The electric energy system has undergone major changes in recent years. Gradually, large scale fossil or nuclear power plants are being replaced by distributed energy resources (DER) often based on renewable energies like wind power and solar energy. In contrast to large scale thermal power plants, DER are mostly connected to the low and medium voltage grids. Up to now, ancillary services like frequency or voltage control, which are essential for a stable operation of the electric power system, are predominantly provided by the remaining large scale thermal power plants (Braun 2009). To reduce carbon dioxide emissions large coal-fired power plants are to be replaced by further expansion of DER. This makes it increasingly important that DER not only contribute to active power provision, but are also involved in the provision of ancillary services (Deutsche Energie-Agentur GmbH 2012).
DER such as photovoltaic plants or wind turbines are normally connected to the grid via power-electronic converters. In the future converter dominated grid DER must take over ancillary services so far merely provided by large scale power plants (e.g. primary reserve for frequency control or reactive power provision for voltage regulation in the transmission grid). At the same time, DER meet new challenges, which arise from their distributed nature, their connection to the low- and medium voltage grid and the fluctuating and to some extent uncertain supply of wind power and solar energy. Among these challenges are voltage deviations and voltage band violations in the distribution grid, congestion of lines and transformers and a changing dynamic behavior of the power system.
Power-electronic converters are technically capable of providing arbitrary reactive power along with active power as long as current and voltage limitations are met. In Germany, reactive power control capability for low- and medium voltage connected DER is defined in the technical guidelines VDE AR 4105 (low voltage) and the BDEW Medium Voltage Guideline (VDE, FNN 2011; BDEW Bundesverband der Energie- und Wasserwirtschaft e.V 2008). The guidelines define local control characteristics such as cosφ(P) or Q(U) for reactive power supply of converter-connected DER. At the same time, grid operators incorporate new operating equipment to solve voltage balancing problems. This is changing the formerly largely passive distribution grid to an active system with a great number of actuating variables, which have to be coordinated to optimize overall system operation and to avoid controller conflicts (i.e. adverse control actions directed at one or more units based on different control targets and stakeholders) leading to inefficiencies or even instabilities of the system.
The DFG-project “Reliable Operation of Converter-Dominated ICT-Reliant Energy Systems”, in the context of which this work is conducted, aims to develop and evaluate a decentralized agent-based control and information exchange structure for grid operation with the help of DER and their coordination with top-level control centers. The main idea is to combine local converter-based control with multi-agent based optimization to form a hybrid control system as depicted in (Fig. 1). The converter-based control guarantees real-time behavior and relaxes time constraints for the overlying multi-agent system, which in turn ensures long-term optimization of system operation and controller conflict mitigation by dynamically optimizing the configuration of the local controllers.
For optimization a formal description of the system boundaries is needed. This is typically done by providing constraints next to optimization objectives. For dynamic optimization of controller configurations this approach is not suitable, as it would require the reformulation of the optimization problem each time the system changes, for example when new DER are connected to the system or when the flexibility of an energy unit with regard to one service is temporarily reduced by other higher prioritized services.
A promising approach to deal with dynamic optimization problems is to use a machine learning surrogate model to describe the flexibilities of the underlying systems. A surrogate model is a black-box model that abstracts from the technical model of a complex system and approximates the observable behavior (without the internal causal relations) based on a limited set of sampled data. From the surrogate model a so-called decoder can be derived, which maps the unrestricted search space to the solution space and thus allows for contraint-free optimization with standard optimization heuristics such as evolutionary optimization methods (Bremer 2015).
In the PhD-project presented in this abstract, this approach shall be applied and evaluated for dynamic agent-based optimization of local controller configurations, particularly with regard to voltage regulation in active distribution grids. As mentioned before, the decoder approach does not require the reformulation of the optimization problem when parameters of the underlying system change and is thus more flexible and easier to automate. But still surrogate model and decoder have to be learned resp. derived from scratch in case of system changes, which is computationally expensive and time consuming. Therefore, one main research goal in this PhD-project is to develop a method, which allows for dynamic adoption of surrogate model and decoder to changes in scenario settings.
To allow for the optimization of higher grid levels based on lower level flexibilities, a description of the aggregated flexibilities resp. constraints of downstream entities is required. Therefore, another important research goal is to develop fast training set sampling techniques for ensembles (groups) of DER avoiding the distribution folding problem (the distribution of the sum of independent random variables results from the convolution of the individual random variables) when combining independently sampled training sets from different downstream entities for training aggregated decoders in upstream agents.