International Journal of Electrical and Electronics Engineering Research (IJEEER) ISSN(P): 2250-155X; ISSN (E): 2278-943X Vol 4, Issue 1, Feb 2014, 229-240 © TJPRC Pvt Ltd DISTRIBUTION SYSTEMS RECONFIGURATION USING PARTICLE SWARM TECHNIQUE N VIKRAMAN1 & E ANBARASU2 Assistant Professor, KTVR KPET College, Coimbatore, Tamilnadu, India SVCE, Sholinghur, Vellore, Tamilnadu, India ABSTRACT This work represents the Distribution System Automation (DSA) that is being carried out very seriously throughout the world to enhance the reliability of the system and to minimize the huge losses that occurs in the Distribution System The Basic concept of distribution reconfiguration is to arrive at the best set of sectionalizing switches to be opened for a given set of tie switches such that the system performance in terms of loss reduction is enhanced The flow on a switch is just taken as a loop flow on the link branch for this work For this work the algorithm consists of two steps At the first step, all the tie switches are closed to form a meshed network and then an optimal matching loop flow is calculated to determine which switches are most suitable to be opened A practical criterion is developed to deal with the problem in opening switches on a common path shared by different loops To further optimize the network, optimal matching loop flow for radial network is again introduced at the second step and at the same time, a radial network structure is maintained with all loads energized The Particle Swarm Optimization (PSO) algorithm is used in this work to solve the optimal network reconfiguration problem for power loss reduction The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems It is a population-based approach The PSO was inspired from natural behavior of the bees on how they find the location of most flowers The proposed PSO algorithm is introduced with some modifications such as using an inertia weight that decreases linearly during the simulation This setting allows the PSO to explore a large area at the start of the simulation A modification in the number of iterations and the population size is also presented KEYWORDS: Distribution System Automation (DSA), Particle Swarm Optimization (PSO), Distribution System, Reconfiguration INTRODUCTION The area under discussion of minimizing distribution systems losses has gained a great deal of attention due to the high cost of electrical energy and therefore, much of current research on distribution automation has focused on the minimum-loss configuration problem There are many alternatives available for reducing losses at the distribution level Reconfiguration, capacitor installation, loads balancing, and introduction of higher voltage levels This research focuses on the reconfiguration alternative Two types of switches are used in primary distribution systems There are normally closed switches (sectionalizing switches) and normally open switches (tie switches) Those two types of switches are designed for both protection and configuration management Network reconfiguration is the process of changing the topology of distribution systems by altering the open/closed status of switches Because there are many candidate-switching combinations in the distribution system, network reconfiguration is a complicated combinatorial, non-differentiable constrained optimization problem The change in network configuration is achieved by opening or closing of these two 230 N Vikraman & E Anbarasu types of switches in such a way that the ‘radiality’ of the network is maintained The distribution systems are characterized by their prevailing radial nature and high R/X ratio An artificial neural network based method for feeder reconfiguration was presented in [5] However, such technique can encounter difficulties, such as getting trapped in local minima, increased computational complexity, and not being applicable to certain objective functions This led to the need of developing a new class of solution methods that can overcome these shortcomings Recently, power system applications have benefited from the powerful nature of Particle Swarm Optimization (PSO) as a new optimization technique [11, 12] The particle swarm algorithm is a method for optimizing hard numerical functions based on simulating the social behavior of bees and how can reach the location of most flower concentration In [13], a discrete particle swarm optimization (DPSO) algorithm was used as new algorithm for solving the reconfiguration problems The DPSO algorithm was applied to two test systems but, it was found that such method is often not efficient because the extremely large number of unfeasible non-radial solutions appearing at each generation will lead to a long computing time before reaching an optimal solution DPSO algorithm uses the value and to denote that the status of corresponding switch in the feeder is open or closed, respectively This work proposes a personalized PSO algorithm for distribution system reconfiguration with a new variable expression design to overcome the drawbacks in the previous methods To verify the effectiveness of the proposed method, comparative studies are conducted on a 33- node test system with encouraging results The results obtained using the proposed PSO approach, are compared with results obtained using other modern techniques to examine the performance DISTRIBUTION SYSTEM Electricity Distribution Electrical Distribution is the final stage in the delivery of electricity to end users A distribution system's network carries electricity from the transmission system and delivers it to consumers Typically, the network would include medium-voltage (less than 50 kV) power lines, electrical substations and pole-mounted transformers, low-voltage (less than 1000 V) distribution wiring and sometimes electricity meters So that the part of power system used for distribution of electric power for local use is known as distribution system In general, the distribution system is the electrical system between the substation fed by the transmission system and the consumers’ meters Power Distribution System Distribution networks have typical characteristics The aim of this article is to introduce distribution networks design and establish the distinction between country and urban distribution networks History of Distribution System In the early days of electricity distribution, direct current DC generators were connected to load sat the same voltage The generation, transmission and loads had to be of the same voltage because there was no way of changing DC voltage levels, other than inefficient motor-generator sets Low DC voltages were used (on the order of 100 volts) since that was a practical voltage for incandescent lamps, which were then the primary electrical load The low voltage also required less insulation to be safely distributed within buildings The losses in a cable are proportional to the square of the current, the length of the cable, and the resistivity of the material, and are inversely proportional to cross-sectional area Early transmission networks were already using copper, which is one of the best economically feasible conductors for this application To reduce the current and copper required for a given quantity of power transmitted would require a higher transmission voltage, but no convenient efficient method existed to change the voltage level of DC power circuits To keep Distribution Systems Reconfiguration Using Particle Swarm Technique 231 losses to an economically practical level the Edison DC system needed thick cables and local generators Modern Distribution System The modern distribution system begins as the primary circuit leaves the sub-station and ends as the secondary service enters the customer's meter socket A variety of methods, materials, and equipment are used among the various utility companies, but the end result is similar First, the energy leaves the sub-station in a primary circuit, usually with all three phases The most common type of primary is known as a Wye configuration (so named because of the shape of a "Y".) The Wye configuration includes phases (represented by the three outer parts of the "Y") and a neutral (represented by the centre of the "Y".) The neutral is grounded both at the substation and at every power pole The other type of primary configuration is known as delta This method is older and less common Delta is so named because of the shape of the Greek letter delta, a triangle Delta has only phases and no neutral In delta there is only a single voltage, between two phases (phase to phase), while in Wye there are two voltages, between two phases and between a phase and27 neutral (phase to neutral) Wye primary is safer because if one phase becomes grounded, that is, makes connection to the ground through a person, tree, or other object, it should trip out the circuit breaker tripping similar to a household fused cut-out system In delta, if a phase makes connection to ground it will continue to function normally Classification of Distribution System  Nature of Current: According to nature of current, distribution system may be classified as  d.c distribution system and  a.c distribution system Now-a-days a.c system is universally adopted for distribution of electric power as it is simpler and more economical than direct current method  Type of Construction: According to type of construction, distribution system may be classified as  Overhead system and  Underground system The overhead system is generally employed for distribution as it is to 10 times cheaper than the equivalent underground system In general, the underground system is used at places where overhead construction is impracticable or prohibited by the local laws  Scheme of Connection: According to scheme of connection, the distribution system may be classified  Radial system,  Ring main system and  Inter-connected system Each scheme has its own advantages and disadvantages RECONFIGURATION The Reconfiguration Problem has the Following Constrains  Power flow equations 232 N Vikraman & E Anbarasu  Upper and lower bounds of nodal voltages  Upper and lower bounds of line currents  Feasible conditions in terms of network topology Distribution Power Flow The power flow equations for a radial distribution system are derived as the relationship between the specified complex bus powers and the bus voltages Let is the complex power flowing from bus ‘i’ to bus’j’ (3.1) The ‘i’th bus powers are expressed as (3.2) k(i) is the set of nodes connected to node i, and Pi /Qi denote the real/reactive power at node i The complex non linear equations (2) are to be solved to determine the bus voltages The real and imaginary parts of the equations are separated and solved using numerical methods Formulation of Proposed Method for Load Buses The basis for the proposed method is that an N bus radial distribution network has only N-1 lines (elements) and the branch currents (powers) can be expressed in terms of bus currents (powers)For an element ij connected between nodes ‘i’ and ‘j’ the bus current of node j can be expressed as a linear equation (3.3) k(j) is the set of nodes connected to node j For the slack bus the power is not specified so it is excluded and the relationship between bus currents and branch currents are derived as a non-singular square matrix (3.4) (3.5) The matrix K is element incidence matrix It is a non singular square matrix of order N-1.The elemental incidence matrix is constructed in a simple way same like bus incidence matrix In this matrix K each row is describing the element incidences The elements are numbered in conventional way i.e the no of element ‘ij’ is j-1  The diagonal elements of matrix K are one The variable j is denoting the element number K(j, j) =1  For each ‘j’th element let m (j) is the set of element numbers connected at its receiving end K(j, m(j)) = -1  All the remaining elements are zero It can be Observed that all the elements of matrix K below the main diagonal are zero (3.6) Distribution Systems Reconfiguration Using Particle Swarm Technique 233 The relationship between the branch currents and bus currents can be extended to complex branch powers and bus powers The sending end power and the receiving end powers are not same due to transmission loss The transmission loss is included as the difference between the sending end/receiving end powers The relationship between branch powers and bus powers is established in same way of bus/branch currents Multiplying both sides by element incidence matrix K (3.7) (3.8) The power flow equations are complex quadratic equations A new variable Rij is introduced for each element ‘ij’ and the equations becomes recursively linear (3.9) The branch power of 'ij' th element is expressed in terms of Rij (3.10) (3.11) The proposed method is summarized as follows:  For the first iteration transmission losses are initialized as zero for each element  From the bus powers specified the branch powers are determined as per equation (6&7)  The variable Rij is determined for each element using equation (10)  The bus voltage, branch current and bus current are determined from Rij (3.12) (3.13)  The bus currents are determined from (2) and bus powers are calculated Since the transmission losses are neglected in the first iteration there will be mismatch between the specified powers and calculated powers The mismatch is a part of the transmission loss TLijr is the transmission loss part for ‘ij’th element for ‘r’th iteration Transmission loss of each element is the summation of the transmission loss portions of all previous iterations (3.14)   (3.16) (3.17) (3.18) It can be concluded that the power flow solution always exists for a distribution system irrespective of the R/X 234 N Vikraman & E Anbarasu ratio if it is having connectivity from the source (slack bus) to all the nodes The limitations of the algorithm are being investigated [10] in view of voltage stability limit For system having less transmission loss the algorithm will perform faster The convergence criteria is that the ‘r’th iteration of the transmission loss part of each element should be less than the tolerance value (3.19) (3.20) (3.21) (3.22) (3.23) The trigonometric equations are to be solved to get the phase angle of each PV bus j and the reactive power can be updated as (3.24) Algorithm for Checking the System Radial Topology In this section a new algorithm based on the bus incidence matrix  is proposed for checking the radiality of trial solutions The flow chart of the algorithm is shown in Figure A graph may be described in terms of a connection or incidence matrix Of particular interest is the branch-to-node incidence matrix Â, which has one row for each branch and one column for each node with an entry a ij in row i and column j according to the following rules: a ij = if branch i is not connected to node j a ij = if branch i is directed away from node j a ij = -1 if branch i is directed toward node j Figure 1: Checking System Radiality Algorithm Distribution Systems Reconfiguration Using Particle Swarm Technique 235 These rules formalize the procedure used to set up the coefficient of  In network calculation, a reference node must be chosen The column corresponding to the reference node is omitted from  and the resultant matrix is denoted by A If the number of branches is equal to the number of nodes then, by applying the previous rules a square branch-to-node matrix is obtained The non reference nodes of a network are often called independent nodes or buses, and when it is said that the network has N buses, this means that there are N independent nodes not including the reference node The A matrix has the row-column dimension B×N for any network with B branches and N nodes excluding the reference node By assuming, that there is a branch between this reference node and the root of the network; this will lead to a square matrix if the initial structure of the network is radial The new proposed method is based on the value of the determinant of A It is found that, if the determinant of A is equal to or -1, then the system is radial Else if the determinant of A is equal to zero, this means that either the system is not radial or group of loads are disconnected from service Figure 2: Before Reconfiguration in 33 Node Distribution System Figure 3: After Reconfiguration in 33 Node Distribution System using PSO The advantage of using the proposed method  It reduces the computation time  It restricts each trial solution to be radial network in distribution network reconfiguration  It can be used to determine the branches of the loop formed by closing a tie line PARTICLE SWARM OPTIMISATION PSO an Optimization Tool Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr Ebehart and Dr Kennedy in 1995, inspired by social behaviour of bird flocking or fish schooling 236 N Vikraman & E Anbarasu The system is initialized with a population of random solutions and searches for optimization by updating generations In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles In past several years, PSO has been successfully applied in many research and application areas It is demonstrated that PSO gets better results in a faster, cheaper way compared with other methods PSO Operation The particle swarm concept originated as a simulation of simplified social system The original intent was to graphically simulate the choreography of bird of a bird block or fish school However, it was found that particle swarm model can be used as an optimizer PSO simulates the behaviour of bird flocking  Suppose a group of birds are randomly searching food in an area  There is only one piece of food in the area being searched  All the birds not know where is the food  But they know how far the food is in each iteration  So what's the best strategy to find the food?  The effective one is to follow the bird which is nearest to the food The inertia weight w is set according to the following equation (4.8) Where w -is the inertia weighting factor Wmax - maximum value of weighting factor Wmin - minimum value of weighting factor ITERmax - maximum number of iterations ITER - current number of iteration Figure 4: The Search Mechanism of the Particle Swarm Optimization PSO Algorithm  Initialize the population - locations and velocities  Evaluate the fitness of the individual particle (pBest) 237 Distribution Systems Reconfiguration Using Particle Swarm Technique  Keep track of the individuals highest fitness (gBest)  Modify velocities based on pBest and gBest position  Update the particles position  Terminate if the condition is met  Go to Step PSO for Reconfiguration Problem Solution  Input data and initialize parameters For each particle, the position and velocity vectors will be randomly initialized with the same size as the problem dimension  Measure the fitness (power loss) of each particle (pbest) and store the particle with the best fitness (gbest) value by running the load flow program  Update velocity and position vectors according to equation (4.6) and (4.7) for each particle  Perform violation check  Decrease the inertia weight (w)  Repeat steps 2–5 until a termination criterion is satisfied Power loss (4.9) Where, L: No of transmission lines Pi: Active power loss at bus i Qi: Reactive power at bus i Vi: Voltage at bus i ri : Section resistance SIMULATION RESULT Table 1: 33-Node System Results System Power Loss (P.U) Before Reconfiguration 0.1545 After Reconfiguration using PSO 0.1168 Tie Lines 8-20 12-22 18-33 25-29 3-4 10-11 29-30 25-29 Application to the IEEE 33-Node Distribution System The 33-node test distribution system is a 12.66 kV with one main feeder, laterals, 33 buses, and tie lines The 238 N Vikraman & E Anbarasu schematic diagram of the system is shown in Fig.3.3 The initial system real power loss was 0.1545(p.u) By applying the proposed PSO algorithm gives the final power losses is 0.1168 (p.u) It is shown from the simulation results listed in Table 5.1 that the power losses are after reconfiguration is reduced by 19.48% and 24.40% of its initial value Figure 5: Voltage Profile for 33 Bus System using PSO CONCLUSIONS In this work loss minimization has been done by PSO algorithm It has been proposed to solve the network reconfiguration problem in a radial distribution system The objectives considered were attempt to reduce the real power loss, deviations of nodes voltage, subject to the radial network structure in which all loads are energized and the branch current constraints are not violated It was observed that with the proposed method the objectives are satisfied as compared to those before reconfiguration The simulation studies on a medium size distribution network have proved the feasibility of the proposed approach and obtained results are quite good Comparison of the results of the proposed methods 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