An integrated framework for modelling and control of eP2P interactions based on model predictive control

Zusammenfassung

The energy paradigm is undergoing substantial changes in recent years. In terms of production, it is observable how distributed generation, with an ever-increasing contribution from renewable sources, is displacing large concentrated generation plants. But the fundamental change is not so much about energy supply as about diluting the historical roles of producers and consumers to give way to the concept of prosumers. That is, instead of just being energy consumers, households and industries also become producers. In principle, the purpose of this production, which is inherently distributed, is self-consumption. However, when there is a surplus of production, prosumers can choose between storing the excess, if they have an energy storage system, or sell the unused fraction of energy. An obvious type of prosumers are those industries that have renewable generation facilities and which, as a consequence of their production process, generate by-products that can be used for cogeneration. In this case an obvious problem for the company is to select at all times the power sources that minimize the cost of production, which is known as Optimal Power Dispatch (OPD). If, in addition, the energy consumption time profile of the manufacturing process (per unit of raw material introduced) is known, it is also possible to make an optimal production schedule to minimize energy cost, which is called Optimal Power Scheduling (OPS). Chapter 3 presents an Economic Model Predictive Controller (EMPC) that simultaneously performs OPD and OPS using an olive mill as an example. The emergence of the role of energy prosumers makes it necessary to extend, improve or replace the traditional mechanisms of energy exchange. This thesis includes novel approaches for modelling the behaviour of prosumers. It also proposes new structures to facilitate energy trading, always from the perspective of the peerification of the energy paradigm. Thus, another line of research studies the establishment of peer-to-peer (P2P) markets for the exchange of energy between heterogeneous prosumers (homes, vehicles, intelligent buildings, etc.). The efficiency of markets based on both discrete double auctions (DDAs) and continuous double auctions (CDAs) is compared. An Energy Management System (EMS) is also introduced including market agent software that allows the necessary tasks for participation in the auctions to be carried out automatically (determination of private valuation, role selection and price adaptation). Chapter 4, Chapter 5 and Chapter 6 present some examples of such exchange markets stablished between different types of prosumers: i) energy market for electric vehicles that coincide parked in a large workplace, ii) power market for households within the same neighbourhood and iii) integrated energy and power markets for heterogeneous energy entities. The evolution of aforementioned mechanisms and the appearance of new market models must be accompanied by the development of control techniques that optimise and automate all the processes related to energy saving and trading, by a group of increasingly heterogeneous prosumers. This thesis deals with how different variants of predictive controllers can contribute to this last aspect. For industries with cogeneration capacity, the EMPC contributes to the optimal scheduling of production to maximise the return from energy reuse, either through self-consumption or through the trading of surpluses. The use of stochastic predictive control is proposed in order to maximise the expected return on the participation of prosumers, whatever their type, in continuous markets where the price of energy may undergo stochastic variations.