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International Electrical Engineering Journal (IEEJ) Vol. 5(2014) No.12, pp. 1696-1702 ISSN 2078-2365 http://www.ieejournal.com/ Imperialistic Competitive Algorithm (ICA) for Solving Optimal VAR Dispatch Problem 1 K.R.VADIVELU and 2G.V MARUTHESWAR 1 [email protected],[email protected] Abstract: This paper presents an application of Fast Voltage Stability Index (FVSI) to Imperialistic Competitive Algorithm (ICA) for solving reactive power dispatch problem in a power system. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Imperialistic Competitive Algorithm (ICA), is presented in this paper for solving global unconstrained optimization problem. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and the performance of the algorithm is compared with gravitational search algorithm (GSA). Results show that (ICA) is more efficient than others for solution of single-objective Optimal VAr problem. Key Words: Imperialistic Competitive Algorithm (ICA), swarm intelligence, optimal reactive power, transmission loss 1. INTRODUCTION Optimal reactive power dispatch problem is one of the important problems in power systems. Major point is operating the system unconfident mode and also to get better the economy of the system. The sources of the reactive power are the generators, synchronous condensers, capacitors, static compensators and tap changing transformers. Here the reactive power dispatch problem involve best use of the accessible generator bus voltage magnitudes, transformer tap setting and the output of reactive power sources so as to reduce the loss and to improve the voltage stability of the system. Various mathematical techniques have been utilize to solve this optimal reactive power dispatch problem like the gradient method [1], [2], Newton method [3] and linear programming [4]-[7]. They include Interior Point Methods (IMPs) [8], [9] and [10], Newton-based Nonlinear Programming method [11] and Successive Linear Programming (SLP) [12].The gradient and Newton methods failed to handle inequality constraints. CPF was incorporated successfully in [13]. The traditional solutions to the problem of OPF are highly sensitive to starting points and therefore they usually result in monotonic solution. In order to conquer this problem, evolutionary algorithm is used. Genetic algorithms are an example for evolutionary algorithms that assess complex scenarios and provide solution that will be more precise when compared with conventional solutions [14], [15]. To the problem of OPF Particle Swarm Optimization (PSO) has been applied in [10] that worked out food searching behavior of animals of birds. They also computed the best positional locally and globally at any given point of time in order to find out the best options for searching. This paper heart on building a new evolutionary algorithm for solving OPF-CPF problem. The algorithm is named as “Imperialistic Competition Algorithm”. This algorithm is used to show the real power loss minimization and maximization of VSL of the power distribution systems. ICA has been applied earlier in power distribution systems for harmonic estimation problem [16]. The forging behavior of E. coli (bacteria) has been used in [14].ICA has been around for few years. Recently it was explored in [17] and later used for harmonic estimation problem in power distribution systems as discussed in [14]. Foraging behavior of E.coli is used to build the algorithm. These bacteria live in human intestine. Many variables are simultaneously optimized.. The outcome result revealed that the proposed method has power and can be used in solving real world problems pertaining to extremely nonlinear epistemic. Optimization of the said variables for real power loss minimization and VSL maximization.In this paper, maximum loadabilty is estimated through voltage stability analysis. Voltage stability analysis is conducted using the Fast Voltage stability index (FVSI) [18,19]. The reactive power at a particular bus is augmented until it reach the unsteadiness point at bifurcation. At the instability point, the connected load at the particular bus is resolute as the maximum load-ability. The maximum load-ability for each load bus will be sorted in rising order with the smallest value being ranked highest. The highest rank, imply the weak bus in the system that has the lowest sustainable load. The proposed come up to has been used in the RPP problems for the IEEE 30-bus system [3] which consists of six generator buses, 21 load buses and 41 branches of which four branches, (6,9), (6,10), (4,12) and (28,27) are under load tap-setting transformer branches. The reactive power source installation buses are buses 30, 26, 29 and 25 which are identified based on the FVSI technique. There are totally 14 control variables 2. PROBLEM FORMULATION 1696 .Vadivelu and .Marutheswar, Imperialistic competitive algorithm (ICA) for solving optimal var dispatch problem International Electrical Engineering Journal (IEEJ) Vol. 5(2014) No.12, pp. 1696-1702 ISSN 2078-2365 http://www.ieejournal.com/ i N PQ The objective function in RPP problem comprises two terms j Nl [20]. The first expression represent the total cost of energy loss as follows: (5) iii) Reactive Power source Installation Restriction WC h d1Ploss ,1 QCi (1) min QCi QCi i NC max iv) Reactive Power source Generation Restriction 1 N1 Where, Ploss ,1 is the network real power loss during the period of load level 1. The Ploss ,1 can be expressed in the Ploss gk Vi V j 2VV i j cos ij 2 min Qgi Qgi i Ng max v) Bus Voltage Restriction Vi following equation in the duration dl: 2 Qgi min Vi Vi i Ng max vi)Transformer Tap Setting Restriction (2) Tk min Tk Tk max i NT k NE Where, reactive power flow equations are considered as k i, j equality constraints; VAR source installment restrictions, reactive power generation restrictions, transformer tap-setting The second term represents the cost of VAR source restrictions and bus voltage restrictions are used as inequality installments which has two components, namely, fixed constraints. installment cost and purchase cost: IC ei CCi QCi QCi min Can be less than zero and if Qci is selected as a negative value, say in the light load period, variable (3) inductive reactance should be installed at bus i. The i NC transformer tap setting Tk, generator bus voltages Vg and VAR The objective function, therefore, can be expressed as source installments QC are control variables so they are self-restricted. The load bus voltages Vload and reactive power follows: generations Qg are state variables which are restricted by Min fc = IC + WC , (4) Subjected to adding them as the quadratic penalty terms to the objective function. Equation (4) is therefore changed to the following Min i) Real Power balance equation 0=Pi Vi V j Gij cos ij Bij sin ij i N B l j Nl ii) Reactive Power balance equation 0=Qi Vi V j Gij sin ij Bij cos ij FC FC Vi Vi Vi i NQg lim Q lim 2 Qgi i NV lim gi Qgi lim 2 (6) Subjected to 0=Pi Vi V j Gij cos ij Bij sin ij i N B l 1697 .Vadivelu and .Marutheswar, Imperialistic competitive algorithm (ICA) for solving optimal var dispatch problem International Electrical Engineering Journal (IEEJ) Vol. 5(2014) No.12, pp. 1696-1702 ISSN 2078-2365 http://www.ieejournal.com/ j Nl R R2 2 V2 cos V1V2 X Q2 0 X X sin 0=Qi Vi V j Gij sin ij Bij cosij i N PQ (7) Setting the discriminate of the equation to be greater than or j Nl equal to zero yields Where, λvi and λQgi are the penalty factors which can be increased in the optimization procedure; and are defined in the following equations: R X sin cos 2 R2 Q2 0 V1 4 X X (8) Vi if Vi Vi max max if Vi Vi Vi min Vi lim rearrange (8), we obtain min 4Z 2Q2 X (V1 ) 2 R sin cos 2 1 (9) Since δ is normally very small, then Qgi lim min min min if Q gi Qgi Qgi max max max if Q gi Qgi Qgi =0, =0, =X (10) Taking the symbols ‘i’ as the sending bus and ‘j’ as the receiving bus, FVSI can be defined by 3. FVSI FORMULATION = The FVSI is resulting from the voltage quadratic equation at (11) the receiving bus on a two- bus system [19]. The two-bus . representation 3.1. RANKING OF CRITICAL BUSES BASED ON is illustrated in Figure.1. MAXIMUM LOADABILITY The basic concept behind this technique is use of Line V1 ∟ 0 B u s 1 Bus 2 V2 ∟δ P1 ,Q1,S1 P2, Q2, S2 Stability Index for indicating the voltage stability condition formulated based on line termed as Fast Voltage Stability Index in order to determine the maximum load-ability in a power system. Maximum load-ability is estimated through Voltage stability analysis. The margin measured from base case solution to the maximum convergence point in the load R+ jX flow determines the maximum load-ability at a particular bus Fig. 1two-bus power system model From the figure, the voltage quadratic equation at the receiving bus is written as in the system. Voltage stability is conduct by using line stability index indicate by FVSI to indicate the stressfulness of a line in a transmission system. The reactive power at a particular load bus is increased until it reaches the instability point at bifurcation. At the instability 1698 .Vadivelu and .Marutheswar, Imperialistic competitive algorithm (ICA) for solving optimal var dispatch problem International Electrical Engineering Journal (IEEJ) Vol. 5(2014) No.12, pp. 1696-1702 ISSN 2078-2365 http://www.ieejournal.com/ point, the connected load at the particular bus is determined as maximum load-ability of a particular bus which beyond this converges and optimized the said parameter in power distribution systems. The ICA applied to this project has the steps given in listing 1 limit system infringement will be experienced. The individual maximum load-ability obtained from the load bus will be sorted in climbing order with the smallest value being ranked highest. The highest rank implies the weak bus in the system that has the lowest sustainable load. The bus which ranked lowest is the most secure bus in the system. 3.2. DETERMINING THE MAXIMUM OADABILITY FOR WEAK BUS IDENTIFICATION The following steps are implemented. Step 1: Run the power flow program for the base case. Step 2: Assess the FVSI value for every line in the system. Step 3: Slowly increase the reactive power loading by 0.01pu at a chosen Load Bus until the load flow solution fails to give results for the Maximum Computable FVSI. Step 4: Take out the stability index that has the highest value. Step 5: Choose another load bus and repeat steps 3 and 4. Step 6: Extract the maximum reactive power loading for the maximum Computable FVSI for every load bus. The Algorithm: Imperialistic competitive Algorithm Inputs: Transformer tap positions,VAr compensators, Penalty factors Outputs: Optimized Voltage magnitude and Real Power Loss Step 1 Initialization of variables Repeat Input variables and penalty factors to ICA base line algorithm Compute objective function for real power loss Optimize real power loss Until Voltage magnitude is completely optimized list 1 –steps to optimize real power loss and Voltage magnitude can be seen in list 1 ,the algorithm runs in two part loops.The first part loop optimizes the real power loss.It does mean that it reduces real power loss while the second part loop focuses on rising the Voltage magnitude.The more in Voltage magnitude,the more steady the transmission system should be.The underlying algorithm is ICS that has been adopted from [18] maximum reactive power Loading is referred to as the Step 7: maximum load-ability of a particular bus. 5. NUMERICAL RESULTS Sort the maximum load-ability obtained from step 6 in The validity of the proposed ica Algorithm technique has been demonstrated in standard IEEE-30 bus system. The test system has six generators at the buses 1, 2, 5, 8, 11 and 13 and four transformers with off-nominal tap ratio at lines 6-9, 6-10, 4-12, and 28-27 and the number of the optimized control variables is 10 for this reactive power dispatch problem. The minimum voltage magnitude limits at all buses are 0.95pu. The maximum limit values for generator buses are 1.1pu and 1.05pu for the remaining buses. The minimum and maximum limits of the transformers tapping are 0.9 and 1.1pu. The buses for possible VAR source installation based on max load buses are 25, 26, 29 and 30.. The maximum loadability and FVSI values for the IEEE 30 bus system are given in Table I. The optimum control parameter settings of the proposed ICA approach are given in Table I. And Table II and Table III show the comparison of power loss and voltage deviations. Form the simulation, the most excellent value of active power loss is 4.31934. The voltage deviations obtained from proposed ICA approach respectively. As seen in figure 3, it is evident that the results reveal the Vm at bus 20with respect to load at bus 20. The results revealed that the proposed protocol is capable of achieving its dual goal including the enhancement voltage stability limit.Fig.4 gives the Bus voltage magnitude using ascending order. The smallest maximum load-ability is ranked the highest, implying the Weakest bus in the system. 4. IMPERIALISTIC COMPETITIVE ALGORITHM (ICA). The proposed algorithm is twofold in its functionality. It is destined for minimization of real power loss and also enhancing the voltage stability. The double purpose is serve using a novel algorithm which is enthused by Evolutionary Algorithms (EAs).EAs have been good candidate to solve real world complex problems. Our algorithm is known as Imperialist Competitive Algorithm. This algorithm was originally conceived by Atashpaz-Gargari and Lucas [18].The ICA algorithm has been exploited in this paper or achieving its goals. As the ICA is one of the EAs, it is found suitable for solving the optimization problems specified in this paper. The algorithm has an iterative process that takes care of optimizing two variables i.e., real power loss and voltage stability limit. These two variables are considered appropriately in the form of empires and colonies. By treating them as part of objective functions, the algorithm finally 1699 .Vadivelu and .Marutheswar, Imperialistic competitive algorithm (ICA) for solving optimal var dispatch problem International Electrical Engineering Journal (IEEJ) Vol. 5(2014) No.12, pp. 1696-1702 ISSN 2078-2365 http://www.ieejournal.com/ ICA. The optimum control parameter settings of the proposed ICA approach are given in Table I. And Table II and Table III show the comparison of power loss and voltage deviations. Form the simulation, the most excellent value of active power loss is 4.31934. The voltage deviations obtained from proposed ICA approach respectively. As seen in figure 3, it is evident that the results reveal the Vm at bus 20with respect to load at bus 20. The results revealed that the proposed protocol is capable of achieving its dual goal including the enhancement voltage stability limit.Fig.4 gives the Bus voltage magnitude using ICA. Control Variables setting Case 1: Power Loss Case 2: Voltage Deviations VG1 1.02 0.98 VG2 VG5 1.03 1.03 0.94 1.02 VG8 1.02 1.04 VG11 VG13 1.02 0.94 1.01 1.03 T6-9 T6-10 1.00 1.02 0.90 1.01 T4-12 T27-28 1.02 1.02 1.03 0.90 Power loss (MW) Voltage deviations 4.429765 6.261549 0.723125 0.104678 TABLEI .III. COMPARISON OF THE RESULTS FOR ACTIVE POWER LOSS Figure 2.IEEE 30 bus system TABLE.I.Bus Ranking and FVSI Values Rank 1 2 3 4 5 6 7 8 9 10 Bus 30 26 29 25 15 27 10 24 14 18 Qmax(p.u) 0.26 0.29 0.33 0.47 0.50 0.57 0.60 0.62 0.75 0.77 FVSI 0.9786 0.9649 0.9946 0.9760 0.9708 0.9856 0.9837 0.9748 0.9764 0.9876 Control Variabl es Setting ICA GSA [21] Multi Objectiv e Ea [22] As Single Objective [22] 1.049 Individ ual Optimi zations [22] 1.050 VG1 1.03 1.050 1.045 VG2 1.03 1.024 1.041 1.045 1.042 VG5 1.03 1.025 1.018 1.024 1.020 VG8 1.02 1.02 1.017 1.025 1.022 VG11 1.02 1.03 1.084 1.073 1.057 VG13 0.94 0.98 1.079 1.088 1.061 T6-9 1.00 1.06 1.002 1.053 1.074 T6-10 1.02 1.08 0.951 0.921 0.931 T4-12 1.02 1.10 0.990 1.014 1.019 T27-28 1.02 1.03 0.940 0.964 0.966 Power Loss (Mw) Voltage Deviati ons 4.31 4.61 5.1167 5.1168 5.1630 0.69 0.83 0.7438 0.6291 0.3142 TABLE II. OPTIMUM CONTROL PARAMETERS VALUES TABLE IV. COMPARISON OF THE RESULTS FOR 1700 .Vadivelu and .Marutheswar, Imperialistic competitive algorithm (ICA) for solving optimal var dispatch problem International Electrical Engineering Journal (IEEJ) Vol. 5(2014) No.12, pp. 1696-1702 ISSN 2078-2365 http://www.ieejournal.com/ VOLTAGE DEVIATIONS Voltage Profiles at all buses Control Variabl es Setting IC A VG1 0.98 VG2 GSA [21] Multi Objec tive EA [22] 1.016 As Single Objectiv e [22] 0.995 Individu al Optimiz ations [22] 1.009 0.94 0.950 1.006 1.012 1.021 VG5 1.02 1.043 1.021 1.018 1.021 VG8 1.04 1.021 0.998 1.003 1.002 VG11 1.01 1.100 1.066 1.061 1.025 VG13 1.03 1.062 1.051 1.034 1.030 T6-9 0.90 0.905 1.093 1.090 1.045 T6-10 1.01 1.035 0.904 0.907 0.909 T4-12 1.03 1.038 1.002 0.970 0.964 T27-28 0.90 0.925 0.941 0.943 0.941 Power Loss (Mw) Voltage Deviatio ns 6.10 6.371 5.8889 5.6882 5.6474 0.09 0.106 0.1435 0.1442 0.1446 Voltage at respective buses 1.5 1.021 Table I and II shows the bus ranking and optimal control parameter values. Table III shows the active power loss is less using proposed ICA algorithm comparing with GSA .Table.IV, voltage magnitude is less than using ICA algorithm comparing with GSA. 0 [2] 0.6 0.4 [3] 0.2 0.4 0.6 0.8 10 15 bus numbers 20 25 30 FVSI approach has been developed for solving the weak bus leaning optimal VAr dispatch problem. Based on FVSI, the locations of reactive power strategy for voltage control are determined. The individual maximum load-ability obtained from the load buses will be sorted in rising order with the least value being ranked highest. The maximum rank implies the weakest bus in the system with low sustainable load. These are the possible locations for reactive power devices to maintain stability of the system. The proposed approach has been applied to optimal VAr power dispatch problem on the IEEE 30- bus power system. The simulation results indicate the effectiveness and robustness of the proposed algorithm to solve optimal VAr power dispatch problem in test system. The ICA approach has revealed best quality solution for the different objective functions. 0.8 0.2 5 6. CONCLUSION [1] 0 0 Figure. 4 Bus voltage profile using ICA CPF Curve Prediction-Correction Curve 1 0 0.5 REFERENCES Vm at bus 20 w.r.t. load (p.u.) at 20 1.2 1 1 1.2 [4] Fig. 3 – Results of experiments (voltage) [5] O. Alsac and B. Scott,(1974) “Optimal load flow with steady state security,” IEEE Transaction on Power Apparatus and Systems, vol. PAS-93, no. 3, pp. 745-751. K. Y. Lee, Y. M. Paru, and J. L. Oritz,(1985) “A united approach to optimal real and reactive power dispatch,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-104, no. 5, pp. 1147-1153.. A. Monticelli, M. V. F. Pereira, and S. 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Electronics, Circuits 1702 .Vadivelu and .Marutheswar, Imperialistic competitive algorithm (ICA) for solving optimal var dispatch problem