Linear programming control of a group of heat pumps

For a new district in the Dutch city Meppel, a hybrid energy concept is developed based on bio-gas co-generation. The generated electricity is used to power domestic heat pumps which supply thermal energy for domestic hot water and space heating demand of households. In this paper, we investigate direct control of the heat pumps by the utility and how the large-scale optimization problem that is created can be reduced significantly. Two different linear programming control methods (global MILP and time scale MILP) are presented. The latter solves large-scale optimization problems in considerably less computational time. For simulation purposes, data of household thermal demand is obtained from prediction models developed for this research. The control methods are compared with a reference control method resembling PI on/off control of each heat pump. The reference control results in a dynamic electricity consumption with many peak loads on the network, which indicates a high level of simultaneous running heat pumps at those times. Both methods of mix integer linear programming (MILP) control of the heat pumps lead to a much improved, almost flat electricity consumption profile. Both optimization control methods are equally able to minimize the maximum peak consumption of electric power by the heat pumps, but the time scale MILP method requires much less computational effort. Future work is dedicated on further development of optimized control of the heat pumps and the central CHP

Minimizing costs is easier than minimizing peaks when supplying the heat demand of a group of houses

This paper studies planning problems for a group of heating systems which supply the hot water demand for domestic use in houses. These systems (e.g. gas or electric boilers, heat pumps or microCHPs) use an external energy source to heat up water and store this hot water for supplying the domestic demands. The latter allows to some extent a decoupling of the heat production from the heat demand. We focus on the situation where each heating system has its own demand and buffer and the supply of the heating systems is coming from a common source. In practice, the common source may lead to a coupling of the planning for the group of heating systems. On the one hand, the external supply of the energy for heating up the water may have to be bought by an energy supplier on e.g. a day-ahead market. As the price of energy varies over time on such markets, this supplier is interested in a planning which minimizes the total cost to supply the heating systems with energy. On the other hand, the bottleneck to supply the energy also may be the capacity of the distribution system (e.g. the electricity networks or the gas network). As this has to be dimensioned for the maximal consumption, in this case it is important to minimize the maximal peak. The two mentioned coupling constraints for supplying the energy for producing the heat, lead to two different objectives for the planning of the group of heating systems: minimizing cost and minimizing the maximal peak. In this paper, we study the algorithmic complexity of the two resulting planning problems. For minimizing costs, a classical dynamic programming approach is given which solves the problem in polynomial time. On the other hand, we prove that minimizing the maximal peak is NP-hard and discuss why this problem is hard. Based on this, we show that this problem becomes polynomial if all heating systems have the same consumption of energy when turned on. Finally, we present a Fix Parameter Tractable (FPT) algorithm for minimizing the maximal peak which is linear in the number of time intervals

VOLTAGE SUPPORT IN DISTRIBUTION GRIDS USING HEAT PUMPS

ABSTRACT This paper investigates the potential of heat pumps to increase the self-consumption of households and t

Review of control strategies for improving the energy flexibility provided by heat pump systems in buildings

Peer ReviewedPostprint (author's final draft

Heat pump controls to exploit the energy flexibility of building thermal loads

Smart controls for heat pumps are required to harness the full energy flexibility potential of building thermal loads. A literature review revealed that most strategies used for this purpose can be classified in two categories: simpler rule-based control (RBC), and model predictive control (MPC), a more complex strategy based on optimization and requiring a prior model of the systems. Both RBC and MPC can use external penalty signals to prompt their actions. The price of electricity is most often used for this purpose, leading to strategies of cost reduction. As an alternative penalty signal, a novel marginal CO2 emissions signals was also conceived. In this thesis, both an RBC and an MPC controllers were developed as supervisory controls for an air-to-water heat pump supplying the heating and cooling needs of a residential building type from the Mediterranean area of Spain. The RBC strategy modulates the temperature set-points, while the MPC strategy minimizes the overall summed penalties (costs or emissions) due to the heat pump use, while balancing with comfort constraints and a proper operation of the systems. The MPC controller in particular required the development of a simplified model of the building envelope and of the heat pump performance, both adjusted differently for heating or cooling. The MPC included several novelties, such as the mixed-integer formulation, the heat pump simplified model based on experimental data and the consideration of its computational delay. The developed controllers were then tested, firstly in an experimental “hardware-in-the-loop” setup, with a real heat pump installed in the laboratory facilities, and connected to thermal benches that emulated the loads from a building model. Implementing the control strategies on a real heat pump enabled to highlight some practical challenges such as model mismatch in the MPC, communication issues, interfacing and control conflicts with the heat pump local controller. Secondly, a simulation-only framework was developed to test other configurations of the controllers, with TRNSYS as the main dynamic building simulation tool, coupled with MATLAB for the MPC controller. In that case, the real heat pump was replaced by a detailed model which was specially developed for this purpose. It is based on static tests performed in the laboratory, and therefore reproduces the dynamic behavior of the heat pump with high fidelity. The results from experimental and simulation studies revealed the ability of both types of controllers to shift the building loads towards periods of cheaper or less CO2-emitting electricity, these two objectives being in fact contradictory. In the cases where the reference control presented a large margin for improvements, the RBC and MPC controllers performed equally and provided important savings: around 15% emissions savings in heating mode, and 30% cost savings in cooling mode. In the cases where the reference control already performed close to optimally, the RBC controller failed to provide improvements, while the MPC benefitted from its stronger optimization and prediction features, reaching 5% cost savings in heating mode and 10% emissions savings in cooling mode. The research carried out in this thesis covered many aspects of energy flexibility in buildings: creation of input penalty signals, graphical representation of flexibility, development of controllers, performance in realistic experimental setup, fitting of appropriate models and compared performance in heating and cooling. The development efforts and barriers hindering the deployment of MPC controllers at large scale for building climate control have additionally been discussed. The performance of the developed controllers was evidenced in the thesis, proving their potential for load-shifting incentivized by different penalty signals: they could become a strong asset to unlock demand-side flexibility and in fine, help integrating a larger share of RES in the grid.Para aprovechar todo el potencial de flexibilidad energética de las cargas térmicas en los edificios equipados con bombas de calor se requiere de sistemas de control inteligente. Una revisión bibliográfica ha revelado que la mayoría de las estrategias de gestión utilizadas para esta finalidad pueden ser clasificadas en dos categorías: control en base a reglas (RBC en inglés) o predictivo (MPC en inglés), basado en optimización y en el uso de modelos. Tanto RBC como MPC pueden utilizar señales externas de penalización para fundamentar sus decisiones. El precio de la electricidad es utilizado a este fin de forma habitual en estrategias de reducción de coste. Una nueva señal de emisiones marginales de CO2 fue también creada como alternativa. Se han desarrollado un controlador RBC y un MPC para sistemas de bombas de calor aire-agua que cubren las demandas de climatización y agua caliente en el ámbito residencial. El RBC modula las consignas de temperatura, y el MPC minimiza las penalizaciones totales del sistema, al mismo tiempo que se consideran restricciones operativas y de confort. En particular, el MPC ha requerido el desarrollo de nuevos modelos simplificados, para predecir la demanda del edificio y el rendimiento de la bomba de calor, tanto en modo calefacción como en modo refrigeración. Otras novedades añadidas en la configuración del MPC son la formulación entera mixta, y la consideración del retraso debido al tiempo de cómputo. Los controladores fueron testeados, primeramente, en un entorno experimental -hardware-in-the-loop-, con una bomba de calor real instalada en el laboratorio y conectada a unos bancos térmicos que emulan las cargas térmicas del edificio. El entorno experimental ha permitido poner de manifiesto algunos retos prácticos tales como la discrepancia en el modelo del MPC y conflictos de conexión con el controlador local de la bomba de calor. En segundo lugar, un entorno de simulación ha sido creado para testear diversas configuraciones, usando TRNSYS acoplado con MATLAB. Para ello, se ha desarrollado un modelo detallado de la bomba de calor, basado en ensayos realizados en laboratorio, que reproduce el comportamiento dinámico de la bomba de calor con alta fidelidad. Tanto los resultados experimentales como los simulados han revelado la capacidad de los dos tipos de control de desplazar las cargas del edificio hacia periodos donde la electricidad era más barata o había menos emisiones de CO2, estos dos objetivos presentando de hecho impactos contradictorios. En los casos donde el control de referencia presentaba un amplio margen de mejora, los controladores RBC y MPC han demostrado la capacidad de actuar eficientemente y proveer ahorros importantes: alrededor de un 15% de emisiones en modo calefacción, y de un 30% de coste en modo frío. En aquellos casos en el que el control de referencia actuaba de forma cercana a la óptima, los controladores RBC no han sido capaces de aportar mejoras significativas, mientras que el MPC ha demostrado la capacidad de conseguir ahorros de un 5% de coste en modo calefacción y de un 10% de emisiones en modo frío. La investigación realizada en esta tesis ha abarcado amplios aspectos de la flexibilidad energética en los edificios: la generación de señales de penalización, la representación gráfica del potencial de flexibilidad, el ajuste de modelos simplificados, el desarrollo de controladores, el ensayo en entorno experimental y de simulación, con la consecuente evaluación de su rendimiento comparado en periodos de invierno y de verano, así como una discusión de las barreras que dificultan la implementación de controladores MPC y RBC a gran escala. Finalmente, la tesis ha evidenciado el rendimiento de los controladores desarrollados si se formulan de forma adecuada, demostrando su potencial para el desplazamiento del consumo eléctrico en la edificación residencial con sistemas de bomba de calor respondiendo a diferentes señales de penalización. En conclusión, los sistemas propuestos pueden ser elementos muy valiosos para favorecer la necesaria flexibilidad de la demanda térmica en la edificación y posibilitar la integración de sistemas de generación renovables en la re

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Processing and Technology of Dairy Products

This foods Special Issue contains seven papers on a range of technical dairy topics. Three involve beneficial uses of proteolytic enzymes, two involve the use of membrane technology in cheese making, while two deal with the role of ingredients, raw milk in the UHT paper and apricot fibre in the yogurt paper, in product quality. In all, the papers demonstrate the breadth of on-going research for an industry based on just one raw material, milk