This paper presents a fuzzy system for reliability-based power distribution network planning. The proposed Mamdani type fuzzy inference system with subsequent application of the Bellman-Zadeh decision-making method is used to evaluate the reliability of the power line feeders as criteria for power system planning. Unplanned outages of system components, the Energy Not Supplied (ENS) and age of the power lines are used as input variables of the system and are fuzzified using triangular fuzzy functions. The proposed model was tested on a model of a realistic distribution network in order to prove its relevance and applicability. Results demonstrated that this model could make a contribution in this field as it can be used in practical planning situations for project priority ranking.

This paper investigates the influence of electric vehicle charging station variations for the cases with and without supplementary renewable sources integration, concentrating on symmetry and voltage stability of the network. The study was performed on a realistic low voltage network using is the load flow analysis in DIgSILENT Power Factory software and P-V method. The analysis is based on defined variations for analysis of the baseline variation and electric vehicles with and no additional source as the PV system. It was demonstrated that the complementary operation of EVs and PV can, if planned properly, improve the power system voltage quality parameters.

Electrical power systems throughout the world experience an unprecedented transformation. One of the main motivation for this is a transition from conventional power generation technologies towards renewable energy sources (RES). This transformation has numerous positive effects on power systems, environment and social engagements on a global level. However, poorly planned and allocated RES add complexity to power systems operations and can cause numerous challenges. This paper investigates some of the most common parameters used in the RES grid integration process. In particular, the impact of different PV penetration levels on energy losses and transformer current loading in a PV predominated power system are presented. The analysis is performed in DigSILENT® Powerfactory software using quasi-dynamic analysis on a modified IEEE 14 bus system. The results demonstrated that the energy losses could be reduced until the critical point of PV penetration. After the critical point is reached, the energy losses start to grow rapidly. The current loading of the transformers also tend to reduce with the increase in PV penetration until the critical point and rapidly grow after the critical point. In conclusion, results presented in this work demonstrate the importance of appropriate RES integration planning and analysis, which remains an important engineering task.

The increasing integration of renewable energy resources into distribution systems promotes microgrids as important and emerging network concept. The coordination control between the photovoltaic (PV) generator and the battery energy storage system (BESS) is required to provide a necessary amount of active power in the system. Method for voltage regulation for a microgrid which consists of a PV generator with the maximum power point tracking (MPPT) control and BESS in the stand-alone mode of operation is presented in the paper. MATLAB/Simulink is used to perform all simulation studies. The validity of the proposed methods is clearly verified on the model of a real distribution network, which might be operated as a microgrid. Obtained results demonstrate that the suggested method can be used for effective voltage regulation in microgrid applications, which remains a vibrant field of research.

Abstract Power systems around the world have undergone a number of important organizational, structural and technological changes over the past few decades; they are a direct consequence of the electricity market liberalization and transition from conventional energy conversion technologies towards renewable resources. These changes represent many advantages as well as challenges for the Distribution System Operator (DSO). The aim of this paper is to review the most important principles, objectives and technical criteria used in planning the development of the electricity distribution network. Presented principles can be used as basic guidelines when developing short-term and long-term plans for the construction and reconstruction of power distribution facilities. This paper also presents a methodological approach to the planning and ranking of proposed electricity facilities with an example from practice that is based on the real planning problem in ED Mostar. The basic conclusion of the paper is that the identification of objectives, criteria and the application of an appropriate and unique methodology is of the utmost importance for formulating the framework of the planning process.

This paper presents a method for distributed generation (DG) allocation in low voltage distribution network based on the total annual energy loss reduction and Artificial Neural Network (ANN). The proposed method is applied to the PV solar based DG allocation problem in the low voltage distribution network using realistic network data and measurements. This research is motivated by numerous realistic issues faced by the Distribution System Operator in the area of DG planning. The main objective of this work is to develop, test and validate a robust method for DG allocation which can be used in practical problems without the need for extensive system modelling and load flow analysis. The results confirm the importance of appropriate DG planning and show that the proposed method can be used as a promising tool for efficient and effective DG allocation in low voltage distribution network.

The use of Distributed Generation (DG) throughout the world increasing. DG siting and sizing is an important engineering consideration, which is inherently influenced by the system load and DG power output uncertainties. This paper presents research results of the uncertainty influence on DG allocation problem. This influence is investigated using a constrained optimization problem for power loss reduction. The optimization is performed using Genetic Algorithm. The power system load and DG power output uncertainties are addressed using a possibilistic (α – cut method). The algorithm is applied to realistic distribution system to demonstrate its practical relevance. Results indicate that DG can reduce losses. and that uncertainties play a major role in final optimisation results. This paper contributes to the existing knowledge by applying, to a realistic test power system, a DG allocation method, which considers the influence of load and generation uncertainties on optimization results.