An Improved Lightning Search Algorithm Employed Performance Enhancement in Distribution System

The proposed research work minimizes the power loss in distribution system under load conditions which is the major issue nowadays that has been reduced to reach the maximum possible power for satisfying the customer needs. Optimal siting of Distribution Static Compensator (DSTATCOM) and Photo-Voltaic (PV) array in distribution system is used to attain voltage profile improvement, reduced voltage instability and less power loss. For this, Improved Lightning Search Algorithm (ILSA) has been proposed to accomplish the objectives. The proposed ILSA has reached the Voltage Stability Index (VSI) value as 0.9877 and it outstandingly decreased the power loss to 55.92 kW which are validated with IEEE 30-bus system using MATLAB toolbox. The obtained results are compared with the existing optimization algorithms and it depicts that the proposed ILSA is more advantageous than other optimization algorithms.


Introduction
At present, electrical energy demand increases because of the increasing utilization in industries and in daily life. Good quality and uninterrupted electrical energy should be provided to the customer for their needs is an important issue at present. To meet this challenge, power plants are increasing to deliver the expected energy demand. Consequently, emissions present in air causes harmful defects and using fuels to generate electricity are going to be exhausted. Because of this, renewable energy sources such as wind energy, solar system, hydro power plant etc., are used presently in the distribution systems. To obtain the maximum potential benefits of distributed generation, optimal allocation is important in distribution systems [1,2]. Conservation Voltage Reduction (CVR) in real time management has been solved with optimally placing DG in the distribution systems [3][4][5][6].
To enhance the voltage profile values under load conditions DG has been located optimally in the distribution system [7]. However, improving voltage stability value is needed in distribution system. To achieve this aspect, renewable energy-based DG has been optimally allocated in the distributed systems [8,9]. To attain the maximum power loss reduction in distribution system, multiple DGs are placed appropriately with new method [10]. However, PV array-based DG in distribution system for optimal location requires reactive power compensation [11].
Because of reactive power compensation in distribution system, power electronics component like Distributed Flexible Alternating Current Transmission System (DFACTS) devices came into picture because of its low cost, portable size and increasing system stability [12]. Many DFACTS devices are there like DSTATCOM, Unified Power Flow Controller (UPFC), Static Var Compensator (SVC) etc. In distributed system, SVC device has been used as reactive power controller to improve the voltage profile values and to reduce the system losses [13].
Many optimization techniques have been proposed with FACTS devices to improve the system stability.

Total Voltage Deviation (TVD)
TVD can be written as, where, ' e n ' is the bus voltage magnitude and ' e nref ' is the reference voltage.

Proposed Methodology
LSA is based on the natural phenomenon of lightning and it is inspired by the probabilistic nature and sinuous characteristics of lightning discharges during a thunderstorm. The mechanism of step leader propagation utilizing the theory of fast particles known as projectiles. In LSA, three types of projectile models named transition, space and lead projectiles are used to find the optimal solution. Like other algorithms, here projectiles are act as particles. The advantage of using LSA compared to other optimization algorithm is fast tracking and high accurate results. However, its searching capability is very poor. To avoid this, ILSA is proposed here. The flow diagram of the proposed model has been presented in Fig. 1 to explain the working of ILSA easily.  The proposed method to improve LSA with the allocation of DSTATCOM and PV array simultaneously in the distribution network for various load conditions to accomplish the goals is abridged in the following steps.
Step 1: Load the bus data and line data to get the base case (1) values at each bus using Newton-Raphson's method of load flow analysis, under various load conditions like light load (0.5), nominal load (1), and heavy load (1.6).
Step 2: Initialize the higher and smaller limits, iteration counts, channel time for the limits.
Step 3: Calculate the value of KVAR to be added within the smaller and higher limits and set the random LSA population.
Step 4: Form the collection of solution vectors f(x).
Step 5: Check whether the maximum population has been reached by the obtained value. If this has been satisfied, then proceed with the next step or else store the value and increase the value of 'j'.
Step 6: Check whether the maximum iteration has been reached by the obtained value. If this has been satisfied, then save the value as the final optimal value otherwise continue the next step.
Step 7: The projectile values and leader tips energies are updated.
Step 8: The worst and best optimal solutions are updated and estimate the objective function of the step leader f(SL). Rank the step leader in descending order.
Step 9: Check whether the maximum channel time has been reached by the obtained value. If this has been satisfied, update the direction and energy otherwise eliminate the worst channel and then update the values.
Step 10: Assess the performance of the projectile's energies.
Step 11: Repeat the same procedure in step 5. Update the LSA projectile value using fuzzy. Make another solution by revising LSA and make a comparison with the fitness value of the new solution and the best solution. If the newly formed solution has a better fitness value than best solution, then save this as the best solution.
Step 12: Evaluate the actual function of solution vector f(x).
Step 13: If f(x) > f(SL) condition is satisfied then check the forking event possibility and update the SL positions else stay on the same point and increase the iteration value and the channel time.
Step 14: Next go to step 6, check whether the maximum iteration is reached. If this has been satisfied then save the value as the best result otherwise repeat the steps 7-13.
Step 15: Exhibit the optimum value.

Results and Discussion
The Optimal siting of DSTATCOM and PV array using ILSA for different load conditions has been done in IEEE 30-bus test system using MATLAB software to calculate the power loss and voltage profile values. In this, the load factor values of light load, nominal load and heavy load are 0.5, 1.0 and 1.6 respectively. The four cases used to demonstrate the usefulness of the proposed ILSA are, Case (1): system without compensation under load conditions.
Case (3): system with PV array under load conditions. Case (4): system with DSTATCOM and PV array under load conditions. Case (1): system without compensation under load conditions Load flow analysis is done using the Newton Raphson method for an uncompensated IEEE 30-bus system. At light load, the minimum voltage is 0.9850pu and the minimum angle is -17.7024 which are presented in Table 1. At this condition, the power loss is 369.11 kW and VSI value is 0.8436 which are given in Table 5. The optimal location can be found by using the Improved Lightning Search Algorithm. At nominal load, the minimum voltage is 0.9761pu and the minimum angle is -20.6883 which are shown in Table 1. In this condition, the power loss is 495.59 kW which is given in Table 5. At heavy load, the minimum voltage is 0.9668pu and the minimum angle is − 21.4409 and these values are tabulated in Table 1. At heavy load, the power loss is 879.46 kW which is shown in Table 5. Figure 2 shows the voltage graph under various load levels for network without compensation.
Case (2): System with DSTATCOM under load conditions The voltage profile values have been calculated and are presented in Table 2. At light load, the power loss is 40.98 kW and VSI value is 0.9811 which are observed from Table 5. At nominal load, the power is 83.34 kW and the VSI value is 0.9795 which are tabulated in Table 5. At heavy load, the power loss is 143.28 kW and the VSI value is 0.9795 which are presented in Table 5. Figure 3 shows the voltage graph under various load levels for network with DSTATCOM under load conditions. Case (3): system with PV array under load conditions The voltage values have been calculated and are given in Table 3. At light load, the power loss is 45.64 kW and the VSI value is 0.9804 which are shown in Table 5. At nominal load, the power loss is 69.43 kW and the VSI value is 0.9802 which are shown in Table 5. At heavy load, the power loss is 224.27 kW and VSI value is 0.9800       which are shown in Table 5. Figure 4 shows the voltage graph under various load levels for network with PV array.

Case (4): System with DSTATCOM and PV array under load conditions
The voltage values have been calculated and are presented in Table 4. At light load, the power loss is 27.01 kW and the VSI value is 0.9881which are shown in Table 5. At nominal load, the power loss is 55.92 kW and the VSI value is 0.9877 which are shown in Table 5. At heavy load, the power loss is 95.72 kW and the VSI value is 0.9875 which are tabulated in Table 5. Figure 5 shows the voltage graph under various load levels for network with DSTATCOM and PV array. Table 5 represents the results of the IEEE-30 bus system with DSTATCOM and PV array for various load levels. From this, the system with DSTATCOM and PV array (case 4) for various load levels gives the better results compared to other three cases. Figure 6 depicts the comparison of total power loss for various load levels. It clearly exhibits that the total power loss is very low in proposed case (4). Figure 7 represents the comparison of % power loss reduction for various load levels. From this figure, the proposed case (4) has high percentage of loss reduction is verified. Figure 8 demonstrates the VSI comparison for various load levels. From this, the voltage is highly stable in proposed system has been proved. Figure 9 depicts the comparison of TVD for various load levels. This figure illustrates that the proposed system has less voltage deviation. Figure 10 shows the comparison of minimum voltage (V min ) for various load levels.  Table 6. It clearly shows that the proposed system has very low loss for all the load levels.
The proposed ILSA method is compared with other algorithms which is shown in Table 7 to show the effectiveness of the proposed method with IEEE 30-bus system for various load levels. Figure 12 illustrates the comparison of power loss with existing methods. From this, the power loss in proposed method is very less has been proved. From Fig. 13, % P loss reduction in the proposed method is very high has been verified. Figure 14 depicts that the voltage value is improved in the proposed approach.

Conclusion
The proposed ILSA is an effective method to optimally allocate the DSTATCOM and PV array in the distribution system for various loading conditions. Using IEEE 30-bus system, the effectiveness of the proposed ILSA method has been verified in the distribution system. The ILSA method has been investigated with the various scenarios in IEEE 30-bus system to show the proposed fourth case is more advantageous than others in reduce the power loss and voltage profile improvement. In this, the total power loss is 55.92 kW and the percentage power loss reduction is 88.71% by the improvement in voltage profile. Obviously, the results show the proposed method is better than other algorithms with comparison.