Limited-Communication Distributed Model Predictive Control for HVAC Systems

This dissertation proposes a Limited-Communication Distributed Model Predictive Control algorithm for networks with constrained discrete-time linear processes as local subsystems. The introduced algorithm has an iterative and cooperative framework with neighbor-to-neighbor communication structure. Convergence to a centralized solution is guaranteed by requiring coupled subsystems with local information to cooperate only. During an iteration, a local controller exchanges its predicted effects with local neighbors (which are treated as measured input disturbances in local dynamics) and receives the neighbor sensitivities for these effects at next iteration. Then the controller minimizes a local cost function that counts for the future effects to neighbors weighted by the received sensitivity information. Distributed observers are employed to estimate local states through local input-output signals. Closed-loop stability is proved for sufficiently long horizons. To reduce the computational loads associated with large horizons, local decisions are parametrized by Laguerre functions. A local agent can also reduce the communication burden by parametrizing the communicated data with Laguerre sequences. So far, convergence and closed-loop stability of the algorithm are proven under the assumptions of accessing all subsystem dynamics and cost functions information by a centralized monitor and sufficient number of iterations per sampling. However, these are not mild assumptions for many applications. To design a local convergence condition or a global condition that requires less information, tools from dissipativity theory are used. Although they are conservative conditions, the algorithm convergence can now be ensured either by requiring a distributed subsystem to show dissipativity in the local information dynamic inputs-outputs with gain less than unity or solving a global dissipative inequality with subsystem dissipativity gains and network topology only. Free variables are added to the local problems with the object of having freedom to design such convergence conditions. However, these new variables will result into a suboptimal algorithm that affects the proposed closed-loop stability. To ensure local MPC stability, therefore, a distributed synthesis, which considers the system interactions, of stabilizing terminal costs is introduced. Finally, to illustrate the aspects of the algorithm, coupled tank process and building HVAC system are used as application examples

A review of thermochemical energy storage systems for power grid support

Power systems in the future are expected to be characterized by an increasing penetration of renewable energy sources systems. To achieve the ambitious goals of the "clean energy transition", energy storage is a key factor, needed in power system design and operation as well as power-to-heat, allowing more flexibility linking the power networks and the heating/cooling demands. Thermochemical systems coupled to power-to-heat are receiving an increasing attention due to their better performance in comparison with sensible and latent heat storage technologies, in particular, in terms of storage time dynamics and energy density. In this work, a comprehensive review of the state of art of theoretical, experimental and numerical studies available in literature on thermochemical thermal energy storage systems and their use in power-to-heat applications is presented with a focus on applications with renewable energy sources. The paper shows that a series of advantages such as additional flexibility, load management, power quality, continuous power supply and a better use of variable renewable energy sources could be crucial elements to increase the commercial profitability of these storage systems. Moreover, specific challenges, i.e., life span and stability of storage material and high cost of power-to-heat/thermochemical systems must be taken in consideration to increase the technology readiness level of this emerging concept of energy systems integration

Enabling technologies for sector coupling: A review on the role of heat pumps and thermal energy storage

In order to reduce greenhouse gas emissions, current and future energy systems need to be made more efficient and sustainable. This change can be accomplished by increasing the penetration of renewable energy sources and using efficient technologies in energy generation systems. One way to improve the operation of the whole energy system is through the generation and end-use sector coupling. Power-to-heat energy conversion and storage technologies, in this view, are enabling technologies that can help in balancing and improving the efficiency of both thermal and electric grids. In the present paper, a comprehensive analysis of the role of heat pumps and thermal energy storage for sector coupling is presented. The main features of the analyzed technologies are presented in the context of smart electric grid, district heating and cooling and multi-carrier energy systems, and recent findings and developments are highlighted. Finally, the technical, social, and economic challenges in the adoption of investigated technologies are discussed.This work was partially funded by the Ministerio de Ciencia, Innovación y Universidades de España (RTI2018-093849-B-C31—MCIU/AEI/FEDER, UE) and by the Ministerio de Ciencia, Innovación y Universidades—Agencia Estatal de Investigación (AEI) (RED2018-102431-T). The authors at the University of Lleida would like to thank the Catalan Government for the quality accreditation given to her research group GREiA (2017 SGR 1537). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia. This work is partially supported by ICREA under the ICREA Academia program

Distributed Control of HVAC&R Networks

Heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems are a major component of worldwide energy consumption, and frequently consist of complex networks of interconnected components. The ubiquitous nature of these systems suggests that improvements in their energy efficiency characteristics can have significant impact on global energy consumption. The complexity of the systems, however, means that decentralized control schemes will not always suffice to balance competing goals of energy efficiency and occupant comfort and safety. This dissertation proposes control solutions for three facets of this problem. The first is a cascaded control architecture for actuators, such as electronic expansion valves, that provides excellent disturbance rejection and setpoint tracking characteristics, as well as partial nonlinearity compensation without a compensation model. The second solution is a hierarchical control architecture for multiple-evaporator vapor compression systems that uses model predictive control (MPC) at both the supervisory and component levels. The controllers leverage the characteristics of MPC to balance energy efficiency with occupant comfort. Since the local controllers are decentralized, the architecture retains a degree of modularity—changing one component does not require changing all controllers. The final contribution is a new distributed optimization algorithm that is rooted in distributed MPC and is especially motivated by HVAC&R systems. This algorithm allows local level optimizers to iterate to a centralized solution. The optimizers have no knowledge of any plant other than the plant they are associated with, and only need to communicate with their immediate neighbors. The efficacy of the algorithm is displayed with two sets of examples. One example is simulation based, wherein a building is modeled in the EnergyPlus software suite. The other is an experimental example. In this example, the algorithm is applied to a multiple evaporator vapor compression system. In both cases the design method is discussed, and the ability of the algorithm to reduce energy consumption when properly applied is demonstrated

Gothenburg District Cooling System - An evaluation of the system performance based on operational data

The global energy demand for providing cooling in buildings is expected to increase the next decades, along with a rapid growth in the number of air conditioners and chillers. A more energy efficient, economical and environmentally viable solution to this increased cooling demand, is district cooling. In Sweden, this technology has been developed since the mid-1990’s and currently delivers about 1 TWh of cooling annually, to 40 cities.Common issues with district cooling are mainly related to the temperatures. First, a low temperature difference between the supply and return water, called low delta-T, persist despite extensive efforts by previous research to provide solutions. Second, low conventional supply and return temperatures remain, potentially as a result of limited knowledge about the temperatures used in the connected buildings. Previous research on the low delta-T has primarily focused on district cooling systems without heat exchangers separating the connected buildings from the distribution system.The purpose of this thesis is therefore to investigate issues with low delta-T in a district cooling system with heat exchanger separation and exploring the potentials of using higher temperatures, by increasing the knowledge about the connected buildings. The investigation is based on analyses of operational data from both primary and secondary sides of the heat exchangers in 37 of the connected buildings in Gothenburg district cooling system. This system is designed for a delta-T of 10 \ub0C and chilled water supply temperatures of 8 \ub0C in the connected buildings.The delta-T in Gothenburg district cooling system varies between 6-8 \ub0C and the results showed that the main causes to this low delta-T are the following: a low temperature approach between the supply streams of the heat exchanger; operation in the saturation zone on the primary side of the heat exchanger; and low return temperatures from cooling coils and fan coil units in connected building chilled water systems. The results also demonstrated that 75% of the recorded chilled water supply temperatures are higher than 8 \ub0C, when the outdoor temperature was 28 \ub0C. If high temperature district cooling was used, more than 50% of the annual district cooling generation would be supplied by free cooling from the river

Supervisory model predictive control of building integrated renewable and low carbon energy systems

To reduce fossil fuel consumption and carbon emission in the building sector, renewable and low carbon energy technologies are integrated in building energy systems to supply all or part of the building energy demand. In this research, an optimal supervisory controller is designed to optimize the operational cost and the CO2 emission of the integrated energy systems. For this purpose, the building energy system is defined and its boundary, components (subsystems), inputs and outputs are identified. Then a mathematical model of the components is obtained. For mathematical modelling of the energy system, a unified modelling method is used. With this method, many different building energy systems can be modelled uniformly. Two approaches are used; multi-period optimization and hybrid model predictive control. In both approaches the optimization problem is deterministic, so that at each time step the energy consumption of the building, and the available renewable energy are perfectly predicted for the prediction horizon. The controller is simulated in three different applications. In the first application the controller is used for a system consisting of a micro-combined heat and power system with an auxiliary boiler and a hot water storage tank. In this application the controller reduces the operational cost and CO2 emission by 7.31 percent and 5.19 percent respectively, with respect to the heat led operation. In the second application the controller is used to control a farm electrification system consisting of PV panels, a diesel generator and a battery bank. In this application the operational cost with respect to the common load following strategy is reduced by 3.8 percent. In the third application the controller is used to control a hybrid off-grid power system consisting of PV panels, a battery bank, an electrolyzer, a hydrogen storage tank and a fuel cell. In this application the controller maximizes the total stored energies in the battery bank and the hydrogen storage tank