Faculty of Electrical Engineering and Information Technologies
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Item type:Publication, Оптимално управување со токови на енергија во микромрежи приклучени на дистрибутивната мрежа(2022-09); ; Zenku, ImerThe increased penetration of renewable energy sources, as well as the higher standards for quality electricity, actualize the implementation of microgrids into the standard power system. Microgrids provide consumers with higher reliability of power supply, and characterize with lower costs and lower power losses. Microgrids consist of many different distributed generators, more interconnected consumers, batteries and backup generators, and therefore optimization is mandatory for proper and balanced operation of the microgrid. The paper analyses the problem of optimal energy management in a hybrid system (microgrid), which consists of a photovoltaic and wind generators, connected to the distribution network. Also, the microgrid includes industrial prosumers. An upgraded genetic algorithm is applied in the optimization, which takes into account the technical limitations of the installed equipment and the voltage levels in the nodes. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimization of Grid-Connected Microgrids with Residential Prosumers Using an Improved Genetic Algorithm(2024); With the continuous increase of the microgrids’ implementation into the power system the problem of maintaining their stability and balance arises and the necessity to adopt an appropriate energy management system emerges. This paper analyses the optimization of the grid-connected microgrid, which consists of a photovoltaic generator, a wind generator, a battery, and residential prosumers. The paper presents the application of an improved genetic algorithm, which takes into consideration the voltage levels on the connection points of the generators and the prosumers, as well as the trading with the local grid. The proposed algorithm suggests the usage of the standard genetic algorithm with the improvement in the fitness and selection process. The results of the simulation are compared with the results obtained when using a standard genetic algorithm with five different types of selection. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Оптимизација на микромрежи поврзани на дистрибутивна мрежа со примена на подобрен генетски алгоритам(2024-10); Енергетската криза со која се соочува светот денес, како и потребата од чиста и одржлива енергија, ги ставаат микромрежите во центарот на вниманието на истражувачите. Нивната работа има позитивно влијание на работата на електроенергетските системи, но поради стохастичната природа на дисперзираните генератори од обновливите извори кои се поврзани на нив, работата на микромрежите може да има негативно влијание на електроенергетскиот систем доколку не е правилно управувана. Оттука, произлегува потребата за оптимизација на микромрежите. Во овој труд ќе биде разгледан проблемот со оптимално управување со токови на енергија во микромрежа која е поврзана на дистрибутивната мрежа. Методот на оптимизација во овој труд, предлага примена на генетски алгоритам со подобрување во делот на евалуација на потенцијалните решенија и селекција на индивидуи кои ќе генерираат нова генерација. Добиените резултати се споредени со веќе докажани методи за селекција и со тоа се оправдува предложеното подобрување. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Electricity Theft Detection Based on Temporal Convolutional Network with Self-Attention(IEEE, 2023-06) ;Marija Markovska ;Branislav Gerazov ;Aleksandra ZlatkovaDimitar Taskovski - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Multi-horizon energy consumption forecasting on daily basis(IEEE, 2023-06) ;Aleksandra Zlatkova ;Bodan Velkovski ;Zivko Kokolanski ;Branislav GerazovMarija Markovska - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis and forecasting energy consumption for educational institutions(2022-06) ;Aleksandra Zlatkova ;Marija Markovska ;Branislav GerazovDimitar TaskovskiThe energy forecasting is one of the biggest challenges in last years. Nowadays, the problems as energy and economic crises, growth of population, fast development of technology impose the need of energy forecasting. In this paper, three popular deep neural networks: Stacked LSTM, LSTM encoder-decoder and CNN-LSTM encoder-decoder are used for forecasting energy consumption. They are trained and tested on time series that represent the energy consumption of Faculty of Electrical Engineering and Information Technologies in Skopje. The prediction is based on energy consumption in past 24 hours. The proposed models are evaluated with two metrics: RMSE and MAE. All three models show high performance, but LSTM encoder-decoder achieves the highest accuracy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Electricity Consumption Forecasting and Theft Detection: Challenges and AI-based Solutions(CIGRE North Macedonia, 2023-09) ;Marija Markovska ;Aleksandra Zlatkova ;Branislav Gerazov ;Bodan VelkovskiZivko KokolanskiForecasting the electricity consumption is a very current and at the same time extremely difficult challenge. It is current because there is still no efficient way to store the produced electricity, so the produced amount must not exceed its consumption, in order to avoid the expensive overloading of production plants and the distribution network. It is difficult because although consumption has repetitive seasonal dynamics, it also follows irregular trends, and is subject to random unpredictable variations. An example of this type of variation is the non-technical loss of electricity, i.e. errors in meter reading, errors in accounting, broken or faulty infrastructure and electricity theft. From these, electricity theft is of the greatest interest. Hence, the challenge of accurate prediction of electrical energy consumption is compounded by the challenge of fast detection of these non-technical losses. The response to the mentioned challenges will contribute to a stable power energy system that will deliver high quality electricity. It will have a positive impact on the economy in the country. Most importantly, it will contribute to the preservation of the environment because it will enable optimization of electricity production, reducing the load on production plants and the distribution network. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The UbiLAB Framework for Remote Laboratories(IEEE, 2023-06) ;Marija Kalendar ;Zivko Kokolanski ;Branislav Gerazov ;Gorjan NadzinskiMarija Poposka
