Title: Dynamic optimization of district cooling network - Conversion, Storage et Distribution.
Key words: Cold production, district network, storage, dynamic optimization, optimal control.
The scientific context
Global market of air-conditioning has increased twofold over the past decade and the European market has increased fourfold in three years. This development involves, nowadays, an over consumption in summer, together with an unacceptable greenhouse gas emission. Contrary to individual or local systems, district networks permit, a better integration of all the resources, a reduction of the environmental global impact and a cost sharing. This kind of system needs an important initial investment cost and an adapted management policy.
Many works have been proposed, at the design stage, concerning the optimization of investment cost. The network topology, the sizing (pipe diameter, heat exchanger area…) and operating (temperature, mass flow rate…) parameters are optimized in order to minimize the investment cost while respecting a set of constraints (needs of consumers, temperature levels…). These works have led to an optimum that corresponds to the nominal working condition of the network in steady state. This approach has already been implemented in the LaTEP with the originality, amongst others, to permit different temperature levels for the different users.
Some authors propose to take into account the variations/disturbances to which the network is subjected: variations of consumer needs, ambient temperature… The approach here is multi-period optimization. It permits to obtain the optimal compromise of the model parameters for different constant values by period. Gang et al., 2016 propose a state of the art and a review of recent works.
The objectives
Our final aim is to propose a methodology for the optimal management of the network by really taking into account the dynamic of the global system (conversion, storage and distribution), in the case of cooling network.
The system data’s are the following:
- The structure of the network and the sizing parameters (diameter, heat exchanger area…). These data result from an upstream design study (Mertz T., Thesis UPPA, 2016).
- The variability of load (consumption). These data come from an users behavioural study.
- The external conditions (seasons, diurnal cycle…)
The aim is to determine the optimal temporal profiles of the operating parameters of the network: power of each sources, mass flow rate, temperatures and storage levels…
The approach retained here is optimal control type that permits to maintain all the system the nearest as possible of the optimal trajectory.
Main tasks:
T1: Review
The aim of this task is to write the state of the art about the modelling of district cooling networks. This first task will also include an analysis of the dynamic optimization methodologies.
T2: System modelling
The heart of the optimization problem includes the modelisation of the conversion systems (cooling machines), the storage and the network. This next phase will take advantage of the successful experiences of the LaTEP. Two times scale will be considered: variation over a day and over a year.
T3: optimization problem formulation
This task will permit to formulate the optimization problem: definition of the objective function, of the variables and of the constraints.
T4: Resolution of the optimization problem
The optimization problem formulated, this task aims to choose the better strategy for the solution strategy, the method (algorithm) and the environment. This approach will be validated on a set of study cases.
Research collaborations
The LaTEP has already developed some collaboration with the UNIANDES (Bogota, Colombia). Recently, this collaboration was about the dynamic optimization (optimal control) of complex systems as reactive distillation (Ramos, 2014 ; Ramos, 2013). This thesis may be the opportunity to reinforce this cooperation assuming a validation of theoretical development with experimental results of the UNIANDES for the conversion part.
Bibliography
District Cooling Systems : Technology Integration, System Optimization, Challenges and Opportunities for applications, Gang W., Wang S., Xiao F. and Gao D., Renewable and Sustainable Energy Reviews, Vol. 53, pp. 253-264, (2016)
Simultaneous Optimal Design and Control of an Extractive Distillation System for the Production of Fuel Grade Ethanol using MPCC, Ramos M. A., Gómez J. M. and Reneaume J. M., Industrial & Engineering Chemistry Research, Vol. 53, No 2, pp. 752-764, (2014).
Optimal Control of the Extractive Distillation for the Production of Fuel Grade Ethanol, Ramos M. A., García-Herrero P., Gómez J. M. and Reneaume J. M., Industrial & Engineering Chemistry Research, Vol. 52, No 25, pp. 8471-8487, (2013).
Skills Required
The candidate should have an Energetic and/or Process Engineering background. Excellent skills in thermodynamic, heat transfer, fluid mechanics, programming and modelling/optimization (numerical optimization; mathematical programming) are required.
Good level of English is also required.
Application form
Applicants must submit the following attachments by mail, preferably in pdf format:
RTP Slot Gacor memang menjadi pilihan menarik bagi banyak pemain karena peluang menangnya yang lebih besar. Dengan persentase RTP Slot Tertinggi, pemain bisa merasa lebih percaya diri saat bermain dan berharap pada peluang yang lebih baik. Saat bermain di RTP Slot Online, sensasi adrenalin saat melihat peluang kemenangan yang tinggi menjadi pengalaman tersendiri. Slot RTP Tertinggi menawarkan stabilitas dan frekuensi kemenangan yang sangat dinantikan banyak pemain.