Degrees of Freedom in Sharing Control of Smart Grid Connected Devices A framework for comparison of cross-organizational control sharing mechanisms for balancing supply & demand Kristian Helmholt, Department: Business Information Services TNO Groningen, The Netherlands Kristian.Helmholt@tno.nl Gerben Broenink, Department: Information Security TNO Groningen, The Netherlands Gerben.Broenink@tno.nl Abstract—Electricity networks require a balance between supply & demand of power in order to maintain stability and to provide a good power quality. The growth of renewable energy sources makes obtaining balance more difficult, because of their intermittent power profiles. Financial incentives for producing ‘green electricity’ locally also increase complexity due to the larger geographical distribution of electricity generation. Not surprisingly, more sophisticated (distributed) control mechanisms for balance in (smart) electricity grids are being proposed. Some of these proposals attempt to solve the problem of balance by managing demand, and thus introduce the concept of sharing control of devices connected to the grid. However, sharing control could introduce imbalances in ‘societal’ power between governments, companies and consumers. We propose that all parties involved should consciously decide on what amount of control they want to share. We provide a framework for comparison of control sharing mechanisms. Keywords-Smart grid; control sharing; privacy. I. INTRODUCTION: WHERE DOES IT SAY SHARING IN ‘GRID CONTROL’? The concept of ‘control of an electricity grid’ can have different meanings. In this paper, we mean control with respect to obtaining balance between supply and demand of power in electricity grids. In an electricity grid, it is quintessential that the total consumption of power is continuously equal to the total production of power. If this is not the case, the quality of the provided power will degrade. In classic grids (as opposed to future ‘smart’ grids), control mechanisms are already put into place in order to deal with the variation in demand by power consumers. When consumers demand more power from the grid, power producing parties connected to the grid have to provide more power as a whole (group). In the future, more will be demanded from control mechanisms [11]. They have to be able to deal with the increase of more distributed and renewable power sources with variable output (wind, solar, wave, etc.).A solar cell or wind turbine cannot be powered down without wasting valuable energy. Also, wind turbines can not be immediately shut down by turning them away from the wind. Another problem is the fact that the power flow is changing from one way to two way. In the classic grid, there are a few ‘centralized’ large power plants and many distributed users. In future grids, there might be many distributed small power plants: home-owners with a wind mill, solar panels, geothermal installations, etc. that have a surplus in electricity production. This does not only reduce the accuracy of prediction the production of power – since it is now closely related to the weather–, but also the accuracy of the prediction of power transported across the grid, since locally generated electricity is consumed ‘first’ before more power is demanded from the grid. Another reason why more intelligence in the energy grid is needed, is that the rise of the usage of Plug-in (Hybrid) Electrical Vehicles (P(H)EV) seems to become a real challenge [12]. It is not unlikely that PHEVs will be plugged into the grid at almost the same time (when people come home from work). This will create a huge demand for power in a relatively short time, possibly resulting in a grid overload. The grid was not dimensioned with all this in mind. With the current grid it seems likely new control mechanisms have to be put in place. Currently, ‘Demand Response’ (DR) of devices connected to the grid is being used in several research projects as a new means of control [13]. Depending on the amount of power that is consumed by devices, it can make sense to switch devices on and off in order to attain balance in the grid. Since DR almost always requires somebody or something else than the owner of the device to (automatically) switch on or switch off the device, device owners are no longer fully in control. For example, when DR is applied at charging PHEVs, the charging process may have to wait for a signal ‘from the electricity network’ that tells the car to start charging. As a society, we should decide how much we want others to be in control of the grid-connected devices we own. For example, do we want to control our own devices in our own home, as we do now, or do we want having our devices controlled by some ‘entity’ in the electricity grid in order to have balance in the electricity grid? To make this decision we need a framework for comparison, which we provide in the remaining sections of this paper. In the next section, related research on this topic will be given. We will see that much research is done, however almost no research is done in comparing different solutions 34 Copyright (c) IARIA, 2012. ISBN: 978-1-61208-189-2 ENERGY 2012 : The Second International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies