Improving Reliability from View of Buyer-Seller by Optimal Reconfiguration: Applicability to Lorestan Distribution Network

Reconfiguration of distribution networks by a series of switching operations is a simple and inexpensive way to improve reliability and reduce power losses, which without the addition of additional equipment to the network, makes optimal use of distribution systems. In this paper, optimal reconfiguration is proposed to improve reliability and minimize power losses as objective functions. To demonstrate the functionality and applicability of the proposed method, five states are defined based on the trade-off between buyer-seller. Particle swarm optimization (PSO) algorithm has been used to solve this problem. Then, the proposed method has been implemented on the Lorestan Distribution Network.


Introduction *
Between 30% to 40% of the total investment in the power system is in the distribution sector. One of the leading challenges in Distribution Networks (DNs) is the proper design of the network to improve reliability and reduce power losses. The high level of power losses and the low level of network reliability are distributed over other parts of the power system (generation and transmission), * mohamadhajivand@gmail.com resulting in large charges imposed on the network. Due to the growth of electric power consumers and the constraints on generation and transmission, the DN has been exploited under overload conditions. The statistical results indicate that most power failures occurred in the DN [1]. There are several ways to reduce losses in the DN. Many methods require new equipment in the installation system, and this additional equipment, in addition to having financial burdens for companies (which may sometimes cost more social benefits), may cause new faults on the network disturbs the service to subscribers. To overcome these problems, initially, the reconfiguration method with no need to install new devices on the DN, and with the same switches, it simply reduces the cost of the losses. There are usually a number of normally open switches and a number of normally close switches in each DN. By closing some common-state switches open and opening the same number of normal shut-off switches, the power distribution path in the DN can be changed so that System losses will be reduced. Subsequently, since the DNs are always used radially, the reconfiguration should be such that the radial structure of the DN is preserved. Reconfiguration transforms the DN structure by switching the switch state. These switches can be divided into two categories: switchers (normally close) and connection switches (normally open) [2]. In fact, by changing the DN structure, the states of the switches should change. Hence, most DNs are radial across the world, because there are some ORGINAL RESEARCH ARTICLE limitations for them. Some of these limitations include the maintenance of radial structure, load balancing and nonoverloading of devices [3].

Objective Function
The main challenge at this technical stage is to introduce the objective function of the problem. The four parameters of reliability and power losses defined in the objective function are very different in quantitative terms, which are used by the normalization technique to include these parameters in the objective function. For this purpose, the values of the trivial parameters of the objective function are divided into pre-position values. With this technique, each parameter is normalized to a logical and scientific basis.
OF SAIDI SAIFI CENS MAIFI Loss (1) In some references, it is seen that weighting factors have been used to solve such problems which, given the initialization of these factors by the user (with the sum of factors equal to 1), is not a logical way to solve such problems, and in the effect of the parameters with lower values in the function the goal is reduced. By this technique values of four indices are normalized.

Objective Function
The constraints of the problem are two parts. The first part contains the constraints of distributed generation resources, which include the number and limits of active and reactive power of each source. The other part of the constraint is the permissible voltage limit on the network loads, so that during the formation of the island, the voltage on the loads should not exceed the permissible limits.
Load Flow Constraint:The accuracy of the load flow is the first step in determining the optimal capacity of the DG. However, the observance of the load flow in solving power system problems is obvious, but its expression is indicative of its importance. The relations (2) and (3) show the load distribution relations for active and reactive power.
Constraint power balance:The injectable power of bus slack and the power generated by the DG units should be equal to the generation resources with the total power consumption of network load points and network losses.

Solving the Problem by Proposed PSO Algorithm
The particle swarm optimization algorithm (PSO) algorithm is used to solve various problems in power systems. The concept of PSO is discussed [35][36]. In the following, the optimal reconfiguration of Lorestan Distribution Network problem solution by PSO algorithms discussed.
In this algorithm, initially, by entering the system information, the load flow program was done by considering the constraints of the load flow problem. Then, using the sensitivity analysis presented, the candidate buses for determining the state of the switch are determined. Finally, the values of the objective function, including reliability indices and loss based on the candidate buses, are calculated. Figure 2. shows the proposed flowchart of optimal reconfiguration solution by the PSO algorithm in order to find the state of switching in which improves the reliability indices and reduces power loss in Lorestan DN.

Simulation Results
To demonstrate the superiority of the proposed retrofit technique, a case study was conducted on the Lorestan DN. A single line diagram of this network is presented in Figure  3. For the above network, 25 loops can be defined. To determine the effect of automation switches, six states are defined for this network. These states are designed to change the number of transient faults (in terms of number per year) and the duration of fault detection (in terms of hours).

Scenario 1: Basic state
In this scenario, the definition of different failure rates and prioritization of the subscriber's study has been done.
Scenario 2: With the same relative failure rate To design this scenario, we define the entire failure rate as 1, so that the failure rate difference does not affect the results.

Scenario 3: Regardless of the importance of the subscribers
The importance of subscribers in 1, its impact on predicted outcomes. Scenario 4: With the same relative failure rate, regardless of the subscriber's importance In this scenario, the reconfiguration is carried out without considering the importance of the subscribers and the different failure rates.    According to the results obtained in Fig. 4: The best value for subscribers SAIFI is obtained in the fourth scenario of the first and third states.
The worst case is also obtained in the second scenario of the third state.
The best and worst for MAIFI are obtained in the fourth scenario of the first state and the second scenario of the third state, respectively. The best value of SAIDI is obtained in the fourth scenario of the first state, and the worst possible amount is seen in the third scenario of the fifth and sixth states.
CENS index is the best in the fourth scenario of the first state, and in the second scenario the third state is the worst. The lowest possible power losses in the fourth scenario of the first state, the third scenario of the second state and the fourth scenario of the third state are presented. The highest amount of power losses is obtained in the first scenario of the fifth and sixth states. The best possible value for the OF is obtained in the fourth scenario of the first state and the worst possible in the third scenario of the third state. Table (2) shows the status of the switch codes in different scenarios and states.

CONCLUSION
In this paper, the problem of reconfiguration of DN with the purpose of improving the capability is carried out. For this purpose, four reliability parameters are considered in the formulation of the problem, which are: SAIFI, SAIDI, AENS, and MAIFI. Also, power losses are included in the objective function. Selection of parameters has been selected based on improved reliability from the buyer-seller's point of view and improved reliability of transient and permanent faults. The problem is optimized using PSO algorithm. The simulation has been performed on the Lorestan DN with four scenarios designs. From simulation results it can be asserted that,except for the first and third states, in the rest of the states the second scenario has the best answer. On the other hand, with the exception of the first two states, the first scenario is the worst, in the rest of the state, the fourth scenario produces the worst response.