Generation and supply optimisation of a power plant and DHC network

  1. Pérez de la Mora, Nicolás
Supervised by:
  1. Víctor Martínez Moll Director

Defence university: Universitat de les Illes Balears

Fecha de defensa: 18 July 2019

  1. Luisa Fernanda Cabeza Fabra Chair
  2. Victoria Laura Barrio Cagigal Secretary
  3. Ulrike Jordan Committee member

Type: Thesis


Introducción This PhD focuses on the operation optimisation of a hybrid power plant which covers the demand of a district heating and cooling network (DHC). This thesis also pursues optimal supply strategies which are a promising and inexpensive way to improve energy efficiency and to reduce expenditure in district network energy supply. Contenido de la investigación To achieve this, this thesis must develop an electricity price for the Spanish market and a thermal demand forecasting tool which works together with an energy simulator. The simulator determines generation strategies by optimizing the production mix that minimises the energy cost and maximises the renewable energy fraction. This leads to an optimization of the power plant's operation and integration of the solar field. Parc Bit is the power plant under study and is in Palma of Majorca, Spain. The power plant can generate heating, cooling and electricity. Thus, the power plant obtains revenue by injecting electricity into the grid and supplying thermal energy to the DHC. To maximise the plant's revenue, it is necessary to develop algorithms that can provide energy generation strategies to meet generation and demand curves. An energy management system is developed to provide the power plant manager with optimal generation strategies. The tool is developed jointly with Politecnico di Torino and can optimise a multi-energy node power plant at different time horizons. This simulator requires information such as thermal and electric demand to fulfil, climatic conditions, power plant configuration, and machine behavior at different generation points. As a result, the tool provides the schedule of the generation machines, primary energy consumption, and total revenue for the time horizon under consideration. A two-cores forecasting tool was developed based on the ARIMAX and neural networks models to obtain the future electricity prices of the Spanish wholesale energy market and the DHC's thermal demand. Those values are fed to the optimisation tool to determine future generation strategies. A solar generation forecaster is developed enabling solar generation to be fed to the optimiser. Therefore, the solar fraction can be maximised by avoiding overlaps with the CHP's thermal generation schedule. Heat losses in the DHC distribution are considered to be part of the thermal load to be fulfilled by the power plant. Therefore, this thesis upgrades the network to acquire reliable information from the energy consumers. The acquired information helps the network operator to optimize supply temperature. Conclusión Moreover, the possibility of modifying the supply temperature allows generators to provide energy more efficiently. Generators provide energy more efficiently when conditions are more relaxed. In addition, these strategies aim to reduce heat losses by modifying the supply temperature within its working boundaries. Through supply temperature adjustment and network's thermal mass harnessing the network can be used as energy storage.