Project Description

The share of renewable energy sources (RES), especially wind power, in electric power systems (EPS) around the world is rapidly increasing [1] and this trend is expected to continue in the future [2], [3]. Same trends are to be expected in Croatia who, as a new member of the European Union (EU), is obliged to follow mandatory regulations on energy and environmental protection, such as "EU Energy and Climate Package" [2]. This often cited document has set ground for future strategies indicating a goal of 20% share of RES in total energy balance by year 2020, together with 20% more efficient energy use, 20% reduced CO2 emissions and 10% more efficient transport. Pathways for achieving the underlying objectives are defined in several documents: "Third Energy Package [3]" from 2009, "Strategic Research Agenda for the European electricity network in the future [4]" from 2007 and "SmartGrids SRA 2035 Strategic Research Agenda Update of the SmartGrids SRA 2007 for the needs by the year 2035 [5]" from 2012. In these documents it is clearly shown that development of Smart Grids and related technologies are strongly connected with growing RES shares and growing requests on the grid to enable their integration. Major stakeholders in the field of Smart Grids have established the “European Technology Platform on Electricity Networks of the Future in order to foster cooperation in the field and to design and implement a Strategic Research agenda (European Technology Platform SmartGrids [6] and Smart Grids Roadmap [7]). Problems frequently pointed out by the opponents of high RES integration is the stochastic nature of electricity production of such resources and difficulties related to planning and accurately predicting their output in time. A large share of variable RES will inevitably cause changes in the EPS control and dynamics. If not handled adequately this can lead to significant disturbances or even outages of some of the vital components in the EPS (generation shortages, line overloads etc). On the other hand growing environmental awareness and strong political impetus have promoted plug-in hybrid electric vehicles (PHEV) as an attractive means of transportation. With higher acceptance of such way of transportation the unpredictability of consumption is increased as well. The prevailing concern is that the combined impact of a large number of randomly connected PHEVs in the distribution network which if not handled correctly can have various negative consequences [8], [9]. Traditionally, dispatchable generation units provide the necessary flexibility in achieving the continuous balance between supply and demand. While the power balance is established through an arrangement of automatic controls, integral (e.g. hourly) amounts of energy vital for system balance are procured in energy markets based on predictions. RES and PHEV dramatically influence the security of energy supply and stability of the whole EPS. In some cases, if no responsive changes to the grid are made, it could cause overloads and congestions in the network. This makes the EPS control significantly more complicated. Passive approach to PHEV integration and charging could have a significant impact on the overall load of future transmission and/or distribution (T&D) networks. This would result in need to upgrade current T&D grids in order to efficiently accommodate a growing PHEV fleet. Challenges lay in recognizing wheatear to invest in network reinforcements or can intelligent usage and control of flexible resources assist the system operators. A similar reasoning can be applied to the distributed generation, especially technologies with the potential of multi energy vector interaction (efficient electric heating, combined heat and power, battery storage etc.). The complexity of the security of energy supply requires a comprehensive and multi-disciplinary framework. The traditional formula for grid owners has been to increase the EPS capacities, i.e. generation and line capacities. This economically inefficient way is even less viable due to the difficulties in obtaining line corridors, long-lasting permits processing etc. Since in many cases the grid overloads and generation shortages are only temporary and it is necessary to find more efficient and cheaper ways of solving the described problem. The progressive re-engineering of the European electric power system will involve a spectrum of innovative and flexible technologies (various energy storage modules, PST (Phase Shift Transformer), HVDC (High Voltage DC Transmission), WAMS (Wide Area Monitoring System), smart metering etc. [10]) –all integrated into the Smart Grid concept. SG is based on wide-scale implementation of novel information and communication technology (ICT) at all EPS voltage levels. Various control architectures, often utilizing aggregation principles, have been proposed in this context, such as Virtual Power Plants, Cells, or MicroGrids.

The energy (power) node concept

Key references

[8] A. Rautiainen, S. Repo, P. Järventausta, A. Mutanen, K. Vuorilehto, and K. Jalkanen. Statistical Charging Load Modeling of PHEVs in Electricity Distribution Networks Using National Travel Survey Data, IEEE Transactions on Smart Grid, 3(4), 2012, pp. 1650-1659
[9] D. Steen, L. A. Tuan, O. Carlson, L. Bertling. Assessment of Electric Vehicle Charging Scenarios Based on Demographical Data, IEEE Transactions on Smart Grid, 3(3), 2012, pp. 1457-1468
[10] A. L’Abbate, G. Migliavacca, T. Pagano, A. Vaféas. Advanced transmission technologies in Europe: a roadmap towards the Smart Grid evolution, 2011 IEEE PowerTech, Trondheim, Norway, 19-23 June, 2011, pp. 1-8
[11] Chicco G, Mancarella P. Distributed multi-generation: a comprehensive view. Renewable and Sustainable Energy Reviews 2009; 13 (3): 535-551.
[12] Chicco G, Mancarella P. Distributed Multi-Generation: energy models and analyses. Nova Publisher, New York; 2009.
[13] Yang C. Hydrogen and electricity: parallels, interactions, and convergence. International Journal of Hydrogen Energy 2008; 33 (8): 1977-1994.
[14] P. Mancarella. Distributed Multi-Generation Options to Increase Environmental Efficiency in Smart Cities, IEEE Power and Energy Society General Meeting, San Diego, USA, 22-26 July, 2012, pp. 1-8
[15] K. Heussen, S. Koch, A.s Ulbig, G. Andersson. Energy Storage in Power System Operation: The Power Nodes Modeling Framework, Innovative Smart Grid Technologies Conference Europe (ISGT Europe), Gothenburg, Sweden, 11-13 October, 2010, pp. 1-8
[16] G. Andersson. A Modeling Framework for Future Energy Systems, ETH Zurich, presentation, 2012
[18] F. Blaabjerg, R. Teodorescu, M. Liserre, A.V. Timbus. Overview of Control and Grid Synchronization for Distributed Power Generation Systems, IEEE Transactions on Industrial Electronics, 53(5), 2006, pp. 1398-1409
[19] Clement-Nyns, K., Haesen, E. & Driesen, J., 2010. The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid, IEEE Transactions on Power Systems, 25(1), pp. 371-380
[20] P. D. Brown, J. A. Pecas Lopes, and M. A. Matos, “Optimization of pumped storage capacity in an isolated power system with large renewable penetration,IEEE Trans. Power Syst., vol. 23, no. 2, pp. 523-531, May 2008.
[21] A. A. Akhil, G. Huff, A. B. Currier, B. C. Kaun, and D. M. Rastler, “DOE/EPRI 2013 Electricity Storage Handbook in Collaboration with NREC, Sandia National Laboratories, Report SAND2013-5131, July 2013.
[22] Machowski, J., Bialek, J.W. & Bumby, J.R., 2008. Power System Dynamics: Stability and Control, John Wiley-Sons, Ltd.
[23] Sortomme, E. & El-Sharkawi, M.A., 2012. Optimal Combined Bidding of Vehicle-to-Grid Ancillary Services. Smart Grid, IEEE Transactions on, 3(1), pp.70-79.