Islanded operation of distributed generators is a problem that can happen when they are connected to a distribution system. In this paper an islanding detection method is presented for inverter based distributed Generation ((DG)) using under/over voltage relay.The method is an adaptive one and is based on the change of (DG) active power reference (Pref) in inverter control interface. The active power reference has a fixed value in normal condition, if the Point of Common Coupling (PCC) voltage changes, Pref, is determined as a linear function of voltage. The slope of Pref depends on the load active power (Pload) and it should be changed if Pload changes. The Non-Detection Zone (NDZ) of the proposed method is zero. If changing of the PCC voltage is sensed, islanding will be detected when it occurs. Also, it does not have any negative effects on the distribution system under normal conditions. The proposed method is evaluated according to the requirements of the IEEE 1547 and UL 1741 standards, using PSCAD/EMTDC software.

The presence or absence of distributed generation ((DG)) sources in a distribution network has a probabilistic nature. In the event of connection or disconnection of these sources, the fault current through a relay and the relay operating time are affected, which leads to miscoordination. For solving this issue, coordination constraints corresponding to the presence or absence of (DG)s have to be considered in the overcurrent relay coordination problem (CP). The incorporation of these constraints increases the operating time (OT) of the conventional overcurrent relays (OCRs). In this paper, a novel adaptive characteristic is proposed to solve this unwanted effect. Accordingly, a function proportional to the equivalent impedance (EI) seen by the relay is added to the relay characteristic. This EI is calculated via in-situ measurement of voltage and current before the occurrence of a fault, continuously; when the fault occurs, the calculated impedance is used in the relay characteristic to determine the OT. The addition of this function to the conventional overcurrent relay characteristic, reduces the effects of disconnecting the (DG)s on the coordination constraint, and in general, improves the OT of the relay. Based on the analytical relations and simulation results, it is shown that the OTs of the primary and backup relays with the proposed characteristic are improved compared to the relays with the conventional characteristic.

Distribution system supplies power to variety of load depending upon the consumer’ s demand, which is increasing day by day and lead to high power losses and poor voltage regulation. The increase in demand can be met by integrating distributed generators ((DG)) into the distribution system. Optimal location and capacity of (DG) plays an important role in distribution network to minimize the power losses. Some researchers have studied this important optimization problem with constant power load which is independent of voltage. However, majority of consumers at load center uses voltage dependent load models, which are primarily dependent on magnitude of supply voltage. In practical distribution network, the assumption of constant power load can significantly affect the location and size of (DG), which in turn can lead to higher power losses and poor voltage regulation. In this study, an investigation has been performed to find the increase in power loss due to the use of inappropriate load models, while solving the optimization problem. Furthermore, an attempt has been made in this study to reduce power losses occurring in large test bus systems with loads being dependent on voltage rather than the constant power load. Different test cases are created to analyse the power losses with appropriate load model and in-appropriate load model (constant power load model). The load at distribution network is not mainly dependent on any single type of load model, it is a combination of all load models. In this study, a class of mix load viz., combination of residential, industrial, constant power, and commercial load, is also considered. In order to solve this critical combinatorial optimization problem with voltage dependent load model, which requires an extensive search, Adaptive Quantum inspired Evolutionary Algorithm (AQiEA) is used. The proposed algorithm uses entanglement and superposition principles, which does not require an operator to avoid premature convergence and tuning parameters for improving the convergence rate. A Quantum Rotation inspired Adaptive Crossover operator has been used as a variation operator for a better convergence. The effectiveness of AQiEA is demonstrated and computer simulations are carried out on two standard benchmark large test bus systems viz., 85 bus system and 118 bus system. In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. Tabulated results show that the location and size of (DG)s determined using in-appropriate load model (constant power load model) has significantly high power losses when applied in distribution system with different load model (other voltage dependent load models) as compared with the location and size of (DG)s determined using the appropriate load model. Experimental results indicate that AQiEA has a better performance compared to other algorithms which are available in the literature.

This study presents a dynamic way in a (DG) planning problem instead of the last static or pseudo-dynamic planning point of views. A new way in modeling the (DG) units’ output power and the load uncertainties based on the probability rules is proposed in this paper. A sensitivity analysis on the stochastic nature of the electricity price and global fuel price is carried out through a proposed model. Six types of clean and conventional (DG) units are included in the planning process. The presented dynamic planning problem is solved considering encouraging and punishment functions. The imperialist competitive algorithm (ICA) as a strong evolutionary strategy is employed to solve the (DG) planning problem. The proposed models and the proposed problem are applied on the 9-bus and 33-bus test distribution systems. The results show a significant improvement in the total revenue of the distribution system in all of the defined scenarios.