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Methodology for assessing the impacts of distributed generation interconnection. National University of Colombia. Candidate , National University of Colombia, luisluna84 gmail. This methodology consists of two analysis schemes: a technical analysis, which evaluates the reliability conditions of the distribution system; on the other hand, an economic analysis that evaluates the financial impacts on the electric utility and its customers, according to the system reliability level. The proposed methodology was applied to an IEEE test distribution system, considering different operation schemes for the distributed generation interconnection.

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Methodology for assessing the impacts of distributed generation interconnection. National University of Colombia. Candidate , National University of Colombia, luisluna84 gmail. This methodology consists of two analysis schemes: a technical analysis, which evaluates the reliability conditions of the distribution system; on the other hand, an economic analysis that evaluates the financial impacts on the electric utility and its customers, according to the system reliability level.

The proposed methodology was applied to an IEEE test distribution system, considering different operation schemes for the distributed generation interconnection. The application of each one of these schemes provided significant improvements regarding the reliability and important economic benefits for the electric utility.

However, such schemes resulted in negative profitability levels for certain customers, therefore, regulatory measures and bilateral contracts were proposed which would provide a solution for this kind of problem. 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 situation has led to implement the concept of small generating units located near to consumption points, incorporating the electrical system backup, as an option of great penetration in the electric sector commonly known as distributed generation DG. The worldwide acknowledgment of DG inclusion in power systems and the incentives for optimizing energy resources has received great interest. This situation has mainly been guided by environmental statutes aimed at providing greater coverage, quality and better costs for customers.

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. Although implementing DG is not prohibited in Colombia, no market schemes or interconnection technical specifications have been established for DG. The DG integration leads to a certain technical and economic impacts on distribution networks, because power systems were not designed to incorporate power generation sources into distribution levels.

Such impacts should thus be estimated and studied before allowing DG to participate in the market. Since reliability represents a key distribution system performance measurement, due to its high impact on costs and customer satisfaction, then it represents an important aspect when evaluating DG interconnection feasibility.

This paper proposes a methodology for evaluating the technical and economic impacts of these generation sources through stochastic simulation techniques to contribute to feasibility studies regarding DG interconnection in distribution systems.

It begins by providing an overview of reliability assessment and requirements of the incentives and compensations scheme due to the reliability supplied. It then describes the methodology proposed which evaluates the DG effects by a balance between performance and costs. Finally, it applies this methodology to a distribution system and it identifies regulatory strategies when DG interconnection is not profitable.

The Colombian regulatory policies established by CREG resolution CREG, , provided the rules for electric utilities concerning distribution system reliability. Such rules were defined in an incentives and compensations scheme aimed at stimulating the ongoing improvement of reliability. Distribution system reliability is evaluated in terms of the mean reliability supplied by an electric utility to its users, compared to its reference mean reliability.

Such mean reliabilities are expressed as the following indexes:. Depending on the amount of ENS during a calculation quarter regarding the reference level, an incentives scheme will be applied to the electric utility allowing it to receive a bonus or a penalty. The incentives scheme consists of a dead zone Z3 where neither a penalty nor a bonus will be assigned. If reliability is worse than the dead zone boundary Z2 , a penalty is assessed. The penalty increases as performance worsens and it is capped when a maximum penalty is reached.

Rewards for good reliability can be implemented in a similar way. If reliability is better than the dead zone boundary Z1 , a bonus is given. The bonus grows as reliability improves and it is capped at a maximum value.

The scheme so described is presented in Figure 1. The incentives scheme is complemented by a compensations scheme to ''worst served'' customers, which seeks to reduce the dispersion of reliability supplied by an electric utility around its mean reliability. This will ensure a minimum level of reliability for customers. The regulatory scheme's object is to ensure ongoing improvement reliability.

This allows electric utility to increase historic levels of reliability for the whole distribution system. The incentives and compensations applied to electric utility are directly included in customers' electricity bill, therefore, they are who promote the reliability improvement.

The object of electrical network reliability assessment is to determine indexes reflecting the electricity continuity on distribution systems, substations, circuits or defined regions.

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, By doing so, a utility may have a more efficient distribution system and greater knowledge about its system's operation. Reliability evaluation techniques can be based on analytical methods or simulation methods Billinton, Jonnavithula, Analytical methods generally involve base conditions and include a combination of reliability parameters of the system components by applying mathematical tools that quantify the reliability supplied.

It is also used as reference, state diagrams, logic diagrams, etc, depending on the case and accuracy required. One of the most popular techniques in systems evaluation using analytical methods is called the Markov model. Simulation methods generate an artificial history of the system by using computational tools, assuming probability distributions for each component which represent their operation conditions.

One of the most popular techniques in systems evaluation using simulation methods is called Monte Carlo. Both methods have advantages and disadvantages depending on the scenarios considered, the system features, the available tools and the desired accuracy in studying a particular system, which should be considered when choosing a reliability evaluation method. The proposed methodology consists of a technical and an economic analysis scheme.

The technical analysis evaluates the distribution system reliability conditions and the economic analysis evaluates the financial impacts on the electric utility and its customers, according to system's reliability level.

In order to carry out the methodology application, it is necessary as a first step to simulate a reference period leading to determine the reliability level annually provided by the electric utility to its customers. However, if the utility has historical information about its reliability behavior, then this step is unnecessary.

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. Then, the assessment periods of the reliability supplied by electric utility to its customers are simulated.

For simulating the first period, the iterative simulation procedure is applied for the same operation scheme without DG , which is executed until the number of preset iterations is fulfilled for example, Finally, each operation scheme for the DG interconnection which it is desired to evaluate is simulated. For each scheme, it is necessary to model the distribution system considering three variables:. Once the distribution system with the DG interconnection has been modeled, it is applied the iterative simulation procedure which is executed until the number of preset iterations is fulfilled.

On the other hand, the following variables are calculated: financial incentives and compensations for the electric utility, and the customers' electricity bill. These variables allow evaluating the behavior on the electricity bill of each system customer, and the behavior on financial benefits or penalties for the electric utility due to reliability supplied.

The simulation procedure described above is presented on a flowchart in Figure 2. These results allow through a balance between performance and costs, contribute to feasibility studies for DG interconnection in customer installations. The incentives and compensations scheme CREG , described in section II, which promotes the improvement in the reliability supplied by electric utility.

The tariff scheme for energy commercialization in the regulated customers CREG , 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. This is because the period of time defined for each Monte Carlo iteration is one year.

Methodology application. For this application case, the distribution system does not consider the two in-line regulators, the in-line transformer and the shunt capacitors. Additionally, all the loads are considered ''spot''. For the system components such as generation units, distribution lines and transformers, a two states model is used to represent their availability, which is shown in Figure 4. This model is equivalent to a continuous time process for a repairable component, and it is constructed from historical information about output events and their corresponding reconnection times.

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. The times to failure and repair times of generation units and lines, were fitted to an exponential probability density distribution.

Electrical Model of Components and Demand: The traditional models for load flow are used, therefore, the positive sequence of impedances and admittances for lines and transformers is required. 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.

The maximum value of the demand curves for each load point correspond to its respective data provided of active and reactive power. In order to carry out the methodology implementation, initially, it was necessary to simulate a reference period because there was not historical information regarding the reliability supplied. To simulate this reference period, the IEEE test feeder was modeled without considering the DG interconnection, and the iterative simulation procedure described in section III-A was then applied.

This reference period led to determining among others, the dead zone for the incentives scheme that is shown in Figure 5. Next, the assessment periods of the reliability supplied by electric utility to its customers were simulated. For simulating the first assessment period, the iterative simulation procedure was applied for the same operation scheme without DG which was executed for years of analysis. After, two assessment periods were simulated which considered different operation schemes for the DG interconnection in the test system.

For simulating each of these periods, the iterative simulation procedure for years of analysis was applied. The characteristics of the DG units considered in each of these schemes are shown in Table 1. However, it should be noted that the generation sources capacities are theoretical and do not represent the construction standard capacities for these sources. The first study implies the simultaneous installation of four DG units, located in the test system customers with the highest electricity consumption.

The capacities of these generation sources allow supplying the total demand of the distribution system in a fault condition in the power system. This interconnection scheme represents a very optimistic condition, because it evaluates the simultaneous installation of four DG units in a distribution system as lightly loaded as the one designed by the IEEE.

On the other hand, the second study considers the simultaneous installation of four DG units, located in the same customers with the highest demand. However, this study assumes that the capacities of the DG plants adequately represent the peak demand of the respective plant owner customers, which is a more realistic situation. 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:.

Also, it was required certain information of the DG technologies considered. This information consists of the investment and generation costs of each technology, which are presented in Table 2 Corredor, The technical impacts for system were quantified by the reliability index ITAD , which was assessed for each operation scheme in study with and without DG. The results of this analysis are presented in Table 3. Based on the results presented in Table 3 and Figure 5 , it 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.

The execution of the first study would imply large reductions in the estimated value of the ITAD , regarding the reference conditions offered by the dead zone. This produces that the mentioned value take place on the left hand edge of zone number one Z1 , because the operation scheme designed for this study led to ensuring an excellent reliability for system customers. The application of the second study would bring small reductions in the estimated value of the ITAD reliability index, regarding the reference conditions offered by the dead zone.

This produces that the mentioned value takes place on the right hand side of zone number one Z1 , because the operation scheme designed for this study does not provide great benefits to the test system reliability, however, it represents a more realistic situation.

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