SHORT-TERM POWER SYSTEM HOURLY LOAD FORECASTING USING ARTIFICIAL NEURAL NETWORKS

Artificial neural networks (ANN) have been used for many application in various sectors. The learning property of an ANN algorithm in solving both linear and non-linear problems can be utilized and applied to different forecasting problems. In the power system operation load forecasting plays a key role in the process of operation and planning. This paper present the development of an ANN based short-term hourly load forecasting model applied to a real data from MIBEL – Iberian power market test case. The historical data for 2012 and 2013 ware used for a Multilayer Feed Forward ANN trained by Levenberg-Marquardt algorithm. The forecasted next day 24 hourly peak loads and hourly consumptions are generated based on the stationary output of the ANN with a performance measured by Mean Squared Error (MSE) and MAPE (Mean Absolute Percentage Error). The results have shown good alignment with the actual power system data and have shown proposed method is robust in forecasting future (short-term) hourly loads/consumptions for the daily operational planning

Prvi cjeloviti višefazni elektroenergetski sustav na svijetu – Krka Šibenik

Značajni iskoraci u razvoju elektrotehnike učinjeni su u 19. stoljeću. To je vrijeme Tesline prve hidroelektrane Niagara Falls na rijeci Niagari te vrijeme uspostavljanja prvih električnih sustava na području Europe. Manje je poznato da se u to vrijeme veliki pothvat događao i u Hrvatskoj što je i prepoznato u međunarodnoj stručnoj javnosti 2013. godine. Hidroelektrana Krka (kasnije nazvana Jaruga I) na slapovima rijeke Krke uvrštena je na popis povijesno važnih inženjerskih iskoraka u svijetu kroz IEEE-ov program Milestone (Miljokaz) kao najstarija izmjenična hidroelektrana na ovom pro- storu i sastavnica jednog od prvih cjelovitih elektroenergetskih sustava u svi- jetu. Ovaj rad predstavlja povijesnu pozadinu i aktivnosti vezane uz nastaja- nje sustava Krka-Šibenik koji su doveli do njezinog puštanja u pogon 1895. godine te kasnije promjene i rad hidroelektrana na toj lokaciji kroz preko stoljeća dug radni vijek

Determining the Transmission Capacity of Existing Transmission Lines Under High Wind Generation Conditions

Determining the transmission capacity of existing transmission lines is determine by the conductor current. Transmission line can withstand current below thermal standpoint limit to avoid irreparable damage to conductor. The maximum value of current can be determined with static approach (STR – Static Thermal Rating) and dynamic approach (DTR - Dynamic Thermal Rating). STR is defined by simple calculations and does not change often throughout the year where the DTR is calculated for in time conditions taking into account atmospheric conditions, conductor geometry and conductor current. Most common approach to calculate conductor temperature is done by applying IEEE standard (IEEE 738, 2012) or CIGRE (TB601, 2014). Most congestion in the transmission network occurs during the higher production from wind farms when the wind have significant speed. It is to be expected that similar meteorological conditions (wind speed and direction) will occur on transmission lines in the immediate geographical area of wind power plants. In this paper, analysis of relations between atmospheric parameters (wind speed and direction, ambient temperature and solar radiation) and ampacity is described as functional dependence. Taking historical weather data from meteorological stations, atmospheric conditions on transmission line corridors and taking account the frequency of occurrence of individual meteorological variations ampacity of conductor will be determined. For such determined conditions that are influenced by a certain parameters variation of ampacity have a different rating scales. The obtained results will provide an insight into the current ampacity and the possibilities of the transmission line capacity during the high engagement of wind power plants

SHORT-TERM POWER SYSTEM HOURLY LOAD FORECASTING USING ARTIFICIAL NEURAL NETWORKS

Artificial neural networks (ANN) have been used for many application in various sectors. The learning property of an ANN algorithm in solving both linear and non-linear problems can be utilized and applied to different forecasting problems. In the power system operation load forecasting plays a key role in the process of operation and planning. This paper present the development of an ANN based short-term hourly load forecasting model applied to a real data from MIBEL – Iberian power market test case. The historical data for 2012 and 2013 ware used for a Multilayer Feed Forward ANN trained by Levenberg-Marquardt algorithm. The forecasted next day 24 hourly peak loads and hourly consumptions are generated based on the stationary output of the ANN with a performance measured by Mean Squared Error (MSE) and MAPE (Mean Absolute Percentage Error). The results have shown good alignment with the actual power system data and have shown proposed method is robust in forecasting future (short-term) hourly loads/consumptions for the daily operational planning

Modeliranje i vrednovanje fleksibilnih više-energijskih sustava u niskougljičnom okolišu.

Aggregating groups of consumers of different energy vectors and generating units at a single location with centralized control is known as the concept of multi-energy microgrid (MEM). However, if those potentially flexible producers and consumers do not have the ability to balance the variability and uncertainty of their renewable energy sources production within them, from the system perspective, they are seen as potential problem in maintaining the equilibrium of production and consumption. One of the key characteristics of the microgrid operation that needs to be achieved is flexibility. Main goal of this research is to quantify this ability of MEM components to provide flexibility. The thesis presents an optimization framework that includes the MILP (Mixed Integer Linear Programming) model enhanced with corrective receding horizon approach in order to capture the value of integrating multiple energy vectors, their optimal operation and their flexibility potential for low carbon energy system. Scientific contributions of the thesis include firstly a mixed integer linear optimisation model for planning and estimating long-term flexibility aspects of multi-energy microgrids; secondly receding horizon corrective scheduling based algorithm for optimal short-term operation of flexible multi-energy microgrids; and finally a model for defining the potential and value of flexibility services of multi-energy microgrids to a low-carbon power system operation.Agregiranje grupa potrošača različitih energetskih vektora te različitih proizvodnih jedinica na jednome mjestu pomoću centralnog upravljanja naziva se konceptom višeenergijskih mikromreža. No, ako je slučaj da ovi potencijalno fleksibilni potrošači i proizvođači nemaju mogućnost balansiranja varijabilnosti i neizvjesnosti proizvodnje iz obnovljivih izvora energije, onda će biti razmatrani kao izvor poremećaja u održavanju ravnoteže između proizvodnje i potrošnje. Mogućnost ostvarivanje fleksibilnog odziva u pogonu mikromreža cilj je upravljanja svim elementima mikromreže. Ovaj rad ima osnovni cilj kvantificirati utjecaj koji različiti elementi više-energijskih mikromreža imaju na fleksibilnost pogona. U sklopu provedenog istraživanja razvijen je simulacijski okvir koji koristi optimizacijski postupak spojen s upravljačkim algoritmom. Sukladno tome, doktorski rad opisuje mješovito cjelobrojni optimizacijski model koji je korišten unutar simulacijskog okvira te koji je proširen s korektivnim upravljanjem temeljenim na pristupu pomičnog horizonta. Doprinos disertacije je izražen kroz 1) mješovito cjelobrojni linearni optimizacijski model za planiranje i estimaciju dugoročne fleksibilnosti više-energijskih mikromreža; 2) algoritam vođenja fleksibilnih više-energijskih mikromreža temeljeno na korekcijskom planiranju kratkoročnog optimalnog pogona jedinica s pomičnim horizontom; 3) model za određivanje potencijala i vrijednosti fleksibilnosti usluga više-energijskih mikromreža u niskougljičnom elektroenergetskom sustavu

Modeliranje i vrednovanje fleksibilnih više-energijskih sustava u niskougljičnom okolišu.

Aggregating groups of consumers of different energy vectors and generating units at a single location with centralized control is known as the concept of multi-energy microgrid (MEM). However, if those potentially flexible producers and consumers do not have the ability to balance the variability and uncertainty of their renewable energy sources production within them, from the system perspective, they are seen as potential problem in maintaining the equilibrium of production and consumption. One of the key characteristics of the microgrid operation that needs to be achieved is flexibility. Main goal of this research is to quantify this ability of MEM components to provide flexibility. The thesis presents an optimization framework that includes the MILP (Mixed Integer Linear Programming) model enhanced with corrective receding horizon approach in order to capture the value of integrating multiple energy vectors, their optimal operation and their flexibility potential for low carbon energy system. Scientific contributions of the thesis include firstly a mixed integer linear optimisation model for planning and estimating long-term flexibility aspects of multi-energy microgrids; secondly receding horizon corrective scheduling based algorithm for optimal short-term operation of flexible multi-energy microgrids; and finally a model for defining the potential and value of flexibility services of multi-energy microgrids to a low-carbon power system operation.Agregiranje grupa potrošača različitih energetskih vektora te različitih proizvodnih jedinica na jednome mjestu pomoću centralnog upravljanja naziva se konceptom višeenergijskih mikromreža. No, ako je slučaj da ovi potencijalno fleksibilni potrošači i proizvođači nemaju mogućnost balansiranja varijabilnosti i neizvjesnosti proizvodnje iz obnovljivih izvora energije, onda će biti razmatrani kao izvor poremećaja u održavanju ravnoteže između proizvodnje i potrošnje. Mogućnost ostvarivanje fleksibilnog odziva u pogonu mikromreža cilj je upravljanja svim elementima mikromreže. Ovaj rad ima osnovni cilj kvantificirati utjecaj koji različiti elementi više-energijskih mikromreža imaju na fleksibilnost pogona. U sklopu provedenog istraživanja razvijen je simulacijski okvir koji koristi optimizacijski postupak spojen s upravljačkim algoritmom. Sukladno tome, doktorski rad opisuje mješovito cjelobrojni optimizacijski model koji je korišten unutar simulacijskog okvira te koji je proširen s korektivnim upravljanjem temeljenim na pristupu pomičnog horizonta. Doprinos disertacije je izražen kroz 1) mješovito cjelobrojni linearni optimizacijski model za planiranje i estimaciju dugoročne fleksibilnosti više-energijskih mikromreža; 2) algoritam vođenja fleksibilnih više-energijskih mikromreža temeljeno na korekcijskom planiranju kratkoročnog optimalnog pogona jedinica s pomičnim horizontom; 3) model za određivanje potencijala i vrijednosti fleksibilnosti usluga više-energijskih mikromreža u niskougljičnom elektroenergetskom sustavu

Modeliranje i vrednovanje fleksibilnih više-energijskih sustava u niskougljičnom okolišu.

Aggregating groups of consumers of different energy vectors and generating units at a single location with centralized control is known as the concept of multi-energy microgrid (MEM). However, if those potentially flexible producers and consumers do not have the ability to balance the variability and uncertainty of their renewable energy sources production within them, from the system perspective, they are seen as potential problem in maintaining the equilibrium of production and consumption. One of the key characteristics of the microgrid operation that needs to be achieved is flexibility. Main goal of this research is to quantify this ability of MEM components to provide flexibility. The thesis presents an optimization framework that includes the MILP (Mixed Integer Linear Programming) model enhanced with corrective receding horizon approach in order to capture the value of integrating multiple energy vectors, their optimal operation and their flexibility potential for low carbon energy system. Scientific contributions of the thesis include firstly a mixed integer linear optimisation model for planning and estimating long-term flexibility aspects of multi-energy microgrids; secondly receding horizon corrective scheduling based algorithm for optimal short-term operation of flexible multi-energy microgrids; and finally a model for defining the potential and value of flexibility services of multi-energy microgrids to a low-carbon power system operation.Agregiranje grupa potrošača različitih energetskih vektora te različitih proizvodnih jedinica na jednome mjestu pomoću centralnog upravljanja naziva se konceptom višeenergijskih mikromreža. No, ako je slučaj da ovi potencijalno fleksibilni potrošači i proizvođači nemaju mogućnost balansiranja varijabilnosti i neizvjesnosti proizvodnje iz obnovljivih izvora energije, onda će biti razmatrani kao izvor poremećaja u održavanju ravnoteže između proizvodnje i potrošnje. Mogućnost ostvarivanje fleksibilnog odziva u pogonu mikromreža cilj je upravljanja svim elementima mikromreže. Ovaj rad ima osnovni cilj kvantificirati utjecaj koji različiti elementi više-energijskih mikromreža imaju na fleksibilnost pogona. U sklopu provedenog istraživanja razvijen je simulacijski okvir koji koristi optimizacijski postupak spojen s upravljačkim algoritmom. Sukladno tome, doktorski rad opisuje mješovito cjelobrojni optimizacijski model koji je korišten unutar simulacijskog okvira te koji je proširen s korektivnim upravljanjem temeljenim na pristupu pomičnog horizonta. Doprinos disertacije je izražen kroz 1) mješovito cjelobrojni linearni optimizacijski model za planiranje i estimaciju dugoročne fleksibilnosti više-energijskih mikromreža; 2) algoritam vođenja fleksibilnih više-energijskih mikromreža temeljeno na korekcijskom planiranju kratkoročnog optimalnog pogona jedinica s pomičnim horizontom; 3) model za određivanje potencijala i vrijednosti fleksibilnosti usluga više-energijskih mikromreža u niskougljičnom elektroenergetskom sustavu

Challenges of High Renewable Energy Sources Integration in Power Systems—The Case of Croatia

This paper presents a high-level overview of the integration of renewable energy sources (RES), primarily wind and solar, into the electric power system (EPS) in Croatia. It presents transmission system integration aspects for the particular case of this country. It explains the current situation and technical characteristics of the current conventional generation units and currently installed wind energy capacities. Based on the current situation future development scenario is determined and used to evaluate the impacts of the wide-scale integration of renewables. Grid connections aspects, power balancing, market participation, and inertia reduction aspects are considered. Furthermore, some specifics of both solar and wind integration are discussed identifying problems and potential solutions. Primarily through the provision of the inertial response of both solar and wind and through better forecasting of wind production. Finally, the outlook for the Croatian power system is given, that will most probably double its RES capacity in the coming 3-year period and a certain level of investments and changes of current operational practices will need to be provided

Wind Power Monitoring and Control Based on Synchrophasor Measurement Data Mining

More and more countries and utilities are trying to develop smart grid projects to make transformation of their power infrastructure towards future grids with increased share of renewable energy production and near zero emissions. The intermittent nature of solar and wind power can in general cause large problems for power system control. Parallel to this process, the aging of existing infrastructure also imposes requirements to utility budgets in the form of a need for large capital investments in reconstruction or maintenance of key equipment. Synchrophasor and other synchronized measurement technologies are setting themselves as one of the solutions for larger wind power integration. With that aim, in this paper one possible solution for wind power control through data mining algorithms used on a large quantity of data gathered from phasor measurement units (PMU) is described. Developed model and algorithm are tested on an IEEE 14 bus test system as well as on real measurements made on wind power plants currently in operation. One such wind power plant is connected to the distribution grid and the other one to the transmission grid. Results are analyzed and compared

Algorithm for Fast and Efficient Detection and Reaction to Angle Instability Conditions Using Phasor Measurement Unit Data

In wide area monitoring, protection, and control (WAMPAC) systems, angle stability of transmission network is monitored using data from phasor measurement units (PMU) placed on transmission lines. Based on this PMU data stream advanced algorithm for out-of-step condition detection and early warning issuing is developed. The algorithm based on theoretical background described in this paper is backed up by the data and results from corresponding simulations done in Matlab environment. Presented results aim to provide the insights of the potential benefits, such as fast and efficient detection and reaction to angle instability, this algorithm can have on the improvement of the power system protection. Accordingly, suggestion is given how the developed algorithm can be implemented in protection segments of the WAMPAC systems in the transmission system operator control centers