® OMS | Energy Computer Systems
Hence, some countries have modified their regulatory policies to promote the installation of DG systems, allowing such plants to become competitive compared to large-scale generators.
Based on the assignation of the faulty component, the distribution system is reconfigured either to a single subsystem supplied by power system or by DG units or two subsystems the first one supplied by power system and the other one by DG plantsbasically depending on three variables: The results presented in Table 5 were evaluated with the following two assumptions: The ITAD reliability index and the incentives and compensations scheme adopted in the methodology are not evaluated quarterly as described in section II, but annually.
For this application case, the distribution system does not consider the two in-line regulators, the in-line transformer and the shunt capacitors. Distribution System Modeling 1.
This paper proposes a methodology rceg evaluating the technical and economic impacts of these generation xreg through stochastic simulation techniques to contribute to feasibility studies regarding DG interconnection in distribution systems.
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The information of the ITAD behavior for the operation scheme without DG and the second study was fitted to a weibull function of probability density. Based on the results presented in Table 3 and Figure 5it was observed that without DG interconnected to test system, the estimated value of the ITAD reliability index came within the dead zone for the incentives scheme or zone number three Z3.
Finally, it applies this methodology to a distribution system and it identifies regulatory strategies when DG interconnection is not profitable. The system registers the time dedicated to an event, the type of event, employed human resources and materials. For simulating the first assessment period, the iterative simulation procedure was applied for the same operation scheme without Xreg which was executed for years of analysis.
NSGA II algorithm; multiobjective optimization; relocation of distribution transformers; distribution systems.
The times to failure and repair times of generation units and lines, were fitted to an exponential probability density distribution. Then, the assessment periods of the reliability supplied by electric utility to its customers are simulated. To implement the proposed methodology, a computational tool was developed using MATLAB and the simulation technique of Monte Carlo sequential of mixed time.
Due to growing demand and concern over environmental pollution, new electricity generation with technological alternatives having the lowest impact on the environment is becoming a global reality. This tool consisted of two analysis schemes: If reliability is better than the dead zone boundary Z1a bonus is given.
Besides providing a set of indexes, reliability assessment can be used for determining how a system can fail, the consequences of such failure, and it also provides information for the electric utility to relate the quality of its system to capital investment Brown, Burke, For the application of these studies that consider the DG interconnection, it was necessary to define the generation technologies to be analyzed for these plants which corresponded to renewable sources, and they are presented below:.
In order to carry out the implementation of this study, it was necessary as a first step to bring up a simple key analysis for evaluating the results of the comparative method, which is shown in Figure 7.
The bonus grows as reliability improves and it is capped at a maximum value. However, if the DG units described in either of the two studies are connected, the utility should compensate to such customers with a lower annual amount over the case without DG, due to the dispersion of the reliability supplied around the mean reliability would fall.
On the other hand, the statistical parameters assumed for lines were obtained from the Billinton test distribution circuit Billinton, Allan,where the failure rates are proportional to the length.
These impacts result from implementing the compensations scheme to ”worst served” customers and they are discussed in the next section IV-C4. The simulation technique used corresponds to Monte Carlo sequential of mixed time Billinton, Jonnavithula,therefore the methodology designed was adapted to the guidelines proposed by this technique.
To simulate the reference period, it is necessary to model the distribution system without considering the DG interconnection, and the iterative simulation procedure described below section III-A is then applied. However, it should be noted that the generation sources capacities are theoretical and do not represent the construction standard capacities for these sources.
Evaluating and comparing the electricity bill of each customer, for the two operation schemes with and without DG. This will ensure a minimum level of reliability for customers. The maximum value of the demand curves for each load point correspond to its respective data provided of active and reactive power. This information is accumulated in an historic database for further analysis and for reporting.
Simulation methods generate an artificial history of the system by using computational tools, assuming probability distributions for each component which represent their operation conditions.
The worldwide acknowledgment of DG inclusion in power systems and the incentives for optimizing energy resources has received great interest. Based on the results presented in Table 5 and according to the assumptions outlined above, it was observed as expected, that the photovoltaic system represents the least profitable technology from an economic point of view, due to such technology has the highest investment costs, and therefore it has the longest time to recover the initial investment.