1.

Member of editorial board of scientific journal "Reliability engineering & systems safety"with science impact factor (IF 2012: 1.901, IF 2011: 1.770)

Scientific journal "Reliability engineering & systems safety" is one of the most important journals in the field of reliability.

C.06 Editorial board membership

2.

Leader of technical committee: Quantitative Risk Analysis

ESRA (European Safety and Reliability Association) is a society of professionals from the field of safety and reliability methods development and application. Leader of technical committee Quantitative Risk Analysis takes care about several tenths of research papers at yearly conference ESREL (European Safety and Reliability).

D.03 Membership in foreign/international boards/committees

3.

Participation of wind turbines in frequency regulation in power systems

In the dissertation, a novel wind turbine management method is presented that enables wind turbines to participate in frequency regulation. This method can be applied in power systems with large shares of renewable energy sources. As wind generation is stochastic, the generation variability effects the production of energy and consequently affects the frequency in the power system. By using the proposed method, the effects of frequency deviation can be mitigated, i.e. the method enables wind turbines to participate in frequency control.

D.09 Tutoring for postgraduate students

COBISS.SI-ID: 10071124

4.

IT solutions for mastering dynamic simulations of power system

Verified model of Slovenian electric power system for dynamic simulations which among others serves as a basis for development of the WAMPAC system

F.17 Transfer of existing technologies, know-how, methods and procedures into practice

COBISS.SI-ID: 9767252

5.

Demand-side provision of active power reserve

In the thesis we present a new stochastic modelling approach of demand-side reserve provision in co-optimized day-ahead electricity and reserve markets. The model is composed of two parts: in the first part an optimisation algorithm is presented. The algorithm presents co-optimized day-ahead electricity and reserve markets. In the second part input parameters of the optimization algorithm are presented and modelled. Since the periods in which the consumers provide system reserve are typically followed by load recovery periods, the energy payback effect is also considered in modelling of the demand-side reserve provision. This approach minimizes the electricity production costs, the cost of scheduled reserve and the expected cost of deployed reserve used to maintain a balance of electricity supply and demand. The proposed methodology could be beneficial for demand-side aggregators, suppliers or large industrial consumers who can use it to determine the optimal market offering strategy on the co-optimized day-ahead energy and reserve electricity markets.