Application of the distributed generation ((DG)) is a direct consequence of deregulation of modern power networks. Regulatory changes and advances in (DG) technologies have led utilities to consider these technologies as alternative to central generation. With regard to regulations imposed by tariff and also the market competition, the exact planning of distribution networks to avoid overinvestment is quite necessary. Most of the studies in this field which were carried out in the past are concerned with investments aiming to maximize the investors’ benefits. In addition, the impact of various (DG) technologies has not been considered in the planning procedure. Each investment planning for (DG) can be assessed from the viewpoint of distribution companies, regulatory entities or consumers. It is obvious that both the distribution companies and consumers regard their own benefits, whereas the regulator will prefer only those plans which benefit both parties. In this paper, a new approach is presented for (DG) investment in distribution network in which the benefits of both entities are taken into account. The benefits for utility are provided through system loss reduction while for consumers via purchasing energy from (DG) instead of grid. These objectives are described as social welfare and its maximization is our main goal in this paper. Furthermore, the impact of (DG) technologies is considered and the best one is selected. The genetic algorithm (GA) is employed to solve this optimization problem since it can provide the global solution by its inherent capability in modeling the complex constraints.

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 of distributed generation sources ((DG)s) will affect the extent and duration of system failures. This will inevitably require the need to review the functioning of the system of protection and re-coordination of the relevant equipment. Because the lack of an appropriate coordination between the (DG) units connected to a distribution system could lead to the exchange of power between these units and the system's instability, improper operation of the system of protection or the unintended islanding of a part of the system. Due to the fact that synchronous machine type (DG)s (SM(DG)s) are the most problematic for system coordination (over-current relays) than other types of (DG)s, in this paper, controlling the output current of generators Synchronization is proposed by tap changer of the transformer connected to it. In this method, the SM(DG)'s participation in the flow of error is limited by the control of the pincer. Before the fault occurred and in accordance with the system conditions, the transformer tapping device connected to the synchronous generator has been changed and it reduces the flow during an error. This strategy, in addition to reducing the generation error of the generators and transformer assembly installed as a dispersed generation source, also increases the permeability coefficient of these sources. The proposed technique is implemented on a sample distribution system in the ETAP software, the results of the simulation show the effectiveness of the proposed method.

The growth of internet services and business dependency on them makes it necessary to assess services weakness before operating them. In its network branch, this needs modelling internet traffic similar to the real world traffic. Single platforms which support generating heavy traffic are costly. Therefore, we introduce a toolkit named distributed Variant Traffic generator (DVTG) which has two main advantages. It is able to generate heavy traffic via a cluster of simple machines and is capable of making diversity in the generating traffic by implementing and embedding various protocols. The tool uses statistical techniques to simulate the actual behavior of network traffic. DVTG can be used to evaluated performance of network and its elements such as switch, router and firewall. Experiments illustrate more than nine gigabits throughput using ten machines each has one gigabits network card. So, the overhead is less than 10 percent.

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.

Lighting passages is done for citizens’ welfare simultaneously with the peak of the consumption of the network, from sunset to sunrise. The present study aimed at designing a model of sustainable urban management in the field of lighting, with simulation of the use of photovoltaic LEDs instead of sodium and halogen lamps. Accordingly, in a system simulation of the network, the scenarios for adjusting the input of various photovoltaic capacities to the electricity supply system of the city of Mashhad have been investigated. The results of on-grid analysis by using this decentralized production pattern shows, taking into account the 200 watts capacity and the 20% utilization factor for each photovoltaic LEDs and installing a photovoltaic LED instead of sodium and halogen lamps, all the power needed to lighting of city streets is provided by photovoltaic solar technology. Moreover, by reducing the potential between fossil and renewable production, emissions of pollutants are reduced by 104, 000 tons. Therefore, this method can be used to manage clean and sustainable energy in urban scale consumption, and, while helping the environment and reducing air pollution, it prevents losses caused by the transfer of electrical energy from the plant to the place of consumption.

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.

In this paper, an intelligent islanding detection method is presented for inverter based distributed generation ((DG)) using probabilistic neural network (PNN) and wavelet transform. The presented method is based on the change of (DG) reactive power reference (Qref) in inverter control interface to create a small forced transient in frequency and its derivative. Changing the Qref causes a forced transient in system frequency and also in its derivative in islanding conditions. The main idea is to use the created transient in frequency derivative in islanding conditions. The PNN is trained by features extracted from the frequency derivative data through the discrete wavelet transformation (DWT) in islanding and non-islanding conditions. The proposed method is evaluated in islanding and non-islanding conditions, using PSCAD/EMTDC and MATLAB software. Simulation results show that the proposed method has a proper operation in the islanding and non-islanding conditions.

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.