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Metall- und Maschinenbauunternehmen müssen im Durchschnitt pro Jahr ca. zwei Prozent ihres Umsatzes für Strom und Erdgas ausgeben und die Unternehmer gehen von weiteren Preissteigerungen aus. Damit rückt das Thema Energieeinsparung stärker denn je in den Fokus und wird zu einem strategischen Faktor. Um Kosten zu sparen und Wettbewerbsvorteile zu sichern, ist es notwendig, zielgenaue Energieeinsparmaßnahmen einzuleiten. Die ersten Maßnahmen, welche die meisten Maschinenbauunternehmen umsetzen, sind die Erneuerung der Beleuchtungs-, Heizungs- und Lüftungsanlage, die Verbesserung der Drucklufterzeugung sowie die thematische Sensibilisierung der Mitarbeiter. Aber auch in Maschinen mit ihren dazugehörigen elektrischen Antrieben, Lüftern und Aggregaten verbirgt sich eine große Menge an Optimierungspotenzial. Allerdings ist es hier notwendig nicht die Verbraucher im Einzelnen, sondern die Maschine und deren Prozesse im Ganzen zu betrachten. Meist fehlen hierfür aber geeignete Schnittstellen, um die Messwerte von Sensoren (bspw. Temperatur-, Drucksensoren, etc.) und Antrieben auslesen zu können, was dazu führt, dass diese Potenziale nicht ausgeschöpft werden.

The average metal and mechanical engineering company must spend around two per cent of its annual turnover on electricity and natural gas, and companies are expecting further price increases. As a result, the issue of energy saving is becoming more of a strategic factor than ever before. In order to save costs and ensure competitive advantages, it is necessary to introduce precise energy-saving measures. The first steps taken by most mechanical engineering companies are to replace lighting, heating, and ventilation systems, improve compressed air generation and raise employee awareness. However, there is also a great potential for optimization in machines with their individual electrical drives, fans, and units. In this case, though, it is necessary to look at the machine and its processes as a whole rather than the individual electrical energy consumers. In most cases, however, there is a lack of suitable interfaces for analyzing the measured values from sensors (e.g. temperature, pressure sensors, etc.) and drives, which concludes that this potential is not fully exploited.

Mälarenergi’s vision is a world where we live and operate together without climate impact. This degree project has examined which opportunities Mälarenergi Elnät has in order to work towards this vision by looking more closely at whether their bigger substations can become self-sufficient in terms of heating, cooling and battery charging. The purpose of this degree project was to investigate how heat recovery from the substations’ transformers and the installation of PV-systems could contribute to both more environmentally friendly and self-sufficient substations. In addition to that, the economics and how this would affect the Swedish power grid regulation were of interest. The thesis was based on current values and data for oil temperatures and installed power in three of Mälarenergi Elnät’s substations. In addition to this, the thesis also includes a literature study, where previous research in heat transfer from power transformers, up-to-date information about PV-installations and the power grid regulation in Sweden were studied. The results of the thesis showed that both PV-installations and heat exchange for heating the station buildings could be of great benefit for Mälarenergi Elnät. In all but one case, the energy saving measures resulted in lower life cycle costs than if no measures were taken. It shows that the measures investigated in the thesis are not only good from an environmental perspective, but also has economic profitability.

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Studien är utförd åt Freezing Food Småland Öland AB. Syftet med undersökningen var att ge förslag på åtgärder som minskar anläggningens energibehov samt att beräkna återbetalningstid för åtgärder. Genom användningen av simuleringsprogramvara tillsammans med data från praktiska mätningar så testades olika förändringar i anläggningen. Studien resulterade i förslag på en höjning av frysrumstemperaturen och temperaturen i LTB1. Dessa åtgärder höjer anläggningens köldfaktor och minskar energibehovet. Förslag för att få bukt på istillväxten är att isolera av komponenter så som rör och ventiler. Isolering ger en energibesparing och en minskad risk för korrosion. Genom belastningstester framkom det att kompressorerna arbetar ofördelaktigt så förslag på lämpliga driftområden togs fram för att öka verkningsgraden och minska underhållskostnaderna och energibehovet. Anläggningen visade sig vara väl dimensionerad mot transmissionsförluster men att golvvärmen står för en oproportionerligt stor del av förlusterna i förhållande till dess yta. / The study is conducted for Freezing Food Småland Öland AB. The purpose of the study was to propose measures to decrease the facility’s energy demand and to calculate the payback time for these suggestions. By means of using simulation software along with data from practical measurements different configurations in the facility were tested. The study resulted in suggestions consisting of an increase of the temperature in the freezing room and the temperature in LTB1.Those suggestions increases the facilities COP and decreases the energy consumption. Proposals to curb the ice growth are the insulation of components such as pipes and valves. Insulation results in a small decrease in energy demand but greatly increases the accessibility and also decreases the risk of corrosion. Through load tests conducted on the compressors it showed that the compressors were not driven in the optimal load range, suggestions were made for operation in a more favourable load range. Thus increasing the efficiency and cutting the maintenance costs. From the results it is shown that the facility is well built and dimensioned against thermal transmission. Though it turned out that the floor heating accounts for a disproportionate amount of the thermal transmission.

Wastewater treatment facilities around the world use significant amount of energy which contributes to large quantities of greenhouse gas (GHG) emissions. According to the U.S.EPA, nearly 3% of the USA's energy is used to treat wastewater. This consumption is increasing at faster rates with increase in population and regulations. Wastewater facilities use large number of pumps in their transfer stations, treatment plants, and effluent pump stations. All these pumps consume considerable amounts of energy. This study presents a preliminary energy inspection of two facilities from Louisiana. This audit provides an inventory of the energy consumed for various activities like pumping, treatment, and discharge. This analysis helps the operators to identify the potential power consuming areas and optimize by adopting several energy conservation measures (ECMs). This study also involves the quantification of GHG emissions based on the energy consumption. The benefits of the study include minimizing energy and GHG emission.

La maîtrise de la demande en climatisation des bâtiments tertiaires peut contribuer à la limitation du réchauffement climatique à 2°C. Les réseaux de froid urbain sont une solution pour répondre à cette demande avec une haute efficacité énergétique. Une conduite performante est cependant essentielle pour maintenir et augmenter leurs avantages compétitifs. L'objectif de la thèse est de contribuer à la construction d'un outil d'aide à la conduite journalière des réseaux de froid. La difficulté réside à deux niveaux : la diversité des décisions et la complexité des phénomènes physiques sous-jacents. L'originalité est de proposer une méthodologie pour aider au pilotage des groupes frigorifiques, des tours aéroréfrigérantes, de la pression différentielle et de la répartition de puissance entre des centrales de production aux performances variables. La méthodologie développée est appliquée au réseau de froid de Paris-Bercy exploité par Climespace. Tout d'abord, un modèle intégrant une représentation physique des centrales de production, du réseau de distribution et des sous-stations, est développé. En particulier, un modèle de type semi-empirique, paramétrable sur des mesures, est modifié pour calculer les performances non-nominales des groupes frigorifiques centrifuges. La validation du modèle complet est réalisée sur un jeu de données indépendant de l'identification. Ensuite, le modèle est exploité pour rechercher une conduite optimisée à partir d'un modèle de prévision de la demande. La méthode proposée est séquentielle : résolution a priori des optimisations locales puis génération de modèles quadratiques de centrales servant à déterminer la répartition optimale. La pression différentielle est minimisée à partir de l'identification, par simulation, de la sous-station défavorisée. Enfin, la réduction de la consommation électrique est évaluée sur une semaine d'été. / Cooling demand management of commercial buildings can contribute to limit global warming below 2°C. District cooling is an energy-efficient option. However, improving operational performance is of great importance to ensure and increase its competitive advantages. The aim of this thesis is to contribute to the development of a decision-support tool for daily operation of district cooling networks. Challenges lie at two levels: diversity of decisions to be taken and complexity of physical phenomena involved. The original aspect of our work is to propose a methodology to improve chillers and cooling towers control, differential pressure management and dispatching between production plants with variable efficiency. Our developments are applied to the district cooling of Paris-Bercy, operated by Climespace. First; a model featuring a physical description of chilled-water production plants, distribution network and buildings substations, is developed. In particular, a semi-empirical model with identified parameters is modified to compute non-nominal characteristics of centrifugal chillers. The system model is validated against an independent dataset. Then, the model is used to find optimized controls from cooling loads forecast. The proposed methodology is sequential: pre-computation of optimal set-points at plant level and then generation of quadratic plant models to solve the dispatching optimization problem at each time step. Differential pressure is minimized with a simulation-based tracking of the critical substation. To conclude, electricity consumption reduction with optimized controls is evaluated during a summer week.

Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving clock speed, reducing energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long wires having high load capacitance which leads to delay in execution and significantly high energy consumption. Inter-cluster communication also introduces many short idle cycles, therby significantly increasing the overall leakage energy consumption in the functional units. The trend towards miniatrurization of devices (and associated reduction in threshold voltage) makes energy consumption in interconnects and functional units even worse and limits the usability of clustered architectures in smaller technologies. In the past, study of leakage energy management at the architectural level has mostly focused on storage structures such as cache. Relatively, little work has been done on architecture level leakage energy management in functional units in the context of superscalar processors and energy efficient scheduling in the context of VLIW architectures. In the absence of any high level model for interconnect energy estimation, the primary focus of research in the context of interconnects has been to reduce the latency of communication and evaluation of various inter-cluster communication models. To the best of our knowledge, there has been no such work in the past from the point of view of enegy efficiency targeting clustered VLIW architectures specifically focusing on smaller technologies. Technological advancements now permit design of interconnects and functional units With varying performance and power modes. In thesis we people scheduling algorithms that aggregate the scheduling slack of instructions and communication slack of data values to exploit the low power modes of interconnects and functional units . We also propose a high level model for estimation of interconnect delay and energy (in contrast to low-level circuit level model proposed earlier) that makes it possible to carry out architectural and compiler optimizations specifically targeting the inter connect, Finally we present synergistic combination of these algorithms that simultaneously saves energy in functional units and interconnects to improve the usability of clustered architectures by archiving better overall energy-performance trade-offs. Our compiler assisted leakage energy management scheme for functional units reduces the energy consumption of functional units approximately by 15% and 17% in the context of a 2-clustered and a 4-clustered VLIW architecture respectively with negligible performance degradation over and above that offered by a hardware-only scheme. The interconnect energy optimization scheme improves the energy consumption of interconnects on an average by 41% and 46% for a 2-clustered and a 4-clustered machine respectively with 2% and 1.5% performance degradation. The combined scheme options slightly better energy benefit in functional units and 37% and 43% energy benefit in interconnect with slightly higher performance degradation. Even with the conservative estimates of contribution of functional unit interconnect to overall processor energy consumption the proposed combined scheme obtains on an average 8% and 10% improvement in overall energy delay product with 3.5% and 2% performance degradation for a 2-clustered and a 4-clustered machine respectively. We present a detailed experimental evaluation of the proposed schemes using the Trimaran compiler infrastructure.

Emerging low power, embedded, wireless sensor devices are useful for wide range of applications, yet have very limited processing storage and especially energy resources. Sensor networks have a wide variety of applications in medical monitoring, environmental sensing and military surveillance. Due to the large number of sensor nodes that may be deployed and the required long system lifetimes, replacing the battery is not an option. Sensor systems must utilize the minimal possible energy while operating over a wide range of operating scenarios. The most of the efforts in the energy management in sensor networks have concentrated on minimizing energy consumption in the communication subsystem. Some researchers have also dealt with the issue of minimizing the energy in computing subsystem of a sensor network node. Some proposals using energy aware software have also been made. Relatively little work has been done on compiler controlled energy management in sensor networks. In this thesis, we present our investigations on how compiler techniques can be used to minimize CPU energy consumption in sensor network nodes. One effectively used energy management technique in general purpose processors, is dynamic voltage scaling. In this thesis we implement and evaluate a compiler assisted DVS algorithm and show its usefulness for a small sensor node processor. We were able to achieve an energy saving of 29% with a little performance slowdown. Scratchpad memories have been widely used for improving performance. In this thesis we show that if the scratchpad size for the system is chosen carefully, then large energy savings can be achieved by using a compiler assisted scratchpad allocation policy. With a small size of 512 byte scratchpad memory we were able to achieve 50% of energy savings. We also studied the behavior of dynamic voltage scaling in presence of scratchpad memory. Our results show that in presence of scratchpad memory less opportunities are found for applying dynamic voltage scaling techniques. The sensor network community lacks a comprehensive benchmark suite, for our study we also implemented a set of applications, representative of computational workload on sensor network nodes. The techniques studied in this thesis can easily be integrated with existing energy management techniques in sensor networks, yielding in additional energy savings.