Policy-based power consumption management in smart energy community using single agent and multi agent Q learning algorithms

Power consumption in residential sector has increased due to growing population, economic growth, invention of many electrical appliances and therefore is becoming a growing concern in the power industry. Managing power consumption in residential sector without sacrificing user comfort has become one of the main research areas recently. The complexity of the power system keeps growing due to the penetration of alternative sources of electric energy such as solar plant, Hydro, Biomass, Geothermal and wind farm to meet the growing demand for electricity. To overcome the challenges due to complexity, the power grid needs to be intelligent in all aspects. As the grid gets smarter and smarter, considerable efforts are being undertaken to make the houses and businesses smarter in consuming the electrical energy to minimize and level the electricity demand which is also known as Demand Side Management (DSM). It also necessitates that the conventional way of modelling, control and energy management in all sectors needs to be enhanced or replaced by intelligent information processing techniques. In our research work, it has been done in several stages. (Purpose of Study and Results) We proposed a policy-based framework which allows intelligent and flexible energy management of home appliances in a smart home which is complex and dynamic in ways that saves energy automatically. We considered the challenges in formalizing the behaviour of the appliances using their states and managing the energy consumption using policies. Policies are rules which are created and edited by a house agent to deal with situations or power problems that are likely to occur. Each time the power problem arises the house agent will refer to policy and one or a set of rules will be executed to overcome that situation. Our policy-based smart home can manage energy efficiently and can significantly participate in reducing peak energy demand (thereby may reduce carbon emission). Our proposed policy-based framework achieves peak shaving so that power consumption adapts to available power, while ensuring the comfort level of the inhabitants and taking device characteristics in to account. Our simulation results on MATLAB indicate that the proposed Policy driven homes can effectively contribute to Demand side power management by decreasing the peak hour usage of the appliances and can efficiently manage energy in a smart home in a user-friendly way. We propounded and developed peak demand management algorithms for a Smart Energy Community using different types of coordination mechanisms for coordination of multiple house agents working in the same environment. These algorithms use centralized model, decentralized model, hybrid model and Pareto resource allocation model for resource allocation. We modelled user comfort for the appliance based on user preference, the power reduction capability and the important activities that run around the house associated with that appliance. Moreover, we compared these algorithms with respect to their peak reduction capability, overall comfort of the community, simplicity of the algorithm and community involvement and finally able to find the best performing algorithm among them. Our simulation results show that the proposed coordination algorithms can effectively reduce peak demand while maintaining user comfort. With the help of our proposed algorithms, the demand for electricity of a smart community can be managed intelligently and sustainably. This work is not only aiming for peak reduction management it aims for achieving it while keeping the comfort level of the inhabitants is minimum. It can learn user’s behaviour and establish the set of optimal rules dynamically. If the available power to a house is kept at a certain level the house agent will learn to use this notional power to operate all the appliances according to the requirements and comfort level of the household. This way the consumers are forced to use the power below the set level which can result in the over-all power consumption be maintained at a certain rate or level which means sustainability is possible or depletion of natural resources for electricity can be reduced. Temporal interactions of Energy Demand by local users and renewable energy sources can also be done more efficiently by having a set of new policy rules to switch between the utility and the renewable source of energy but it is beyond the scope of this thesis. We applied Q learning techniques to a home energy management agent where the agent learns to find the optimal sequence of turning off appliances so that the appliances with higher priority will not be switched off during peak demand period or power consumption management. The policy-based home energy management determines the optimal policy at every instant dynamically by learning through the interaction with the environment using one of the reinforcement learning approaches called Q-learning. The Q-learning home power consumption problem formulation consisting of state space, actions and reward function is presented. The implications of these simulation results are that the proposed Q- learning based power consumption management is very effective and enables the users to have minimum discomfort during participation in peak demand management or at the time when power consumption management is essential when the available power is rationale. This work is extended to a group of 10 houses and three multi agent Q- learning algorithms are proposed and developed for improving the individual and community comfort while at the same time keeping the power consumption below the available power level or electricity price below the set price. The proposed algorithms are weighted strategy sharing algorithm, concurrent Q learning algorithm and cooperative distributive learning algorithm. These proposed algorithms are coded and tested for managing power consumption of a group of 10 houses and the performance of all three algorithms with respect to power management and community comfort is studied and compared. Actual power consumption of a community and modified power consumption curves using Weighted Strategy Sharing algorithm, Concurrent learning and Distributive Q Learning and user comfort results are presented, and the results are analysed in this thesis

Artful Systems: Investigating everyday practices of family life to inform the design of information technology for the home

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The research in this thesis was motivated by an interest in understanding the work and effort that goes into organising family homes, with the aim of informing the design of novel information technology for the home. It was undertaken to address a notable absence of in-depth research into domestic information and communication technology in the fields of Human Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW). To that end, this thesis presents an ethnographic study of everyday routines in thirteen family homes. Following an established tradition within HCI and CSCW, the study applies qualitative fieldwork methods as a means to investigate and interpret the empirical materials. Periods of extended observation and semi-structured interviews with the thirteen families over a three-year period form the basis of the empirical material. The materials are analysed using a hybrid perspective composed of a combination of influences from the study of material culture, to interaction analysis and ethnography. The hybrid analytical perspective draws out insights regarding the families’ mundane practices and the artfully devised solutions they use to organise daily life. Four household activities and artefacts are given specific focus: (i) household list making, (ii) the display qualities of refrigerator doors, (iii) the organisation of household clutter, and (iv) the devising of bespoke solutions in organising home life. Broader findings include the observations that people tailor solutions to meet their needs, that optimum efficiency is not the pre-eminent determinant in what method or artefact people choose to organise themselves and their homes, and that homes determine their individual characters in part by how everyday tasks and organisation are accomplished. In short, the personal qualities of these mundane practices are part of what makes a home a home. These findings are used to elicit implications for information technology design, with the aim of encouraging designers of domestic technology to be aware of and respectful towards the idiosyncratic nature of the home, and, wherever possible, to design in such a way as to allow the technology to be appropriated for families’ bespoke tailoring. To evaluate and address this point, two design projects, one on augmented magnets and another on a “media bowl”, are used to develop and test out this approach. Both projects are critically examined to reflect on the efficacy of the design approach and what lessons might be learnt for future studies and design exercises. The combination of detailed ethnographic fieldwork on family homes combined with the development of experimental design projects is intended to deepen the understanding of the mundane behaviours and everyday routines of family homes, in order to better inform the design of information technology for the home

Artful systems : investigating everyday practices of family life to inform the design of information technology for the home

The research in this thesis was motivated by an interest in understanding the work and effort that goes into organising family homes, with the aim of informing the design of novel information technology for the home. It was undertaken to address a notable absence of in-depth research into domestic information and communication technology in the fields of Human Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW). To that end, this thesis presents an ethnographic study of everyday routines in thirteen family homes. Following an established tradition within HCI and CSCW, the study applies qualitative fieldwork methods as a means to investigate and interpret the empirical materials. Periods of extended observation and semi-structured interviews with the thirteen families over a three-year period form the basis of the empirical material. The materials are analysed using a hybrid perspective composed of a combination of influences from the study of material culture, to interaction analysis and ethnography. The hybrid analytical perspective draws out insights regarding the families’ mundane practices and the artfully devised solutions they use to organise daily life. Four household activities and artefacts are given specific focus: (i) household list making, (ii) the display qualities of refrigerator doors, (iii) the organisation of household clutter, and (iv) the devising of bespoke solutions in organising home life. Broader findings include the observations that people tailor solutions to meet their needs, that optimum efficiency is not the pre-eminent determinant in what method or artefact people choose to organise themselves and their homes, and that homes determine their individual characters in part by how everyday tasks and organisation are accomplished. In short, the personal qualities of these mundane practices are part of what makes a home a home. These findings are used to elicit implications for information technology design, with the aim of encouraging designers of domestic technology to be aware of and respectful towards the idiosyncratic nature of the home, and, wherever possible, to design in such a way as to allow the technology to be appropriated for families’ bespoke tailoring. To evaluate and address this point, two design projects, one on augmented magnets and another on a “media bowl”, are used to develop and test out this approach. Both projects are critically examined to reflect on the efficacy of the design approach and what lessons might be learnt for future studies and design exercises. The combination of detailed ethnographic fieldwork on family homes combined with the development of experimental design projects is intended to deepen the understanding of the mundane behaviours and everyday routines of family homes, in order to better inform the design of information technology for the home.EThOS - Electronic Theses Online ServiceGBUnited Kingdo