The difficulties associated with **using** the mathemat- ical optimization of complex engineering problems have contributed to the development of alternative solu- tions. In the literature, many standard optimization methods and hybrid variants based on metaheuristic al- gorithms have been proposed and applied with success for solving many complex problems related to power system protection **coordination** [7]. Authors in [8] pro- posed a Hybrid GA-NLP Approach for solving the op- timal **coordination** of direction **overcurrent**. A seeker optimization method is adapted and applied to solv- ing the **optimal** **coordination** of **directional** **overcurrent** **relays** DOCRs [9].

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Abstract: Most studies in relay **coordination** have focused solely on **coordination** of **overcurrent** **relays** while distance **relays** are used as the main protection of transmission lines. Since, simultaneous **coordination** of these two types of **relays** can provide a better protection, in this paper, a new approach is proposed for simultaneous **coordination** of distance and **directional** **overcurrent** **relays** (D&DOCRs). Also, pursued by most of the previously published studies, the settings of D&DOCRs are usually determined based on a main network topology which may result in mis-**coordination** of **relays** when changes occur in the network topology. In the proposed method, in order to have a robust **coordination**, network topology changes are taken into account in the **coordination** problem. In the new formulation, **coordination** constraints for different network topologies are added to those of the main topology. A complex nonlinear optimization problem is derived to find the desirable relay settings. Then, the problem is solved **using** hybridized Genetic Algorithm (GA) with Linear Programming (LP) method (HGA). The proposed method is evaluated **using** the IEEE 14-bus test system. According to the results, a feasible and robust solution is obtained for D&DOCRs **coordination** while all constraints, which are due to different network topologies, are satisfied.

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3.2 Case II: IEEE 14-Bus Test System The IEEE 14-bus test system, illustrated in Fig. 8, is the second test system that the proposed relay **coordination** approach is applied to it. This system, with the voltage levels of 132/33 kV, consists of 16 lines, 5 synchronous machines including 2 synchronous generators and 3 synchronous compensators, and 3 transformers. It is assumed that the lines are protected by 32 distance **relays** as well as 32 DOCRs. The IEEE 14-bus test system data are presented in [22]. Since the secondary currents of the current transformers are set to the nominal value of 5 amperes, the pickup currents of all **overcurrent** **relays** are considered as discrete values in the range of 2.5 to 12.5 amperes, with the steps of 1.25 amperes.

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This paper presents an **optimal** **coordination** of inverse definite minimum time (IDMT) **directional** **overcurrent** **relays** (DOCR) in the presence of Wind Energy Farms (WEF). Firstly, the impact of WEF on the **relays** **coordination** is focused, after that we search for the new **relays** setting to ensure an **optimal** **coordination** of the **relays**. The **coordination** problem is formu- lated as a constrained nonlinear mono-objective optimization problem. The objective function of this optimization problem is the minimization of the operation time of the associated **relays**. In terms of decision variables; two types of optimizations are considered in this paper, namely: real parameter optimization where, the time dial setting (TDS), and the pickup current set- ting (I P ) are considered as the real decision variables of the optimization problem and the mixed integer optimization, where the IEC curve characteristic of each relay is added to the previ- ous variables as an integer decision variable. The character- istics of the **relays** are always chosen arbitrary or by trial and error method. To solve this constrained non linear optimization problem, the particle swarm optimization method is used. The proposed method is validated on IEEE 8-bus power transmis- sion test systems **considering** various scenarios.

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Damchi, Y., Mashhadi, H. R., Sadeh, J., & Bashir, M. (2011, 16-20 Oct. 2011). **Optimal** **coordination** of **directional** **overcurrent** **relays** in a microgrid system **using** a hybrid particle swarm optimization. Paper presented at the Advanced Power System Automation and Protection (APAP), 2011 International Conference on. Darji, G. U., Patel, M. J., Rajput, V. N., & Pandya, K. S. (2015, 12-14 Aug. 2015). A

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ABSTRACT: This paper aims to solve the **coordination** problem encounter by IDMT **directional** **overcurrent** **relays** in meshed power systems, **using** a hybrid optimization algorithm called hybrid BFO-DE (Hybrid Bacterial Foraging Optimization and Differential Evolution). The operating time of the **overcurrent** **relays** influence a non-linear relationship with TDS and PS. The objective of hybrid optimization algorithm is to reduce total operation time for each protective relay. The competence of the proposed hybrid algorithm is shown in the paper. In this study two models are considered namely IEEE 3-bus model and IEEE 4-bus model. The result has shown that the BFO-DE approach provides good convergence speed and solution quantity.

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[4] Urdaneta A. J, Ramon N., Luis G.P.J “**Optimal** **Coordination** Of **Directional** **Overcurrent** **Relays** In Interconnected Power Systems”, IEEE Transactions on Power Delivery, Vol. 3, No. 3, July 1988. [5] Rashesh P Mehta, **Optimal** Relay **Coordination**, Journal Of Engineering And Technology, Sardar Patel University, Vol. 19, December 2006.

Protection of distribution networks is one of the most important issues in power systems. **Overcurrent** relay is one of the most commonly used protective **relays** in these systems. There are two types of settings for these kinds of the **relays**: current and time settings. A proper relay setting plays a crucial role in reducing undesired effects of faults on the power systems [1, 2]. **Overcurrent** **relays** commonly have plug setting (PS) ranging from 50 to 200% in steps of 25%. The PS shows the current setting of the **overcurrent** **relays**. For an **overcurrent** relay, PS is defined by two parameters: the minimum fault current and the maximum load current. However, the most important variable in the **optimal** **coordination** of **overcurrent** **relays** is the time multiplier setting (TMS) [3]. So far, some research has been carried out on **coordination** of **overcurrent** **relays** [3-7]. Due to the difficulty of nonlinear **optimal** programming techniques, the usual **optimal** **coordination** of **overcurrent** **relays** is generally carried out by linear programming techniques, including simplex, two-phase simplex and dual simplex methods [3]. In these

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For some power grid topologies, there will be limitations in **coordination** for voltage correction based inverse time **overcurrent** protection. To solve this problem, the above limitations are analyzed at first in this paper. Then based on substation area information sharing, this paper proposes to use the voltage information of the high side of transformer to dynamically compensate for the inverse time characteristic curve equation, which can effectively compensate for the limitations of voltage correction based inverse time **overcurrent** protection scheme, and improve the properties of inverse time **overcurrent** protection significantly. The theoretical analysis and simulation results show that the proposed scheme has the feasibility and good practical value.

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The basic function of shunt inverter is to supply or absorb the real power demanded by **series** inverter at the common DC link to support the real power exchange resulting from **series** voltage injection. This DC link demand of **series** inverter is converted back to ac by shunt inverter and coupled to the transmission line bus via a shunt-connected transformer. In addition to this the shunt inverter can also generate or absorb controllable reactive power, if it is desired and thereby provides independent shunt reactive **compensation** for the line. The three main control parameters of UPFC are magnitude (V), angle (α) and shunt reactive current control of real and reactive power can be achieved by injecting **series** voltage with appropriate magnitude and angle. This injected voltage is transformed into dq reference frame, which is split into E d and E q . These coordinates can be used to control the power flow.

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The process of signal transmission from the secondary transmitter to the SUs consists of two different trans- mission modes: direct mode and indirect (relay) mode. Indirect mode takes place when the direct links between the transmitter and cognitive receivers failed due to some problems such as multipath fading, shadowing, and path loss and thus QoS requirements are not satisfied in the secondary network. Under such conditions, relaying process begins and **directional** **relays** are responsible to forward the message signal from the secondary transmitter to the SUs. This cooperative communication method helps to overcome the mentioned problem and tries to guarantee the desired QoS in both primary and secondary networks.

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In **Overcurrent** Protection and **Coordination**, there have many circuit breaker that will take action in one circuit which is „protective‟ circuit breaker and „protecting‟ circuit breaker. Protecting circuit breaker will take action first when fault happen. If protecting circuit breaker fail to isolate the fault, so it will affected the second circuit breaker. Now the damage taken during fault increasing to two damage circuit breaker. During this interruption, the disadvantage will effect to the customer. Customer will don‟t have any power supply until the maintenance complete by worker. Therefore, the maintenance cost will increase compare the damage of one circuit breaker than two circuit breaker that get damage.

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Abstract. In presence of the Distributed Generation (DG) brought new chal- lenges to the protection engineers since novel **coordination** scheme is no longer appropriate with the penetration of the DG. The extreme case is violation to the primary and backup relay selectivity constraint. This violation will have resulted to the degradation of the relay performance. Therefore, this paper proposes the best location of the DG penetration to decrease the effect of the DG presentation to the relay performance **using** the grey wolf optimization (GWO) algorithm. The impacts of the DG prior to the location of the insertion are implemented to the radial 7 bus test system. As a consequence, the best location of the DG penetra- tion is then identified.

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At present power systems, transmission networks are progressively becoming more stressed because demand is increasing and limitations on adding new lines. Many reasons such as growing demand for electric energy, deregulation, and eco-nomical as well as environmental restrictions on expanding the power networks have forced the existing systems to operate very close to their stability limits. One of the impacts of such stressed system is risk of losing stability after a disturbance the techniques of reactive power **compensation** are found to be efficient in a stressed transmission network for the better utilization of existing facilities of the network without sacrificing desired stability margin. The VAR **compensation** improves the stability of ac system by increasing the maximum active power that can be transmitted Voltage magnitude is important factor that affect power supply quality. Voltage sag or swell prove problematic to customer as it leads to production downtime. Reactive power **compensation** improves the performance of ac

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ABSTRACT: This paper presents maximum path, dual simplex and a new proposed method based on linear and non linear programming model for **coordination** of **overcurrent** (OC) **relays**. OC **relays** are the major protection devices in a distribution system. OC **relays** are usually employed as backup protection. To reduce the power outage, mal-operation of the backup **relays** should be avoided and for that **coordination** of OC **relays** in distribution network is major concern. The OC relay **coordination** in radial and parallel network is by conventional maximum path, dual simplex and proposed methods is given. Also **coordination** of OC in radial and parallel network is a constrained optimization problem. The purpose is to find optimum relay setting to minimize the time of operation of **relays** by dual simplex method is given. A brief comparison of all three methods is also given.

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account. In this paper, a novel optimization model for DG planning problem is proposed. The objective function of the presented model consist of DG investment cost and associated operation costs including protection **coordination** and mal-operation costs as well as the cost of energy losses. To best of authors’ knowledge, the protection **coordination** and mal- operation costs have not been taken into consideration in the previous research works in the area of DG planning problems, and it is specific to this paper. The rest of this paper is organized as follows: Section 2 presents a brief review of protection problems raised due to operation of DG in distribution networks. The mathematical formulation of the proposed DG planning model and its solution approach are presented in section 3. Section 4 encompasses the numerical results obtained by application of the suggested model on a standard radial distribution network. Sensitivity analysis is performed in section 5 to demonstrate the impacts of variation in effective parameters on the cost of DG planning problem. Finally, section 6 concludes the paper.

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[17]. Practical experiences suggest that they reach stagnation after certain number of generations as the population is not converged locally, so they will stop proceeding towards global **optimal** solutions. The stochastic search methods are proven in reaching global solutions for certain difficult real world optimization problems [18]. Hence this article comes up with a hybrid approach involving **PSO**-DE and BFOA algorithm for solving non-convex DED problem **considering** valve-point loading effects, ramp-rate limits, prohibited operating regions and spinning reserve capacity.

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not give satisfactory result for a wide variety of operating conditions [8].When both the source voltage and load currents are non- sinusoidal, it is possible to force the source current waveform to be identical with source voltage waveform, but at the expense of power factor. On the other hand, the unity power factor **compensation** is possible, but the shape of the source current will differ with the shape of the source voltage. To obtain both the goals simultaneously than there is a need to optimize the controller parameters [9]. Therefore **PSO** algorithm is proposed to enhance the PI controller tuning that can overcome the drawbacks in existing conventional methods. This paper presents the effectiveness of **using** **PSO** in the PI tuning process even when the system passes by a transient after load variation.Results have proved that the control strategy with **PSO** is efficient for compensating the current harmonics.

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In this paper we find the **optimal** location of STATCOM in the IEEE 30 bus to minimize the value of voltage deviation. For finding the **optimal** location of STATCOM we use the evolutionary computational technique called particle swarm optimization (**PSO**) technique. We use the Newton-Raphson method to find the value of voltage at each and every bus. Voltage deviation is calculated by a objective function which is minimize to find the minimum value of voltage deviation .first we find the **optimal** allocation of one STATCOM in IEEE 30 bus by simple minimizing the value of objective function and after that we will use two STATCOM simultaneously and find the **optimal** allocation of them by **using** particle swarm optimization technique..

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Various advance optimization techniques have been derived from optimization behavior of natural things and can be applied in solving the complex problems like power **considering** the single objective function including genetic algorithm (GA), Simulated Annealing (SA), Tabu Search (TS) and **PSO** Algorithm. These are Evolutionary programming algorithms (EP) which use mechanics of evolutions to produce **optimal** solutions to a given problem. It works by evolving population of candidate solutions towards the global optimum solution. Some of the literature is discussed below:

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