Željko Hederić

Optimal Distributed Generation placement in distribution network

This paper presents a method for optimal Distributed Generation placement with goal of reducing active power system losses and voltage level regulation. Active power losses in radial distribution network are determined using an Artificial Neural Network (ANN) by simultaneous formulation for the determination process based on voltage level control and injected power. Adequate installed power of distributed generation and the appropriate terminal for distributed generation utilization are selected by means of a genetic algorithm (GA), performed in a distinct manner that fits the type of decision-making assignment. The training data for ANN is obtained by means of load flow simulation performed in DIgSILENT PowerFactory software on a part of the Croatian distribution network. The active power losses and voltage conditions are simulated for various operation scenarios in which the back propagation ANN model has been tested to predict the power losses and voltage levels for each system terminal, and GA is used to determine the optimal terminal for distributed generation placement.

Small Biogas Plant Stability Prediction Model

In this paper stability prediction for a small biogas plant in islanded mode depending on local consumers energy consumption growth is given. Biogas plant with two cogeneration facilities and local consumers is tested for on grid and islanded operation and thus represents a microgrid. Generator and regulator modelling as well as surrounding electrical grid modelling in software package Power World Simulator are described. Expected consumption growth through the period of 20 years in microgrid area is simulated. All generator important variables, i.e. voltage, frequency, real and reactive power in case of islanded mode are examined and explained. Finally, stability prediction analysis of biogas plant and surrounding consumers for 20 years period is given.

Battery Pack Design Problems – Influence of the Transverse Magnetic Field on Internal Battery Resistance

The battery pack represents an essential part of electric vehicles (EV), so its design significantly influences the drive characteristics. The system of energy flow control in EV use highfrequency power electronic components that cause the appearance of high harmonics super-imposed on DC component of the battery current. This paper examines the influence of the distribution of the transversal magnetic field inside of the battery pack depending on battery pack design and its influence on battery parameters. DC component of the transversal magnetic field inside of battery cells cause Hall effect ions path allocation that is reflected on internal battery resistance negative change. AC component of the transversal magnetic field in electrically closed loops within battery pack induced e.m.s. that also cause negative phenomena on battery pack parameters.

VOLTAGE AND POWER LOSSES CONTROL USING DISTRIBUTED GENERATION AND COMPUTATIONAL INTELLIGENCE

The paper analyzes the possibility of reducing active power losses in power system, constrained by regulated voltage levels, by implementing appropriate distributed generation capacity. The objectives of this paper were achieved by developing hybrid methods based on artificial neural network and genetic algorithm. Methods have been developed to determine the impact of different distributed generation power on all terminals in the observed system. The method that uses artificial neural network and genetic algorithm is applicable for radial distribution networks, and method using load flow and genetic algorithm is applicable to doubly-fed distribution network. For comparison purposes, additional method was developed that uses neural networks for the decision-making process. Data for training the neural network was obtained by power flow calculation in the DIgSILENT PowerFactory software on a part of Croatian distribution network. The same software was used as an analytical tool for checking the correctness of solutions obtained by optimization.

Safety rules for use in electric vehicle charging infrastructure

Development trend in automotive industry is based on development of electric vehicles (EV) and supporting infrastructure. To ensure safety of users and user friendly interfaces, complex systems of power electronics, high voltage and current levels, as well as control systems in real time have priority in research and development. This paper presents an overview of technical solutions and standard procedures related to systems infrastructure for EV power charging, protocols for connections and security systems.