Towards an Agent Based Framework for Modelling Smart Self-Sustainable Systems

Self-sustainability is a property of a system; a system is considered to be self-sustainable if it can sustain itself without external support in an observed period of time. If this property is mapped to a human settlement in context of resources (water, energy, food, etc.), it would describe a human settlement which is independent of external resources (like the national electrical grid or a central water distribution system), where such external resources are either not available, or not desirable. This article contributes to presenting the state-of-the-art overview of self-sustainability-related research. While self-sustainability as in the above described form was not a direct subject of research, there are several fields which are either related to, or could be of significant value to the self-sustainability research in this context. The extensive literature overview also showed no frameworks for modeling self sustainable systems in the context of human settlements. Herein a motivation for using agent-based modeling and simulation techniques will be given

Agent-based control for decentralised demand side management in the smart grid

Central to the vision of the smart grid is the deployment of smart meters that will allow autonomous software agents, representing the consumers, to optimise their use of devices and heating in the smart home while interacting with the grid. However, without some form of coordination, the population of agents may end up with overly-homogeneous optimised consumption patterns that may generate significant peaks in demand in the grid. These peaks, in turn, reduce the efficiency of the overall system, increase carbon emissions, and may even, in the worst case, cause blackouts. Hence, in this paper, we introduce a novel model of a Decentralised Demand Side Management (DDSM) mechanism that allows agents, by adapting the deferment of their loads based on grid prices, to coordinate in a decentralised manner. Specifically, using average UK consumption profiles for 26M homes, we demonstrate that, through an emergent coordination of the agents, the peak demand of domestic consumers in the grid can be reduced by up to 17% and carbon emissions by up to 6%. We also show that our DDSM mechanism is robust to the increasing electrification of heating in UK homes (i.e. it exhibits a similar efficiency)

A multi-agent intelligent decision making support system for home energy management in smart grid: A fuzzy TOPSIS approach

In the context of intelligent home energy management in smart grid, the occupants' consumption behavior has a direct effect on the demand and supply of the electrical energy market. Correspondingly, the policies of the utility providers affect consumption behavior so techniques and tools are required to analyse the occupants' preferences, habits and lifestyles in order to support and facilitate their decision-making regarding the curtailing of their energy consumption and costs. The uncertainty about householders' preferences increases the uncertainty of appliance prioritization and makes it difficult to determine the consistency of preferences in terms of energy consumption. In this complex system, the preferences and judgments of householders are represented by linguistic and vague patterns. This paper proposes a much better representation of this linguistics that can be developed and refined by using the evaluation methods of fuzzy set theory. The proposed approach will apply the fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) for achieving preferences. Based on our detailed literature review of the multi-agent system approach in this field, it is expected that the proposal model will offer a robust tool for communication and decision-making between occupant agents and dynamic environmental variables. It is shown that the proposed fuzzy TOPSIS approach will enable and assist householders to maximize their participation in demand response programs

Framework for Efficient Electrical Energy Management Practice in Public Universities in Southwestern Nigeria

Energy management practices are subject to various worries that impact on achieving electricity saving objectives. This is most apparent in the case of Public Universities in Nigeria due to the number of electricity end users with conflicting interests. Efficient electrical energy management in Public Universities in Nigeria becomes crucial. The present work developed a multidimensional framework of efficient electricity management by considering all relevant measures of performance. To achieve the formation of this evaluation framework, it has considered the case of three relatively old public universities and collected the viewpoints of 4728 respondents comprising students, staff, and business owners involved in the aggregate electricity use in Public Universities in Nigeria. We adopted a quantitative survey and questionnaire as instrument for gathering relevant data. The results of the analysis of data obtained during the survey were used to develop the framework by considering key attributes. The study concluded that the formation of the newly-proposed quantitative efficient electricity management framework for improving the energy performance of public university buildings can provide the university management with an effective tool to benchmark with different university buildings internationally and assist the priority setting of efficient electricity savings. Keywords: Framework, Efficiency, electrical energy management, Practice, Public universities, Southwestern Nigeri

Fostering Smart Cities through ICT Driven Policy-Making: Expected Outcomes and Impacts of DAREED Project

YesThe concept of smart city is emerging as a key strategy to tackle the problems generated by the urban population growth and rapid development. It is widely recognised that Information and Communications Technology (ICT) play a key role in addressing some of the urban societal challenges such as improving energy efficiency and reducing carbon emissions. Although there are various ICT tools providing intelligence and services relating to energy consumption and monitoring processes, they mostly tend to work in isolation. Therefore, this paper presents the outcomes and impacts of the concept of DAREED which aims to deliver an integrated ICT service platform to drive energy efficiency and low carbon activities at neighbourhood, city and district levels. Furthermore, the research highlights the need for ICT-driven policy making using platforms such as DAREED in the context of e-Government. This paper contributes to the current understandings of e-Government literature in terms of how ICT can help public authorities and stakeholders such as policy makers to achieve and drive energy efficiency. From a practical stance, the paper offers valuable insights to public administrations on how ICT can be used to address pressing societal challenges such as efficient energy use and facilitate better policy making

A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

An Energy Management Service for the Smart Office

The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart building, enabling it to maximize the self-consumption of photovoltaic electricity and to participate in the energy market, thus taking advantage of time-variable tariffs to achieve economic savings. This paper proposes an energy management infrastructure specifically tailored for a smart office building, which relies on measured data and on forecasting algorithms to predict the future patterns of both local energy generation and power loads. The performance is compared to the optimal energy usage scheduling, which would be obtained assuming the exact knowledge of the future energy production and consumption trends, showing gaps below 10% with respect to the optimum