Nitrate discharges from diffuse agricultural sources have long term effects on groundwater and surface water quality. Market-based instruments have been proposed as a means of balancing the demand for nitrate intensive farming and the capacity of the natural water bodies to dilute nitrates. Trading is complicated by the dispersed, delayed, and protracted effects of diffuse sources. Market mechanisms proposed to date have failed to incorporate these physical characteristics of nitrate pollution correctly. We propose a new market mechanism for allocating and pricing nitrate discharge permits, based on the design of modern electricity markets which use LP models to find optimal prices and dispatch schedules. The system operates as a centralized auction. The sources submit bids to the auction indicating the benefits gained from each unit of nitrate discharge. The auction operator runs an LP which maximises the benefits from trade, subject to a set of environmental and operational constraints. The LP solution produces the optimal prices and allocations relative to the economic values indicated in the bids. Our contributions include alternative LP models to suit different hydro-geological and socio-economic conditions. We present a generalized LP model which can include constraints that describe nitrate residence and transport in groundwater and surface water, the ability of water bodies to accept nitrates, and the operational limitations of the commercial sources. We show how to adapt available methods to incorporate the complex physical systems into an optimisation model. We present a double-sided market model which allows the polluters to buy permits, and environmental agents to lease out the ability of the natural water resources to accept nitrates. The model allows the providers of environmental services to participate in the market as sellers. We build up and prove the concepts by explaining the prices and allocations produced by the LP models. Based on the theory of nodal pricing applied in electricity markets, we discuss the price structures and relationships and show how the prices would reflect the spatial and temporal effects of diffuse nitrate discharges. We interpret the information generated from the outcomes of trading and discuss how the available tools and information can be used by the market participants to optimize their bids. We expand the proposed market model to include point sources, and identify the factors that determine the extent to which the point and nonpoint sources can trade with each other. In addition, we develop measures of the extent to which the diffuse sources themselves can trade with each other. We demonstrate the models and the resulting prices and allocations, using a catchment nitrate transport model.

Most smart actuators exhibit rate-dependant hysteresis when the working frequency is higher than 5Hz. Although the Preisach model has been a very powerful tool to model the static hysteresis, it cannot be directly used to model the dynamic hysteresis. Some researchers have proposed various generalizations of the Preisach operator to model the rate-dependant hysteresis, however, most of them are application-dependant and only valid for low frequency range. In this thesis, a first-order dynamic relay operator is proposed. It is then used to build a novel dynamic Preisach model. It can be used to model general dynamic hysteresis and is valid for a large frequency range. Real experiment data of magnetostrictive actuator is used to test the proposed model. Experiments have shown that the proposed model can predict all the static major and minor loops very well and at the same time give an accurate prediction for the dynamic hysteresis loops. The controller design using the proposed model is also studied. An inversion algorithm is developed and a PID controller with inverse hysteresis compensation is proposed and tested through simulations. The results show that the PID controller with inverse compensation is good at regulating control; its tracking performance is really limited (average error is 10 micron), especially for high frequency signals. Hence, a simplified predictive control scheme is developed to improve the tracking performance. It is proved through experiments that the proposed predictive controller can reduce the average tracking error to 2 micron while preserve a good regulating performance.

By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part of the larger concept called smart grids. Previous work in this area has concerned the utilization of demand response by grid owners. In this thesis the focus will instead be shifted towards the electrical companies that have balance responsibility, and how they could use demand response in order to make profits. By investigating electrical appliances in hourly measured households, the business value from decreasing electrical companies’ power imbalances has been quantified. By an iterative simulation scheme an optimal value was found to be 977 SEK/year and appliance. It could however be shown that the value became larger for energy inefficient households, and that such consumers’ participation in a demand response market would be prioritized ahead of other measures like isolating walls is rather unlikely. Thermal appliance whose load depend on the outdoor temperature are less valuable for demand response during the summer months, and the annual value would increase if less seasonally dependent appliances were used. Additionally, by increasing the market price amplitudes and the imbalance price volatility, it could be shown that the potential for such demand response markets is larger in e.g. the Netherlands and Germany.

Electric power distribution systems are gradually adopting new advancements in communication, control, measurement, and metering technologies to help realize the evolving concept of Smart Grids. Future distribution systems will facilitate increased and active participation of customers in Demand Side Management activities, with customer load profiles being primarily governed by real-time information such as energy price, emission, and incentive signals from utilities. In such an environment, new mathematical modeling approaches would allow Local Distribution Companies (LDCs) and customers the optimal operation of distribution systems and customer's loads, considering various relevant objectives and constraints. This thesis presents a mathematical model for optimal and real-time operation of distribution systems. Thus, a three-phase Distribution Optimal Power Flow (DOPF) model is proposed, which incorporates comprehensive and realistic models of relevant distribution system components. A novel optimization objective, which minimizes the energy purchased from the external grid while limiting the number of switching operations of control equipment, is considered. A heuristic method is proposed to solve the DOPF model, which is based on a quadratic penalty approach to reduce the computational burden so as to make the solution process suitable for real-time applications. A Genetic Algorithm based solution method is also implemented to compare and benchmark the performance of the proposed heuristic solution method. The results of applying the DOPF model and the solution methods to two distribution systems, i.e., the IEEE 13-node test feeder and a Hydro One distribution feeder, are discussed. The results demonstrate that the proposed three-phase DOPF model and the heuristic solution method may yield some benefits to the LDCs in real-time optimal operation of distribution systems in the context of Smart Grids. This work also presents a mathematical model for optimal and real-time control of customer electricity usage, which can be readily integrated by industrial customers into their Energy Hub Management Systems (EHMSs). An Optimal Industrial Load Management (OILM) model is proposed, which minimizes energy costs and/or demand charges, considering comprehensive models of industrial processes, process interdependencies, storage units, process operating constraints, production requirements, and other relevant constraints. The OILM is integrated with the DOPF model to incorporate operating constraints required by the LDC system operator, thus combining voltage optimization with load control for additional benefits. The OILM model is applied to two industrial customers, i.e., a flour mill and a water pumping facility, and the results demonstrate the benefits to the industrial customers and LDCs that can be obtained by deploying the proposed OILM and three-phase DOPF models in EHMSs, in conjunction with Smart Grid technologies.

Bidirectional vehicle-to-grid (V2G) system utilizes the batteries of parked electric-drive-vehicles to provide energy storage and backup services in a power system. Such services in a V2G-equipped microgrid system can be used as an enabler of enhancing the renewable energy source (RES) penetration by storing the energy during the surplus of RES supply and supplying the energy during the lack of RES supply. In this research, we aim at enhancing the storage capacity of V2G system by introducing a novel vehicle-to-vehicle power transfer operation that runs on the top of V2G services. The vehicle-to-vehicle (V2V) operation transfers the energy from the source vehicles (which are parked for relatively longer times) to the destination vehicles (which are parked for relatively shorter times). The depleted energy of the source vehicles is fulfilled by the surplus RES supply in the future. In this way, the destination vehicles are effectively charged by RES supply, thereby enhancing the storage capacity of the V2G system. We can also say that the V2V operation would become beneficial only when there is a sufficient amount of surplus RES supply in the future. We propose a decision rule to distinguish if a vehicle should be a source vehicle or a destination vehicle during the V2V operation. The decision rule is designed based on the two factors, namely the state-of-charge of vehicle’s battery, and the remaining time of vehicle to depart. In this research, we conduct a comprehensive study to analyze the impacts of state-of-charge and mobility pattern of vehicles on different performance metrics via simulation. The results shows that in order to achieve better performance of V2V operation, the state-of-charge of vehicle’s battery should be given more priority over the remaining time of vehicle to depart. The vehicle mobility pattern with unexpected departure greatly reduced the overall performance of the V2G system.

Where is technology heading? And how will our behaviors towards these new innovations look? This project questions the direction of ”beyond smart” products, through scenarios within our everyday life. The work is both critical and speculative. Speculative in the sense that it is speculating in how a future scenario with ”beyond smart” products would look like. And by beyond smart I refer to the fact that the products would posses extreme features. Such as complexity and irationalism. But also to be spontaneous and self aware. At the same time the work is questioning, and perhaps criticising, if this sort of development really is beneficial for us or not. If we would turn to technology and smart products for a solution to our desires and problems, how would our human relationships towards each other look? And also how would we interact with these future products and what would the consequences of that be?

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of elds among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of ne-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this thesis, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We showthat our implementation is e cient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the thesis provide energy saving for the smart home.

The purpose of this thesis is to devise a system based on RFID (Radio Frequency IDentification) that can be used for smart healthcare applications. Location estimation, eloping prevention and occupancy detection are monitoring applications of smart healthcare which can provide very useful information for the nursing and administration staff of the nursing-home/hospital. The introduction of ubiquitous networking along with the concepts such as Internet of Things (IoT) can certainly help achieve the goals of smart healthcare. RFID technology has features, such as low power and small size, which makes this technology suitable for researching solutions for smart healthcare. Today several nursing-home/hospital monitoring solutions exist in the market and academia alike. The solutions marketed commercially are very expensive whereas the solutions from academia provides solutions to isolated problems but a comprehensive all in one solution that can meet the need of smart healthcare monitoring applications is missing. In this thesis we present a system that is low cost and suitable for accommodating a number of the smart healthcare applications including occupancy detection, location estimation, eloping prevention and access control. The solution is implemented on a customized Openbeacon Active RFID System (OARS). Active RFID based proximity detection is the core of our system. Practical experiments based on novel Proximity Detection based Weighted Centroid Localization (PD-WCL) method were done to analyze the performance of the system with different applications to highlight the applicability of the system.

In this dissertation, the issues of the increased awareness of energy use are considered. Energy technologies are continuously improved by energy retailers and academic researchers. The Smart Grid are soon customary as part of the energy domain. But in order to improve energy efficiency the change must come from the consumers. Consumers should be active decision makers in the Smart Grid domain and therefor a Recommender system suits the Smart Grid and enables customers. Customers will not use energy in the way energy retailers, and politicians advocates instead they will do what fits them. By investigating how a Recommender can be built in the Smart Grid we focus on parameters and information that supports the costumers and enables positive change. An investigation of what customers perceive as relevant is pursued as well as how relevancy can adjust the system. A conceptual model of how to build a Recommender is rendered through a literature review, a group interview and a questionnaire.

With the development of modern technology, mobile communications are changing people’s life and making their day to day life activities easier. The aim of this thesis work is to address one of the modern technology solution that simplifies and act as an HMI solution between a pump drive and a operator based on smart phones.   Xylem provides a wide range of pump control units, serving several advanced features includes condition monitoring, cleaning sequence, flow calculation, energy optimizer, sump cleaning and so on. Smart run is a pump control unit, whose parameters installed at wastewater pump stations are possible to monitor and configure physically using keypad or remotely using extension communication  gateway, which is a costly solution for installations and maintenance. So, a simple working prototype HMI solution based on smart phones is interested to see how smart phone can relay information between a pump control and an operator in the vicinity of the pump.    For this approach a thorough study has been done on different types of smart phones, their trends and different possible wireless communication solutions between  operator’s smart phone  and the pump. An interactive design process with a focus on usability and data representation  on a smart phone application was developed to support their needs and provide a cost effective solution. The result showed that this approach has many benefits includes serving as cost effective HMI solution, data monitoring, better alarm monitoring with additional information, enhanced display over Smart Run’s OLED displays, multilingual support, provides easier support services and also useful as a receiver unit for dewatering pumps hardware developed in parallel with this thesis. This thesis work is carried out in Xylem Water Solutions AB[1], Stockholm, Sweden in collaboration with Mittuniversitetet[2], Sundsvall, Department of Electronics Design.  This report can be used as groundwork for future development of smart phone applications for Xylem products [1]  http://www.xyleminc.com [2]  http://www.miun.se