Kirsten Mølgaard Nielsen

Using heat pump energy storages in the power grid

The extensive growth of installed wind energy plants lead to increasing balancing problems in the power grid due to the nature of wind fields and diurnal variations in consumption. One way to overcome these problems is to move consumption to times where wind power otherwise cause overproduction and large fluctuations in prices. The paper presents a method which takes advantage of heat capacity in single-family houses using heat pumps which are anticipated to be installed in large numbers in Denmark in next decade. This type of heating gives a large time constant and it is shown possible to move consumption without compromising the comfort of house residents. In the paper an optimization exploiting forecasts of weather and energy prices combined with prediction models of house dynamics is presented. The results show that with the presented method it will be possible to move a substantial amount of energy from one time to another.

Smart grid dispatch strategy for ON/OFF demand-side devices

We consider an aggregator managing a portfolio of runtime and downtime constrained ON/OFF demand-side devices. The devices are able to shift consumption in time within certain energy limitations. We show how the aggregator can manage the portfolio of devices to collectively provide upward and downward regulation. Two control strategies are presented enabling the portfolio to provide regulating power while respecting the runtime, downtime, and energy constraints of the devices. The first strategy is a predictive controller requiring complete device information; this controller is able to utilize the full flexibility of the portfolio but can only handle a small number of devices. The second strategy is an agile controller requiring less device information; this controller is able to handle a large number of devices but not able to utilize the full flexibility of the portfolio.

Observer based model identification of heat pumps in a smart grid

The extensive growth of installed wind energy plants in Denmark leads to increasing balancing problems in the power grid due to the nature of wind fields and variations in consumption. One way to overcome these problems is to move consumption to times where wind power otherwise cause overproduction. A part of a solution can be to take advantage of floor heat capacity in single-family houses using heat pumps. This large heat capacity makes it possible to move consumption without compromising the comfort of house residents. In a Danish research project a virtual power plant using centralized control of a large number of houses with heat pumps is established. In order to make the control algorithm a vital part is a dynamic model of each house. The model predicts the house indoor temperature when heat pump power and outdoor temperature is known. The model must be able to describe a large variety of heat pumps and houses. In the paper a house model and a method to identify the model is presented. The Kalman observer models are optimized using measurements from real houses.

Heat pumps in private residences used for grid balancing by demand desponse methods

Increased production of renewable energy as wind energy will give a fluctuating production which requires flexible energy storages. Heat capacity in single-family houses with electrical heating using heat pumps represents a storage which can be used to balance the electricity supply. It is assumed that electricity prices will reflect surplus or deficiency in production. A performance function describing cost of electricity combined hour by hour with user comfort is formulated. Minimization of this performance will balance the grid by pushing consumption towards hour with surplus production capacity. The minimization results in a power consumption schedule and a temperature schedule for each house. A number of control structures are described aiming to obtain this optimum by communicating references to either house temperature or heat pump power or by offering the consumer an hour by hour price. By simulation the schemes are compared by there ability to time shift consumption and to avoid consumer discomfort. Additionally the necessary information exchange for the schemes is discussed. Comparisons indicate that it is possible to use heat pump heated private houses to move power consumption within a time interval without loss of consumer comfort. However the full potential of the storage capacity can only be achieved in the schemes which combine feedback with an optimizing solution.

Control of an autonomous vehicle for registration of weed and crop in precision agriculture

The paper describes the development of an autonomous electrical vehicle to be used for weed mapping in precision agriculture with special focus on the conceptual framework of the control system. The lowest layer of the control system is the propulsion and steering control, the second layer coordinates the movements of the wheel units, the third layer is path execution and perception and the upper layer performs planning and reasoning. The control system is implemented on an autonomous vehicle. The vehicle has been tested for path following and position accuracy. Based on the results a new vehicle is under construction.

Electricity market optimization of heat pump portfolio

We consider a portfolio of domestic heat pumps controlled by an aggregator. The aggregator is able to adjust the consumption of the heat pumps without affecting the comfort in the houses and uses this ability to shift the main consumption to hours with low electricity prices. Further, the aggregator is able to place upward and downward regulating bids in the regulating power market based on the consumption flexibility. A simulation is carried out based on data from a Danish domestic heat pump project, historical spot prices, regulating power prices, and spot price predictions. The simulations show that electricity price reductions of 18-20% can be achieved compared to the heat pumps currently in operation.

Absorption cycle heat pump model for control design

Heat pumps have recently received increasing interest due to green energy initiatives and increasing energy prices. In this paper, a nonlinear dynamic model of a single-effect LiBr-water absorption cycle heat pump is derived for simulation and control design purposes. The model is based on an actual heat pump located at a larger district heating plant. The model is implemented in Modelica and is based on energy and mass balances, together with thermodynamic property functions for LiBr and water and staggered grid representations for heat exchangers. Model parameters have been fitted to operational data and different scenarios are simulated to investigate the operational stability of the heat pump. Finally, this paper provides suggestions and examples of derivation of lower order linear models for control design.

Model predictive control of a wave energy converter

In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPCs are designed for each sea state using a model assuming a linear loss torque. The mean power results from two controllers are compared using both loss models. Simulation results show that MPC can outperform a reactive controller if a good model of the conversion losses is available.

Analysis of decentralized control for absorption cycle heat pumps

This paper investigates decentralized control structures for absorption cycle heat pumps and a dynamic nonlinear model of a single-effect LiBr-water absorption system is used as case study. The model has four controllable inputs, which can be used to stabilize the operation of the heat pump under different load conditions. Different feasible input-output pairings are analyzed by computation of relative gain array matrices and scaled condition numbers, which indicate the best pairing choice and the potential of each input-output set. Further, it is possible to minimize the effect of cross couplings and improve stability with the right pairing of input and output. Simulation of selected candidate input-output pairings demonstrate that decentralized control can provide stable operation of the heat pump.

Aggregated control of domestic heat pumps

A challenge in Denmark in the near future is to balance the electrical grid due to a large increase in the renewable energy production mainly from wind turbines. In this work an aggregated control system using heat pumps in single family houses to help balancing the grid is investigated. The control system is able to adjust the consumptions of the heat pumps without affecting comfort in the houses and uses this ability to shift the total consumption to hours with high wind energy production.