Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

Design and simulation of an energy homeostaticity system for electric and thermal power management in a building with smart microgrid

Nowadays, microgrids are gaining importance in electric power generation and distribution environments due to their flexibility, versatility, scalability and the possibility of supplying ancillary services when connected to the grid. They allow for the customization of electric supply for very different types of consumers. Therefore, a new control model for power and energy management based on homeostaticity of electric power systems (EPS) is presented, which has been already analyzed and approved by ENEL Chile in its developmental stage. ENEL, the largest electric utility in the country, is interested in incorporating smart microgrids in the electricity distribution market, as part of a worldwide policy. Such microgrids are to be installed in buildings serviced by ENEL. To demonstrate the model’s utility, a Simulink model of a real microgrid is used, which is comprised of PV generation, energy storage, an air conditioning (AC) equipment and thermal storage of the building upon which the microgrid is installed. The behavior of every element is simulated, including the dynamic thermal model of the building in order to optimize energy management and power supply versus consumption. The behavior of the whole system is analyzed under different environmental profiles and energy consumption patterns using the proposed homeostaticity system.Ministry of Education RTI2018-094917-B-I00Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica FPU16-03522,3170399,FP

Towards homeostatic architecture: simulation of the generative process of a termite mound construction

This report sets out to the theme of the generation of a ‘living’, homeostatic and self-organizing architectural structure. The main research question this project addresses is what innovative techniques of design, construction and materials could prospectively be developed and eventually applied to create and sustain human-made buildings which are mostly adaptive, self-controlled and self-functioning, without option to a vast supply of materials and peripheral services. The hypothesis is that through the implementation of the biological building behaviour of termites, in terms of collective construction mechanisms that are based on environmental stimuli, we could achieve a simulation of the generative process of their adaptive structures, capable to inform in many ways human construction. The essay explicates the development of the 3-dimensional, agent-based simulation of the termite collective construction and analyzes the results, which involve besides physical modelling of the evolved structures. It finally elucidates the potential of this emerging and adaptive architectural performance to be translated to human practice and thus enlighten new ecological engineering and design methodologies

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

A Distributed Computing Architecture for the Large-Scale Integration of Renewable Energy and Distributed Resources in Smart Grids

We present a distributed computing architecture for smart grid management, composed of two applications at two different levels of the grid. At the high voltage level, we optimize operations using a stochastic unit commitment (SUC) model with hybrid time resolution. The SUC problem is solved with an asynchronous distributed subgradient method, for which we propose stepsize scaling and fast initialization techniques. The asynchronous algorithm is implemented in a high-performance computing cluster and benchmarked against a deterministic unit commitment model with exogenous reserve targets in an industrial scale test case of the Central Western European system (679 buses, 1037 lines, and 656 generators). At the distribution network level, we manage demand response from small clients through distributed stochastic control, which enables harnessing residential demand response while respecting the desire of consumers for control, privacy, and simplicity. The distributed stochastic control scheme is successfully tested on a test case with 10,000 controllable devices. Both applications demonstrate the potential for efficiently managing flexible resources in smart grids and for systematically coping with the uncertainty and variability introduced by renewable energy

Decentralized Coalition Formation with Agent-based Combinatorial Heuristics

A steadily growing pervasion of the energy distribution grid with communication technology is widely seen as an enabler for new computational coordination techniques for renewable, distributed generation as well as for bundling with controllable consumers. Smart markets will foster a decentralized grid management. One important task as prerequisite to decentralized management is the ability to group together in order to jointly gain enough suitable flexibility and capacity to assume responsibility for a specific control task in the grid. In self-organized smart grid scenarios, grouping or coalition formation has to be achieved in a decentralized and situation aware way based on individual capabilities. We present a fully decentralized coalition formation approach based on an established agent-based heuristics for predictive scheduling with the additional advantage of keeping all information about local decision base and local operational constraints private. Two closely interlocked optimization processes orchestrate an overall procedure that adapts a coalition structure to best suit a given set of energy products. The approach is evaluated in several simulation scenarios with different type of established models for integrating distributed energy resources and is also extended to the induced use case of surplus distribution using basically the same algorithm

Integrating Wind Power into the Danish Electricity System

The present study involves an inquiry into the making of a Danish energy system based on renewable energy sources. Focusing specifically on one of the major barriers to the introduction of renewable energy sources known as the intermittency problem, emphasis is put on how fluctuating electricity generation from wind turbines has been integrated into the Danish electricity system. The study focuses on the ways in which the integration of wind power in Denmark has involved the introduction and reconfiguration of a series electricity markets known as Nord Pool. Significantly, these electricity markets are engineered as control arrangements for electricity system equilibrium maintenance. When attempting to integrate wind power into the Danish electricity system by introducing or reconfiguring these control system market arrangements, metrics from economics are used to describe the ideal outcome or objective to be attained through market construction. Coupling these empirical observations with a line of inquiry concentrating on the use of knowledge, skills, and know-how in market design and management associated with the ‘performativity programme’ in the social and human sciences and especially economic sociology the thesis is framed by the following research question: How have control systems engineering and economics been mobilized in the endeavor to integrate wind power into the Danish electricity system through electricity market design and management? Answering this research question involves an analysis of three different instances of electricity market construction. All three cases demonstrate how integrating wind power into the Danish electricity system has been approached as a matter of electricity market construction increasing the capacity of Nord Pool to exert control and maintain equilibrium in the electricity system. In addition to producing insights into how the intermittency problem is being handled in Denmark, the present study seeks to augment the performativity programme in two ways. One way is to show how control systems engineering, being an understudied form of expertise within the performativity programme, has played a crucial role in the design and management of a series of markets. The other is to show how economics, being a form of expertise studied extensively by the members of the performativity programme in other empirical settings, has had heretofore undescribed functions in market design and management

Smart meters adoption: recent advances and future trends

High growth in electricity demand and peaks in the load curve, caused mainly by households, require big investments in infrastructure that are used for short periods. Because of this, it is necessary to look for new developments that allow meeting the needs of users as well as using the electricity system resources efficiently. This is possible through the Smart Grid (SG), which additionally allows users to have autonomy in the electricity supply chain. Our focus of investigation is with households because they can monitor their demand and help to reduce the peaks of the load curve. To do this, users must use Smart Meters, because these devices allow consumers to obtain the information necessary to control their demand. This paper presents a systematic analysis of published literature related to the study of the SG from the demand side, analyses the current situation of this topic and the impact of Smart Meter penetration in households