Task 4.1: Distributed Scheduling of Flexible Demand in Smart Grids
In recent years, following environmental concerns and technological developments, power systems have been undergoing significant changes, moving from a traditional centralized structure towards the distributed and decentralized concept of the “smart grid”. As a consequence, in the near future, energy generation will be subject to an increasing level of uncertainty and decentralization. In order to guarantee a reliable operation of the grid and achieve efficient utilization of its current assets, it will be necessary to rethink the current centralized approach and involve other entities, such as storage or flexible demand, in the network’s operation. This case study aims at designing decentralized control strategies for the efficient integration of flexible demand in power systems.
The main objective is to achieve coordination of flexible demand (i.e. energy storage units) by adopting a price-based approach, applying elements of game theory and equilibrium concepts to large populations of interconnected smart devices. The analysis will pursue the best trade-off between the satisfaction of individual agents’ requirements and optimization of the system’s level objective functions (social optimization) by allowing the emergence of coalitions within the agents’ population. The scalability of the control strategy will constitute a key element in the design process and different modeling options will be considered to properly capture the complex interactions within the energy network, facilitating a decentralized implementation of the devised techniques in real scenarios. Through simulative studies, it will be possible to evaluate the impact of the increasing penetration of flexible demand in the network and quantify the potential economic advantages of distributed coordination approaches in future smart grids.
Task 4.2: Resilient Load/Frequency Set-Point Reconfiguration Problems in Smart-Grids
Load/frequency control (LFC) [26] has been one of the earlier wide-area control applications in the power industry. Its basic objective is the global matching between power generation and demand, which must be maintained as close as possible regardless of load fluctuations. If an imbalance results, e.g. caused by unusual load profiles and/or faults, large frequency deviations may occur with serious impacts on system operations. Power imbalances are caused by unusual load profiles, fault/failure events on generating units and/or breakdowns of the tie-lines connecting the utilities amongst the areas. All above phenomena are hard to be anticipated and, if not timely detected and corrected, may cause massive power shortages or excesses which result in unacceptable frequency deviations exceeding minimum and maximum limits. When occurring, this usually leads to protection relays activation with the corresponding disconnection of many components of the power grid which break up into relatively small disjointed islands. This case study will focus on the reconfiguration of the set-points in multi-area medium-voltage (MV) microgrids, that consist of a combination of Low/Medium voltage feeders connecting several micro-generators (gas turbines, micro-turbines, fuel cells, photovoltaic modules, small wind turbines and storage devices to uncontrollable/controllable loads including plug-in electrical car charging/discharging stations. While the possibility of having a large power system decomposed in a number of interconnected microgrids, each one composed of controllable power generators, storage systems and loads, may be of help in managing the complexity, increasing the system flexibility and reducing the costs, the coordination and supervision a such a large number of smart-devices create new challenges for operating the grid safely and efficiently. These challenges can be partially addressed by exploiting the potentialities of hierarchical and distributed supervisory CG schemes that enable efficient management of this kind of system.
