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.

The aim of this paper is to present and discuss the influence of distributed generation on power quality. Nowadays, interest in power quality has increased since it has become a very important issue in power system delivery. One of the major problems of ensuring a certain level of power quality are harmonics. The aim of this project is to investigate an impact of photovoltaic (PV) on harmonic voltage distortion (HD) in real MV distribution network. Different scenarios will be implemented where solar power plant is going to be modelled with high variability of load and generation to see their effects on the systems power quality (PQ). Those scenarios are when PV is disconnected from the grid and PVs are connected with 2 different powers. Results presented below showed that PV improves power quality of the system, because their inverters are source of harmonics and they increase HD. However, that impact is not very significant and harmonic limits are not violated. A load flow analysis is done for the model of test system 110/35/10kV in which a distributed generator is added, that is on-grid or off-grid. The network modelling and simulation is done in DIgSILENT PowerFactory software.

ABSTRACT The Online Biomass Potential Atlas is a tool primarily intended for geo-visualisation of biomass data from the Biomass Potential Monitoring System in Bosnia and Herzegovina. However, its role does not have to end here. By developing a functional extension, it can offer an environment for the location analysis of potential biomass users and sources of unused biomass potential. This paper describes an approach for developing tool with such functionality, based on spatial interaction modelling. Determining the optimal location for biogas plants in the region covered by the administrative units of two cantons in Bosnia and Herzegovina is considered as a case study. Based on the analysis conducted in the case study, the feasibility of applying this tool has been demonstrated.

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.

The ascending trend in retail electricity prices since the first energy package is often blamed on the market reforms and the cost of a low carbon economy. The present study analyzes EU-28 statistical data on retail prices for the medium households and industries, for the years 2008–2017, a period of economic slowdown. We focus especially on six countries, Austria, Denmark, Germany, Greece, Latvia and Spain and examine retail prices against the degree of renewable energy sources (RES) penetration and the market liberalization in each country. We also examine the cases of three Western Balkan countries that still have a very low degree of liberalization. The increasing percentage of RES in electricity generation, the number of retailers and the market share of the main retailer are analyzed with respect to the retail electricity price for the period studied. In spite of the different specifics of each country's economy, there are certain common trends. The price increase has been found to be the result of levies and taxes, rather than the energy cost, with the burden carried mostly by households. In the cases studied here, the increase correlates with either the increase in RES or increased competition or both depending on the market structures in place during the examined period and the maturity and performance of the measures towards a liberalized electricity market and a low carbon economy.

Noninvasive load monitoring have been investigated by researchers for decades due to its cost-effective benefits. Upon introduction of smart meters, obtaining data about power consumption of households became easier. Numerous different techniques have been applied on the power consumption data to gain useful information out of it. This study applies machine learning techniques (Bayes network, random forest and rotational forest) to determine the operation state of households, where households are assumed to be either in ON or OFF state. Tracebase power consumption signature repository was used to train and test proposed machine learning models. Tracebase dataset was preprocessed to generate 4 different datasets. Test results have shown that these machine learning algorithms are able to estimate operation state with high accuracy and Bayes network shows outstanding performance among them with overall accuracy of 95%. Proposed method is extremely cost-effective for load monitoring and could replace some of the physical sensors in the smart houses.

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.

This paper presents a new algorithm for distribution system reconstruction planning based on Mamdani type fuzzy inference and BellmanZadeh multi criteria decision making method. The proposed algorithm takes system attributes as inputs (number of customers served by renewed infrastructure, energy losses, power demand and cost of investment) and returns crisp output values which are used as planning criteria. The aim of this paper is to provide a logical decision making framework which can be used to model, evaluate, and rank projects according to required criteria. The proposed model is flexible and can be extended to include additional planning criteria. The proposed method is tested on a realistic distribution system to demonstrate its relevance. It is expected that this paper will make a contribution toward more effective management of power distribution network planning process and that it will be used by planning engineers in practical problems.