Distributed Control Design of District Heating Networks

Distributed Control Design of District Heating Networks

Putter, Yvo (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Delft Center for Systems and Control)

Keviczky, T. (mentor)
Werkman, Ewoud (mentor)

Delft University of Technology

2018-10-12

In The Netherlands, the current heat energy system accounts for 44% of the primary energy usage and relies almost entirely on fossil fuels such as natural gas. To meet the Paris Climate Agreement goals, 4th Generation District Heating (4GDH) networks are expected as sustainable heat energy system solution. The concept relies on optimally matching the heat energy supply of sources such as waste heat, combined heat and power (CHP) plants and geothermal energy, with the demand of consumers such as households or greenhouses, whilst using the flexibility of buffers such as aquifer thermal energy storage (ATES) systems.

In this thesis, a cooperative multi-agent system (MAS) hierarchical model predictive control (HMPC) implementation is presented as smart controller for 4GDH networks, and as alternative approach to improving TNO’s HeatMatcher (HM) algorithm with the proposed algorithm of PowerMatcher (PM) that relies on locational marginal pricing (LMP). The model predictive control (MPC) approach is chosen mainly due to the advantage that it optimizes over a prediction horizon or time span, instead of a single time step. This allows to take into account heat energy demand predictions, time-based constraints, and the inherent dynamic characteristics of 4GDH systems such as buffer flexibility and the variable time delay present in the heat energy exchange.

The centralized model predictive control (CMPC) control problem is formulated as a deterministic, MAS, mixed-integer quadratic programming (MIQP) optimization problem and is subsequently distributed based on the Optimal Exchange Problem formulation using the alternating direction method of multipliers (ADMM). Hybrid system modelling theory is applied to model the agents’ subsystems and a simplified heat energy exchange model with constant time delay is assumed. The latter was chosen as decoupled thermal and hydraulic equations proved to be non-linear in the valve positions and mass flow, iterative due to the friction factor and the Reynolds number, and dependent on a variable spatial sampling to accurately track the thermal propagation through the network.

The CMPC and HMPC algorithms are applied on an academic initial design case study to test desired controller behaviour under perfect heat demand prediction, and on a more realistic case study of the WarmCO2 heat grid involving 5 greenhouses with non-perfect heat demand predictions during a summer and winter scenario.

The initial case study confirms that both algorithms perform as desired with the exception of a small shortcoming of the hybrid modelling, and that they are similar in their optimal solutions as expected. The same holds for the WarmCO2 case study. However, it also showcases that the deterministic optimization can become infeasible due to the time delay modelling and non-perfect heat demand predictions, and that therefore a stochastic optimization approach is preferred. Furthermore, good quality local optimal solutions of the NP-hard problem could be found within a relatively short computing time limit, using the heuristic methods of the Gurobi solver. And lastly, the importance of developing a non-cooperative MPC algorithm to accurately represent the individual optimization goals of different stakeholders.

Hierarchical
Model Predictive Control
Mixed Integer Quadratic Programming
District Heating
Optimal Exchange Problem
Alternating Direction Method of Multipliers
Multi-Agent System
MATLAB
Time Delay
Hybrid Systems
Deterministic Optimization
Greenhouses
Cooperative
Heat Energy Exchange Network Model
HeatMatcher
Locational Marginal Pricing
Sustainable Energy
Flexibility
Receding Horizon

http://resolver.tudelft.nl/uuid:1f441413-9ae6-4821-a2d5-929bf0f451bf

The work in this thesis was supported by the MCS department of TNO. Their cooperation is hereby gratefully acknowledged.

Student theses

master thesis

© 2018 Yvo Putter