Fatemeh Tahersima

Thermal analysis of an HVAC system with TRV controlled hydronic radiator

A control oriented model for an HVAC system is derived in this paper. The HVAC system consists of a room and a hydronic radiator with a temperature regulating valve (TRV) which has a step motor to adjust the valve opening. The heating system and the room are simulated as a unit entity for thermal analysis and controller design. A discrete-element model with interconnected small scaled elements is proposed for the radiator. This models the radiator more precisely than that of a lumped model in terms of transfer delay and radiator gain. This precise modeling gives us an intuition into a regular unwanted phenomenon which occurs in low demand situations. When flow is very low in radiator and the supply water temperature and the pressure drop across the valve is constant, oscillations in room temperature frequently occur. The model derived in this paper demonstrates that the oscillations are in part due to the large gain of the radiator in low demand conditions compared to the high demand situations. The simulation model of radiator is optimized in terms of approximating the small signal gain of radiator in all operating points accurately. The controller designed for high demand weather conditions is applied to the opposite conditions to illustrate the oscillatory condition more apparently. Suggestions to alleviate this situation are proposed.

Economic COP optimization of a heat pump with hierarchical model predictive control

A low-temperature heating system is studied in this paper. It consists of hydronic under-floor heating pipes and an air/ground source heat pump. The heat pump in such a setup is conventionally controlled only by feed-forwarding the ambient temperature. Having shown >;10% cut-down on electricity bills by involving feedback control in a previous study, this paper has continued the same line of argument and has investigated effects of a priori knowledge on weather forecast and electricity price profile to alleviate the total electricity cost subject to constraints on residents thermal comfort. A two level hierarchical control structure is chosen for this purpose. While local PI controllers at the bottom level maintain individual temperature set-points of the rooms, a model predictive controller at the top level minimizes water supply temperature, and hence maximizes the heat pumps coefficient of performance. At the same time, it determines the actual temperature set-points of the rooms by deviating from the user-defined set-points within a thermal tolerance zone. Simulations results confirm significant cut-down on electricity bills without sacrificing resident thermal comfort. The proposed control strategy is a leap forward towards balanced load control in Smart Grids where individual heat pumps in detached houses contribute to preserve load balance through intelligent electricity pricing policies.

Optimal Power Consumption in a Central Heating System with Geothermal Heat Pump

Abstract A ground source heat pump connected to a domestic hydronic heating network is studied to be driven with the minimum electric power. The hypothesis is to decrease the forward temperature to the extent that one of the hydronic heaters work at full capacity. A less forward temperature would result in a dramatic temperature drop in the room with saturated actuator. The optimization hypothesis is inspired by the fact that, the consumed electric power by the heat pump has a strong positive correlation with the generated forward temperature. A model predictive control scheme is proposed in the current study to achieve the optimal forward temperature. At the lower hierarchy level, local PI controllers seek the corresponding room temperature setpoint. Simulation results for a multi-room house case study show considerable energy savings compared to the heat pumps traditional control scheme.

An intuitive definition of demand flexibility in direct load control

Two control approaches: direct and indirect control of demand side energy management in a smart grid are studied. Indirect control of energy demands is based on economic incentives. In this approach, consumers will shift their energy consumption with the benefit of a cut down in the electricity bill and in the cost of being flexible in terms of accepting a wider comfort zone. The other approach is to directly command a power signal to end-user loads provided that the electricity provider company is already aware of the consumers flexibility degree. We have framed a measure of the flexibility in terms of the amount of energy that can be shifted without sacrificing comfort. A specific case study i.e. a residential building equipped with an electric floor heating system is used for demonstration of simulation results. Finally, we proposed a control method to serve both direct and indirect load shifting schemes. Simulation results show a sub-optimal result with the combination approach compared to the optimal solution with the indirect approach.

Eliminating oscillations in TRV-controlled hydronic radiators

Thermostatic Radiator Valves (TRV) have proved their significant contribution in energy savings for several years. However, at low heat demands, an unstable oscillatory behavior is usually observed and well known for these devices. This instability is due to the nonlinear dynamics of the radiator itself which result in a large time constant and high gain for radiator at low flows. A remedy to this problem is to make the controller of TRVs adaptable with the operating point instead of widely used fixed PI controllers. To this end, we have derived a linear parameter varying model of radiator, formulated based on the operating flow rate, room temperature and the radiator specifications. In order to derive such formulation, the partial differential equation of the radiator heat transfer dynamics is solved analytically. Using the model, a gain schedule controller among various possible control strategies is designed for the TRV. It is shown via simulations that the designed controller based on the proposed LPV model performs excellent and stable in the whole operating conditions.

Economic energy distribution and consumption in a microgrid Part1: Cell level controller

We have investigated energy management of a small scale electrical microgrid comprised of local renewable generation, consumption and storage units. The microgrid has the possibility of connection to the electricity grid as well to compensate for energy deficit. The objective is to fulfill microgrids energy demands from the local electricity producers as much as possible. The other objective is to manage the consumption such that consumption costs are minimum for all households. To fulfill the objectives, as the first step of designing a hierarchical controller, we focused on designing an energy and cost minimizing controller for one building. To this aim, a model predictive controller is formulated to schedule the buildings energy consumption using potential load flexibility. Simulation results show the economically optimal energy consumption of one building based on the defined load types, a user-specified comfort criterion and the grid electricity price.

Stability performance dilemma in hydronic radiators with TRV

Thermostatic Radiator Valves (TRV) have proved their significant contribution in energy savings for several years. However, at low heat demands, an unstable oscillatory behavior is usually observed and well known for these devices. It happens due to the nonlinear dynamics of the radiator itself which results in a high gain and a large time constant for the radiator at low flows. If the TRV is tuned in order to dampen the oscillations at low heat loads, it will suffer from poor performance and lack of comfort, i.e. late settling, when full heating capacity is needed. Based on the newly designed TRVs, which are capable of accurate flow control, this paper investigates achievable control enhancements by incorporating a gain schedulling control scheme applied to TRVs. A suitable linear parameter varying model is derived for the radiator which governs the gain scheduler. The results are verified by computer simulations.

Economic energy distribution and consumption in a microgrid Part 2: Macrocell level controller

Abstract Energy management of a small scale electrical microgrid is investigated. The microgrid comprises residential houses with local renewable generation, consumption and storage units. The microgrid has the possibility of connection to the electricity grid as well to compensate energy deficit of local power producers. The final objective is to fulfil the microgrids energy demands mainly from the local electricity producers. The other objective is to manage power consumption such that the consumption cost is minimum for individual households. In this study, a hierarchical controller composed of three levels is proposed. Each layer from bottom to top focus on individual energy consuming units, individual buildings, and the microgrid respectively. At the middle layer, a model predictive controller is formulated to schedule the buildings energy consumption using potential load flexibilities. The top level energy manager is designed to distribute available power resources among the houses or sell the remainder to the electricity grid. Simulation results show the economically optimal energy consumption in the buildings and economically efficient power trading between the houses.