Investment Planning Methodology for Complex Urban Energy Systems Applied to a Hospital Site

Industrial process integration based on mixed integer linear programming has been used for decades to design and improve industrial processes. The technique has later been extended to solve multi-period and multi-scale problems for the design of urban energy systems. Assistance is indeed required for the elaboration of coordinated investment scheduling strategies to promote renewable and efficient urban energy infrastructure shaping the future energy context for the next decades. Major energy consumers, such as hospital complexes, airports, or educational campuses can act as a driving force for the development of renewable energy cities by attracting profitable large-scale energy networks and infrastructure. The proposed methodology generates optimal alternatives for the replacement, in a long-term perspective, of the various energy supply units and systems considering the evolution of the energy demand and the availability of the energy resources. Energy integration techniques are coupled to a parametric multi-objective optimization routine to select and size the energy equipment with both financial profitability and CO2 emission reduction as objectives. The originality of the developed method lies in the integration of a multi-period mixed integer linear programming formulation to generate long-term investment planning scenarios. The method has been demonstrated on a complex of eight hospitals totaling 466,000 m2 and an operating budget of 1.85 billion USD per year. The energy integration of new centralized and decentralized equipment has been evaluated on a monthly basis over four periods until the year 2035. The results show that among the four scenarios identified, the most optimistic alternative allows to decrease the final energy consumption of about 36%, cut the CO2 emissions by a half, multiply the renewable energy share by a factor 3.5 while reducing the annual total cost by 24%. This scenario considers mainly the integration of a very low temperature district heating with decentralized heat pumps to satisfy the heat requirements below 75°C, as well as heat recovery systems and the refurbishment of about 33% of the building stock.

Methodology and Thermo-Economic Optimization for Integration of Industrial Heat Pumps

Helen Carla Becker

This thesis presents a systematic methodology, based on pinch analysis and process integration techniques, to integrate heat pumps into industrial processes. The main goals are to decrease the energy consumption and the corresponding operating costs, and therefore to increase the energy efficiency of an industrial process. The objective of this thesis is to identify heat pump opportunities, and to optimize simultaneously the energy conversion and utility system of a process. The process and utility integration is realized, using mixed integer linear programming (MILP). In order to find systematically the optimal operating conditions of heat pumps, an optimization framework combining linear and non-linear optimization methods is presented. Technologically feasible heat pumps are collected in a data base and proposed to the process. A multi-objective optimization, combined with process integration methods, gives the possibility to systematically identify optimal heat pump sizing and positioning solutions. Pinch analysis is a promising tool, however several limits have been discovered, and the basic methodology has been extended to obtain more realistic solutions. The first extension gives the possibility to integrate heat exchange restrictions due to industrial constraints (e.g. safety reasons, or long distances). A methodology, based on the decomposition into sub-systems, is developed to include heat exchange restrictions. The penalty of these heat exchange restrictions can be decreased by integrating intermediate heat recovery loops, which transfer heat indirectly between two sub-systems. A further developed extension, which enables to define subsystems at different levels, makes the approach very flexible and useful for many different application cases. The second extension is realized to integrate multi-period and multi-time slice problems. The main focus is the integration of storage units, to enable the heat recovery between different time slices. The interest in heat pumps can be increased when integrating storage units, because their working hours and profitability increase. The methodology and its extensions are tested and validated with several real industrial case studies. It is shown that there is a great potential for industrial heat pumps.

EPFL2012

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

Multi-objective design and optimization of district energy systems including polygeneration energy conversion technologies

Céline Weber

In the present context of finding ways to decrease CO2 emissions linked with human activity, district energy systems including polygeneration energy conversion technologies are likely to play a major role. District energy systems meet the heating, hot water, cooling and electricity requirements of a district. Because they meet several types of energy requirements, and for more than one single building, district energy systems represent good opportunities to implement polygeneration energy conversion technologies. Polygeneration energy conversion technologies indeed provide different energy services simultaneously, helping to decrease the CO2 intensity compared to energy conversion technologies that meet only one energy service. Moreover, when providing energy to a whole district, polygeneration energy conversion technologies can take advantage of the various load profiles of the buildings by compensating the fluctuations and having therefore a smoother operation. A district energy system comprises essentially two parts: the plant with the polygeneration energy conversion technologies, and the distribution networks (heating and cooling). When designing the energy system for a district, one has therefore to define which type of polygeneration energy conversion technologies are best suited for the district, as well as which building are worse connecting to the system and which buildings shouldn't be connected (for instance if they are located too far away from the other buildings or if they have too small requirements to justify a connection from the plant). Moreover the operation strategy needs to be defined. In the present thesis, a method is developed that helps designing and optimizing district energy systems, from the structuring of the information available for the district (energy consumption profiles, location of the buildings, available energy sources, possible layouts for the pipes,...), over the thermo-economic modelling of the energy conversion technologies, the design of the network and the simulation of its operation strategy, and finally the evaluation of the results in terms of CO2 emissions and costs. The design and optimization of the district energy system is a multi-objective Mixed Integer Non Linear Programming problem. To solve this problem, a decomposition strategy including a master and a slave problem was developed. The master optimization problem takes care of the energy conversion technologies, whereas the slave optimization problem optimizes the network part. The two sub-problems are solved iteratively and result in the definition of a Pareto optimal curve that gives the trade-offs between the emissions and the costs for various configurations satisfying the requirements of the district. A configuration is characterized by given types and sizes of energy conversion technologies, their location in the district, the network layout, as well as the operation strategy of the technologies. Due to the time dependent energy consumption profiles and the geographical location of the buildings and plant, the method developed combines two well known types of problems, namely the multi-period optimization problems and the network problems. The method developed allows to take into account various constraints such as limited availability of energy sources, forbidden connections between buildings (for instance if a large river separates these two buildings), or else space limitations in underground technical channels. The capabilities of the method are demonstrated by means of a test case, as well as a real case in the Canton of Geneva. The results show the importance of considering all the energy services together (and not separately). Energy systems including a gas engine or a gas turbine combined cycle, together with heat pumps, indeed help decreasing both the emissions and the costs compared to the actual configurations. In the Geneva case study for instance, emissions can be decreased by up to 45%, with a simultaneous costs reduction of 24%. However, the method only deals with water networks, while in some cases space limitations and safety issues make the use of water impossible. A new type of district energy system based on CO2 as energy transfer medium (instead of water), is therefore developed in order to take such issues into account. This new system, that led to the submission of a patent, meets all the different types of energy requirements with only two pipes (instead of three or four like in conventional water based system), and uses the latent heat of CO2 as driving force, instead of the specific heat.

EPFL2008