Security-Constrained Optimal Protection Coordination for Dual-Setting Digital 1 Directional Overcurrent Relays in the Distribution Network Including Non- 2 Renewable/Renewable Synchronous Distributed Generation

: In this paper, the security-constrained optimal protection coordination (SCOPC) is introduced for dual setting digital 13 directional overcurrent relay (DDOCR) in distribution network, which including renewable and non-renewable synchronous 14 distributed generation (SDG). The SCOPC minimizes the total operation time of DDOCRs in primary and backup protection 15 operating to achieve a fast protection coordination. Also, to improve the flexibility in DDOCRs setting, the allowable limits of A 16 and B coefficients, pickup current (PC) and time dial setting (TDS) in both reverse and forward directions are considered as 17 constraints. Another constraint is the Coordination Time interval (CTI). To consideration of the mentioned scheme security, the 18 SCOPC mechanism considered the unavailability of DDOCRs due to their failure, so the stochastic method is used to modelling 19 of this parameter. To calculate the fault current, network variables are proportional to the daily stochastic operation results of 20 distribution network. Moreover, the proposed problem is implemented on the standard distribution networks, and then the optimal 21 solution is obtained with hybrid algorithm of grey wolf optimization (GWO) and training and learning optimization (TLBO). The 22 numerical results illustrate that the proposed algorithm is able to achieve a reliable and fast protection coordination that has a


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According to the U.S. Department of Energy, more than 80 precent of power system faults occur in the distribution network 5 at optimal operating conditions. Therefore, it is possible that the calculated fault current by the power flow doesn't to obtain 83 a reliable result.

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 Most research has used traditional evolutionary algorithms such as genetic algorithm (GA) and PSO algorithm to solve the 85 OPC problem 19 . It is noteworthy that these algorithms are suitable for simple problems. But the OPC problem considering 86 the A, B, PC and TDS for dual setting DDOCRs, will be a complex problem, which is more evident in larger distribution 87 networks. Therefore, it is anticipated that traditional evolutionary algorithms will not be able to provide a reliable optimal 88 solution in this situation.

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To overcome the research gaps that mentioned in this paper, the security-constrained optimal protection coordination (SCOPC) 90 scheme for dual setting DDOCRs in the distribution network in the presence of SDGs is expressed. The proposed problem 91 minimizes the total operation time of all DDOCRs in backup and primary protection modes, while it constrained to the allowable 92 limit of relay adjustment parameters and coordination time interval (CTI). In this mechanism, in order to improve the flexibility 93 of relays adjustments and fast protection coordination achievement in case of fault condition, the proposed scheme achieves the 94 optimal value for A, B, PC and TDS parameters in both forward and reverse directions of DDOCRs. In addition, in order to 95 improve and increase the security of the OPC scheme, the unavailability of relays due to their failure is also considered in the 96 proposed scheme. This parameter is behaved as uncertainty, so the stochastic programming is used to model it. In this method, 97 the Monte Carlo simulation (MCS), proportional to the Bernoulli probability distribution function (PDF), obtains the number of 98 scenarios for the unavailability of the relays uncertainty, which is proportional to the forced outage rate (FOR) of the relays.

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Moreover, the fault current flow of the relays is calculated in commensurate to the optimal daily operation results of the 100 distribution network in the presence of renewable and non-renewable SDGs. This problem minimizes the expected total operation 101 cost of the distribution network and SDGs, which is limited to the AC power flow equations and the SDG constraints. In this 102 problem, the load consumption, energy price and generation power of renewable SDGs are uncertain, and stochastic 103 programming is applied to model these parameters. In this programing, the MCS method first generates a high number of 104 scenarios in proportion to the Normal/Weibull PDF for the consumed load and the energy price / the production power of the 105 renewable SDGs uncertainties. Then, the Kantorovich method is used as a scenario reduction technique to achieve a low number 106 of scenarios with a high probability of occurrence. In the following, the buses voltage and the current flow through the distribution 107 lines are calculated per different fault locations according to the obtained results of the distribution network optimal operation. 108 Finally, to consider the worst case scenario, at all simulation hours and in all scenarios, the fault current flow through the relay 109 is considered to be equal to the maximum value of the fault current passing through the distribution line where the relay is located.

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It is noteworthy that the two mentioned problems are nonlinear, which in this paper to achieve a optimal solution including low 111 standard deviation in responding, a hybrid optimization algorithm that is combination of the grey wolf optimization (GWO) and 6  Implementation of the SCOPC scheme in the distribution network considering the uncertainty of the unavailability of dual

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 Apply the combined GWO and TLBO algorithm for the proposed problems to obtain an optimal solution containing low 120 standard deviation in responding.

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The rest of the paper is organized as follows: the SCOPC scheme is described in Section 2. Section 3 presents the problem 122 solution process using a combined GWO and TLBO algorithm. Then the numerical results and conclusion are shown in Sections 123 4 and 5, respectively. 124 125

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In this section, the SCOPC for dual setting DDOCRs in distribution network with SDGs including micro turbines, diesel 127 generators and wind turbine units is presented. In this scheme, the optimal value of the DDOCR adjustment parameters, i.e. A fw/p , 128 A rv/b , B fw/p , B rv/b , IP fw/p , IP rv/b , TDS fw/p and TDS rv/b , are calculated in a way that the total operation time of these relays is in two 129 primary and backup protection modes is minimized, while the constraint of the coordination time interval (CTI) is satisfied. One 130 of the ability of the proposed SCOPC in this paper is the unavailability of one of mentioned relays that due to their failure, which 131 will be an innovation aspect of this paper. Therefore, the proposed scheme will be modeled as follows:

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In the proposed SCOPC scheme, the unavailability parameter of a DDOCR (u) is used to evaluate the reliability of this scheme.

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The value of this parameter is equal to zero or one, which is the value of zero/one corresponding to no responding/responding of 144 the DDOCR in the distribution network. This parameter is an uncertainty that follows the Bernoulli PDF and is dependent on the 145 FOR of DDOCR. In addition, MCS is used to generate the scenario for this uncertainty parameter.
(2) and (3), the amount of fault current flow through the relays depends on the value of network variables at the 147 moment before the fault. Generally, in most papers, network variables calculate according to the power flow problem, where the 8 problem of distribution network is used to calculate the network variables, which will be another innovation of this paper.
, , , ,,, ,, \ , , , , The objective function of the optimal operation problem is presented in Eq. Finally, the corresponding constraint with the variable DG is presented in Eq. (23) 23 . According to the IEEE1547 standard 24 , 163 the variable DGs are generally used for energy production and their reactive power control capability is not considered, so 164 following this concept, only the active power constraint of them is considered in this paper.

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In Eqs. (13)-(23) of the problem, the load consumption, the energy price and production power of renewable SDG like a wind 166 turbine system are as uncertainty. Therefore, in this paper, stochastic programming is used to model these parameters. In this 167 method, MCS method is used to generate a high number of scenarios corresponding to normal/Weibull PDF for load consumption 168 and energy price/production power of renewable SDG 25 . Then, the Kantorovich mechanism is used as a scenario reduction 169 method to achieve a low number of scenarios with a high probability of occurrence 25 . , The OPC problem will be complex one due to the employment of a number of high adjustment variables for dual setting 182 DDOCR, especially in larger distribution networks. Also, the optimal operation problem of distribution network has such 183 conditions. Therefore, it is predicted that the employment of an evolutionary algorithm will not be able to achieve a reliable 184 response. To overcome for this issue, this paper uses a combination of meta-heuristic algorithms such as combination of GWO 185 26 and TLBO 27 to solve the proposed problems. It is noteworthy that in this case, the number of updating steps of the decision 186 variables value is more than employment an evolutionary algorithm, so it is possible to obtain an optimal solution considering 10 low standard deviation with less computational complexity. Another advantage of this algorithm is the lack of adjustment 188 parameters in this algorithm 26 Subject to: variables. The minimum point is optimal response. In the following, the updating steps will be implemented as the SCOPC 206 problem solving process until the convergence point is reached. Finally, the flowchart of proposed algorithm is shown in Fig. 1.       Table 2. It is noteworthy that for all proposed algorithms, the population size 262 is 50 and the maximum of convergence iteration is 3000, and regulation parameters for SCA and KHO solver are presented in 12 263 and 31 , respectively. Also, to achieve the statistical results such as the mean of the final optimal response and its standard 264 deviation, each proposed algorithm is repeated 20 times. Based on the results that presented in Table 2, it can be seen that the  Table 2, it can be seen that the standard deviation of 275 the objective functions of OT and OC for the combination of GWO and TLBO algorithm is much lower than for other algorithms.

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Also, the standard deviation values of these objective functions in the two 33-bus and 119-bus distribution networks are very 277 close to each other, but this is not established in the other algorithms that presented in Table 2. Hence, it can be said that the 278 proposed algorithm is able to achieve the best solution including low standard deviation, which is very little dependent on the 279 problem data. But in SCA, KHO, GWO and TLBO solvers, increasing the scale of problem data (comparing the results of the 280 119-bus network to the 33-bus network) increases the standard deviation of the optimal point, so it is predicted that in large real 281 networks, these algorithms don't have the ability to achieve the reliable optimal solution. However, since the combination of 282 GWO and TLBO has the same and low standard deviation values in the two mentioned networks, the consistency of this 283 algorithm is slightly dependent on the data scale of the problem and is suitable for large scale networks. It is noteworthy that all 284 the benefits provided in this section confirm the fourth innovation in Section 1. distribution networks in the presence of non-renewable and renewable SDGs (wind system type) are provided. Fig. 4 shows the 289 expected daily curve of SDGs active power. Based on Fig. 4(a), it can be seen that the active power of the wind turbine system 290 has different values for different hours, which is due to changes in wind speed during the day and night. Also, according to Fig.   291 4(b), the non-renewable SDGs in the two mentioned networks are off for 1:00 to 7: 00 and don't inject the active power into the 292 network. Because based on the data in section 4-1, at these hours the purchased energy price from the upstream network is equal 293 to 16 $/MWh, while the fuel price of non-renewable SDGs is equal to 20 $/MWh. Therefore, in order to minimize the expected 294 operation cost (OC), the most optimal status is for consumers to be fed by the upstream network. But in other hours, the opposite 295 is true, so these SDGs inject their maximum active power into the network. In addition, Table 3 presented the advantages of the 296 proposed optimal operation in proportion to the optimal scheduling for SDGs as illustrated in Fig. 4 Table   310 4. According to this table, the total operation time of all DDOCRs in the two primary and backup protection modes considering 311 all the fault locations that provided in Table 1    is able to achieve faster protection coordination than other case studies, which confirms the second innovation in Section 1. It is 334 noteworthy that this advantage is obtained in such a way that A fw/p and B fw/p are set to values greater than 0.14 and 0.02, and A rv/b 335 and B rv/b are around values of 0.14 and 0.02. TDS fw/p is set to its smallest value i.e. 0.1 second, but TDS rv/b is set to a higher value 336 than TDS rv/b in cases I to III. In the following, the pickup current of DDOCRs in the case IV is less than that of the pickup current 337 in cases I to III. Finally, the OT value for the SCOPC scheme in the case V for the two 33-bus and 119-bus networks are 52.32 338 sec and 123.62 sec, respectively. This fitness function are equal to 49.12 sec and 120.61 sec for the case IV, respectively. This 339 time difference is due to the uncertainty of the unavailability of DDOCRs, which has a more reliable response confirming the 340 first innovation capability in section 1.

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In this paper, SCOPC scheme for coordination protection of dual setting DDOCRs in distribution network with renewable and 345 non-renewable SDGs is presented. The SCOPC scheme minimizes the expected total operation time of these relays in the two 346 primary and backup protection modes considering several fault locations, which is constrained to the allowable limits of DDOCR 347 adjustment parameters and CTI limitations. In this problem, the unavailability of DDOCRs is uncertain, and stochastic 20 programming is used to model it. In addition, this paper calculates the fault current flow through the relay corresponding to the 349 stochastic operation results of the distribution network, which minimizes the expected total operation cost of network and non-350 renewable SDGs, while constrained the equations of the optimal AC power flow in the distribution network. Also in this problem, 351 stochastic programming is applied to model the uncertainties of load consumption, energy price and production power of 352 renewable SDGs. Finally, the optimal solution for both optimal operation and SCOPC problems is achieved by a combined 353 GWO and TLBO algorithms. Based on the obtained numerical results in this paper, it was seen that the proposed solver is able 354 to obtain the most optimal point in lower coverage iteration and computational time with low standard deviation in responding 355 to other SCA, KHO, GWO and TLBO algorithms. Also, the standard deviation of this algorithm has a low dependence on the 356 data scale of the problem, so that for two networks and two problems (SCOPC and optimal operation) is about 1%. In addition, 357 based on the simulation results, it was illustrated that the SCOPC scheme based on optimal operation results is about 13% more 358 accurate than the SCOPC based on the power flow analysis considering the constant value for the active power of SDGs. Finally, 359 the protection coordination of DDOCRs has a faster operation time due to the flexibility in different adjustment parameters than 360 OCRs and DOCRs. Also, due to considering the unavailability of DDOCRs in the SCOPC scheme, the obtained results in this 361 scheme have better reliability and confidence than the OPC scheme. 362 meshed distribution systems with DG using dual setting directional over-current relays. IEEE Trans. Smart Grid 6, to Achieve Protection Coordination of Fuse-Recloser in Radial Distribution Networks with Synchronous DGs. Electr.