Multi-Objective Optimisation of District Energy Systems

In the context of finding efficient and environmentally friendly solutions to energy pro- duction and consumption, this work presents a method for the systematic resolution of district energy problems using Multi-Objective Optimisation (MOO) methods. A district energy problem consists in matching the demand in energy of a district with a supply from adapted technologies while minimising environmental and economic objectives. In minimisation, these terms often oppose each other, which means that there is no single correct solution, but rather a multitude of possibilities. Multi-Objective Optimisation (MOO) is therefore necessary in order to find these sets of good solutions in the form of a Pareto frontier. The novelty of this work lies in three major aspects. Firstly, as this work deals with a multi-time approach, a tool is developed allowing for the systematic creation of typical days which reduce the complexity of the MOO. Secondly, post-analysis tools allowing for detailed study of solutions are developed in the form of a global sensitivity analysis. Thirdly a hybrid yearly hour-by-hour simulation tool is developed using MILP optimisa- tion methods. The first part of this work concerns a review of the methods for resolving such a district heating system. Secondly, the development of tools and methods for the implementa- tion of this MOO is undertaken in the form of Evolutionary Multi-Objective Algorithms (EMOO). Tools allowing for a more detailed analysis of specific solutions are also de- veloped. These include tools for the study of specific scenarios, sensitivity analyses and hour-by-hour simulations of the system. This is followed by the development of a database of technologies to be simulated within the context of an EMOO. Conventional energy pro- ducing technologies (boilers, engines, turbines) as well as more environmentally friendly ones (heat pumps, storage systems, solar power) are considered here. Finally, a case study using accurate economical and environmental data obtained from Veolia Environ- ment Research & Innovation (VERI) validates the developed methodology, and provides useful information to engineers working on the project. The data obtained from VERI serves for the Case Study and elaboration of a database it is however confidential.

Decentralized production in urban systems, the vision of the Institute of Energy Sciences of EPFL

François Maréchal

In 1998, the Board of the Swiss Federal Institute of Technology established the challenging vision of the 2000 W society. The goal is to reach, for Switzerland by the year 2050, an energy intensity target of 2000 Wyear/year/cap. Referring to a present intensity of 5000 W year/year/cap, this means an expected factor 4 reduction of the intensity. For the Swiss Federal Institute of Technology, the challenge is to contribute to this target by its Research and Development activities. In the Ecole Polytechnique Fédérale de Lausanne (EPFL), the Institute of Energy Sciences (ISE) of the School of Engineering (STI) is a group of research laboratories that has committed to contribute to this target in the field of efficient conversion and distribution of energy. Decentralised production of electricity in urban areas is one of the multidisciplinary headlight projects that has been selected to reach the 2000 W target. Decentralised production is considered as a way of producing the energy services required by a community in an integrated approach allowing for polygeneration of heating, cooling, refrigeration and electricity services. This new systemic approach requires a new vision where several networks that have to be operated simultaneously. Electricity has to be distributed through microgrids connected with the major grids. In this field, the laboratories from electrical engineering are developing new tools for the design and the operation of such grids as well as new equipments that guarantee the safe operation of the system and its power quality. The design of district heating networks and their integration with the energy services requirements is a complex task since the demands vary with the seasons, the hours of the day and are by nature stochastic due to the behavior of the inhabitants and the weather conditions. Furthermore, the profitability and the conversion efficiency of such systems mainly rely on the appropriate system design, i.e. the size of the piping and the equipments, as well as on its optimal management. Applying techniques such as thermo-economic modeling, process integration , exergy analysis and multi-objective optimisation, the Laboratory for Industrial Energy Systems (LENI) develops computer aided design methods for helping the different stakeholders (energy services companies, technology developers, final users, policy makers) in defining the most appropriate investments both from the side of the infrastructure and the energy conversion equipments and also from the optimal operation management side in order to place the technologies in the energy market context. The Laboratories of the Energy Sciences Institute also work on the development of new equipments for advanced energy conversion, such as high speed turbocompressors for heat pumping, solid oxide fuel cells (SOFC) and cogeneration concepts combining SOFC and gas turbines. Within the Institute, this advanced R&D effort is performed in a multidisciplinary approach combining experimental work with multi-scale multi-physics computer aided design tools like CFD and optimisation.

2005

Sustainable Development Based Methodology for the Optimized Integrated Design and Operation of Energy Conversion Processes and Networks.

Daniel Favrat

A design methodology allowing engineers to consider simultaneously and from the earliest phases of design some of the key factors of sustainable development (pollution, life cycle data) has been developed and successfully demonstrated on two examples of integrated energy systems. The principal idea is to take diverse factors related to thermodynamics, economics and the environment and integrate them in a way that the most optimal syntheses and designs (and operation) can be found. The solution space resulting from such a complete formulation, which can include tens of independant variables, is highly non linear and includes locally continuous but generally non contiguous subspaces. Solution procedures based on specially adapted genetic algorithms, have been implemented and shown to allow the user to tracks the most effective solution paths in a robust way. Pollution penalty factors accounting for both emissions and immission levels have been proposed and applied in dedicated sensitivity analyses. Using a simplified quasi-stationary formulation application examples include the predesign of combined cycle power plant with or without cogeneration and with or without CO2 separation as well as the predesign of district heating systems considering the use of both centralized and/or decentralized heat pumps as well as cogeneration units. Both exergetic and economic optimum solutions are compared. As FN did not finance the entire proposal, additional contributions from FOGA and Alliance for Global Sustainability allowed the completion of this project. Although the present results open exciting prospects and are already being extended in the framework of four different international initiatives, further work is still required. It includes, among others, a further refinement of the link between entropy and/or exergy and pollution, an extension to a broader range of pollutants including those having synergistic effects, a better account for the time dependancy and uncertainties, the coupling with top down approaches including neural net based simplified submodels and parallelisation and an extension of the models of technologies considered to other integrated systems such as direct electrochemical conversion or renewables based devices (new proposal in preparation).

1999

SCCER-FURIES - Report on the role of multi-carrier, multi-services, multi-grids integrated energy conversion systems and their possible role in the Swiss energy 2050 - Deliverable D1.5.3

Luc Girardin, François Maréchal, Paul Michael Stadler

The optimisation of distributed and renewable energy systems in buildings has shown that zero energy systems, using existing technologies, is within reach in the household sector where the thermal and the systems can support each other to increase renewable energy harvesting, co-generation and waste heat recovery. Smart and sustainable systems can be deployed rapidly using solar collectors, heat pumps, energy storages and smart power grid driven by a Smart Energy Management strategy (SEM), based on Model Predictive Control (MPC). Targeting energy autonomous systems will indeed require a step further in the development of the infrastructure. In line with the design of future 100% renewable energy systems and autonomous cities, advanced concepts of multi-service energy systems have been proposed. These concepts of multi-carrier, multi-services and multi-grids systems (electricity, gas, heat distribution and mobility) are built around a "smart thermal grid" connecting buildings, centralised plants and distributed heating and cooling producing units, including individual contributions from the connected buildings and Power to Gas storage (P2G). It has been demonstrated that reasonable investments in advanced heat distribution system could lead to substantial benefits for both the economy and individual consumers, with a break-even time shorter than 6 year.