Orchid Project

Smart Grid

Smart GridDeveloping a modern electricity grid where information flows in both directions between consumers and producers is critical to achieving the UK’s ambitious carbon reduction targets. Human-agent collectives are an essential part of this vision, and we are seeking to develop agents (or ‘energy avatars’) that are capable of continuously monitoring, predicting and feeding back information about energy generation and consumption within the grid, in order to satisfy individuals’ preferences for cost, carbon and comfort.

To address these aims we are developing (i) coalition formation algorithms that allow multiple self-interested parties such as renewable generators to come together with consumers to create virtual power plants that can more effectively manage the intermittent nature of these energy sources and (ii) algorithms to generate effective short term predictions of demand and supply to allow the optimisation of energy use.

Learn more about Smart Grid Technologies

Smart Grid Management in 2050 vignette

It is 2050 and anthropogenic global warming is both a well established scientific fact and an observable phenomenon to billions of people worldwide. Under the UN Framework Convention on Climate Change, the 2040 Beijing Protocol has just been ratified. This subjects all countries that have not yet achieved an 80% reduction in CO2 emissions (compared to 1990 values) to economic penalties and is severely curtailing the burning of fossil fuels. Electricity in the UK is generated from an ageing fleet of nuclear power stations,from solar farms in the South of Spain and in North-African deserts, from offshore wind farms around the coast and from micro-renewable sources (solar PV, tidal and wind) deployed across the country with the majority of homes being able to export electricity back to the grid. Heating in houses and commercial buildings is increasingly electrified through the use of ground and air source heat pumps (with biogas making up the shortfall) and transport is almost completely electrified after the peak in worldwide oil production in 2030 saw oil prices soar to $500 per barrel.


 

Due to this increased demand for electricity and the variable nature of renewable energy sources used to generate it, there is barely enough electricity to satisfy demand at all times. The energy profligacy of the first decade of the century is a distant memory and energy is a scarce resource. There are regular rolling blackouts as the grid fails to meet demand at different periods of the day. In particular, at times when there is less wind around the UK and increased cloud cover over southern Spain, grid operators rely on ageing gas-fired power stations that incur economic penalties that are passed directly to customers, leading to rising consumer dissatisfaction. To make matters worse, electric vehicles are putting unexpected loads on the grid, whose fundamental infrastructure was designed to feed energy from a small number of generators to a large number of consumers. In particular, as consumers charge their cars at their workplace, transmission lines delivering electricity often reach their thermal limits and eventually trip transformers, leaving consumers stranded with their disabled vehicles.

All houses are now equipped with smart meters and electricity is charged in real time, with feedback about home owners’ use of rooms and activities being used to produce real-time estimates of future demand. However, consumer protection agencies are increasingly concerned about the privacy and rights of users and are protesting against the invasive use of these meters and the ways in which energy suppliers are attempting to influence the consumer behaviour by imposing excessively severe, and unannounced, critical pricing periods. In response, many consumers are simply downloading code and ’hacking’ their meters (easily done since the national rollout of smart meters was completed in 2020 and the security features incorporated in these meters are now trivial to break) in order to subvert the pricing policies of the energy suppliers.

It is this dystopian vision of a future energy scenario that we hope to mitigate through the development of HACs within ORCHID. By building systems in which energy users and producers can coordinate and cooperate we hope to avoid blackouts by appropriately prioritising and scheduling energy use and production within the network. By devolving this coordination to agents (or ’energy avatars’ ) that are capable of continuous monitoring, predicting and feeding back information about energy generation and consumption, the individual preferences of both energy consumers and energy suppliers will be better satisfied.

Flexible Autonomy

Consumers, suppliers and grid operators need to work closely with a variety of computational agents. At the consumer level, people may allow software agents to manage energy usage in their house (e.g. through deferment of loads and storing electricity) and the purchase of short-term dynamically negotiated energy contracts from the grid. At the supplier and grid operator levels, agents will be responsible for trading energy in spot markets and identifying and correcting network faults respectively. This requires both humans and agents to have the same understanding of the on-going activities and issues (possibly requiring a dialogue between them or the use of sensors) and will require novel modes of interaction so humans can describe their future activities and desires to the agents. Similarly, when a grid operation agent detects its automated fault correction mechanisms are bringing the network to its stability limits, it may devolve control back to a human operator who will have ultimate responsibility to shed loads to make sure that the system is safe. In both cases the degree of autonomy given to agents needs to be defined, refined according to the prevailing circumstances and tested to evaluate its impact on the lifestyle of the consumer and the economic and system benefits achieved.


Agile Teaming

Given the number of small energy providers there is an opportunity for them to come together to form Virtual Power Plants (VPPs) that can adjust their overall production of electricity to match current demand. Conversely, like-minded consumers may form energy cooperatives to aggregate the demand profiles of their members into a more predictable profile in order to negotiate cheaper electricity. In both cases the formation and on-going operation of such HACs is a major challenge given that interactions in the collective may be affected due to misunderstanding or mistrust and the uncertainty underlying their joint production, or demand, of electricity. This may mean that some VPPs come together for a short period only and then break apart to form other VPPs that better suit demand at other times, Given all the actors in the system are connected through the grid, the behaviour of a given VPP/cooperative is likely to affect the performance of other teams in the system. This interdependence compounds the problem of sharing profits generated by a given team among its members to ensure they stay within the VPP or cooperative.

Incentive Engineering

The scenario highlights the need for reliable data to be provided by the smart meters to predict demand and for incentives to be provided to consumers to influence demand. Consumers also need to be incentivised to inform their smart meter, and hence the grid, of their activities in order to efficiently use energy in the home and allow better prediction of demand. This means consumers should benefit from providing energy suppliers with additional information, rather than being co-opted to do so through closed protocols. This will only work well if the incentives are correctly designed, understood and valued by the consumers. However, consumers may not participate in such exchanges if they do not trust the mechanisms or wish to maintain the privacy of their energy usage. In addition, unless appropriate safeguards are in place, consumers may be enticed to misreport their usage profile in an attempt to join the cheapest cooperatives. Hence there is a clear need to reward truthful revelation and design persuasive technologies to convince consumers to relinquish at least some of their private information and to motivate them to change their behaviour.

Accountable Information Infrastructure

Information about possible changes in demand and supply at different points in the grid, as well as the thermal state of transmission lines, needs to be aggregated by grid operators to guarantee that energy delivery is secured. This requires both metering of specific points in the network and collecting consumer usage profiles. This represents a large amount of real-time data that may be corrupted, delayed or lost in transmission, incomplete due to consumers’ privacy restrictions or the target of a potential cyber-attack. Critical decisions are likely to be made on the basis of this information, so it is important that there is an auditable trail of all decisions made within the system to maintain the accountability of the system and to ensure humans can trust their agents. Computationally efficient techniques are required to search, store and make inferences over such large amounts of incomplete and possibly incorrect data and to ensure that the output of situational awareness process is robust to misrepresentations by certain actors. The information provided to users on their smart meters will need to be proven to come from trustworthy sources in order to be credible and auditable for billing purposes. This information will also need to be easily understandable and verifiable by home owners.

agents | citizen-science | applications | crowdsourcing | disaster response | smart grid | accountable information architecture |agent-based computing | agile teaming | disaster recovery |flexible autonomy | decentralised control | energy management |HACs | human-agent interaction |human computer interaction | human agent collectives | incentive engineering | machine learning |mechanism design | ORCHID |

 

Related publications

  • Alan, A., Shann, M., Costanza, E., Ramchurn, S. D., & Seuken, S. (2016). It is too hot: an in-situ study of three designs for heating. In CHI 2016. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid254,
      booktitle = {CHI 2016},
      title = {It is too hot: an in-situ study of three designs for heating },
      author = {Alper Alan and Mike Shann and Enrico Costanza and Sarvapali D Ramchurn and Sven Seuken},
      year = {2016},
      keywords = {Energy Management, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/254/1/proceedings.pdf} }
  • Stein, S., Gerding, E. H., Nadea, A., Rosenfeld, A., & Jennings, N. R. (2016). Bid2Charge: Market user interface design for electric vehicle charging. In AAMAS 16: 15th Int. Conf. on Autonomous Agents and Multi-Agent Systems. Get Bibtex Citation
    @inproceedings{
      orchid257,
      booktitle = {AAMAS 16: 15th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
      title = {Bid2Charge: Market user interface design for electric vehicle charging},
      author = {Sebastian Stein and Enrico H Gerding and A Nadea and Avi Rosenfeld and Nicholas R Jennings},
      year = {2016},
    keywords = {Energy Management, Human-Agent Interaction, Applications, Incentive Engineering} }
  • de Weerdt, M., Stein, S., Gerding, E. H., Robu, V., & Jennings, N. R. (2016). Intention-aware routing of electric vehicles. IEEE Transactions on Intelligent Transportation Systems, 1-11. Get Bibtex Citation
    @article{
      orchid252,
      title = {Intention-aware routing of electric vehicles },
      author = {M de Weerdt and Sebastian Stein and Enrico H Gerding and Valentin Robu and Nicholas R Jennings},
      year = {2016},
      pages = {1--11},
      journal = {IEEE Transactions on Intelligent Transportation Systems},
    keywords = {Energy Management, Mechanism Design, Machine Learning, Incentive Engineering} }
  • Alan, A., Costanza, E., Ramchurn, S. D., Fischer, J. E., Rodden, T., & Jennings, N. R. (2015). Managing energy tariffs with agents: a field study of a future smart energy system at home.. In The 1st International Workshop on Smart Cities: People, Technology and Data. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid233,
      booktitle = {The 1st International Workshop on Smart Cities: People, Technology and Data},
      title = {Managing energy tariffs with agents: a field study of a future smart energy system at home.},
      author = {Alper Alan and Enrico Costanza and Sarvapali D Ramchurn and J.E. Fischer and T Rodden and Nicholas R Jennings},
      year = {2015},
      keywords = {Energy Management, Human-Computer Interaction, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/233/1/alan.pdf} }
  • Bistaffa, F., Farinelli, A., & Ramchurn, S. D. (2015). Sharing Rides with Friends: a Coalition Formation Algorithm for Ridesharing. In AAAI-15: Twenty-Ninth Conference on Artificial Intelligence. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid220,
      booktitle = {AAAI-15: Twenty-Ninth Conference on Artificial Intelligence},
      title = {Sharing Rides with Friends: a Coalition Formation Algorithm for Ridesharing},
      author = {Filippo Bistaffa and Alessandro Farinelli and Sarvapali D Ramchurn},
      year = {2015},
      keywords = {Energy Management, Mechanism Design, Incentive Engineering},
    howpublished = {http://www.orchid.ac.uk/eprints/220/1/aaai2015.pdf} }
  • Ghosh, S., Reece, S., Rogers, A., Roberts, S. J., Malibari, A., & Jennings, N. R. (2015). Modelling the thermal dynamics of buildings: a latent force model based approach. ACM Transactions on Intelligent Systems and Technology, 6(1), 1-27. Get Bibtex Citation Download as PDF
    @article{
      orchid234,
      volume = {6},
      number = {1},
      title = {Modelling the thermal dynamics of buildings: a latent force model based approach},
      author = {Siddhartha Ghosh and Steven Reece and Alex Rogers and Stephen J Roberts and Areej Malibari and Nicholas R Jennings},
      year = {2015},
      pages = {1--27},
      journal = {ACM Transactions on Intelligent Systems and Technology},
      keywords = {Energy Management, Mechanism Design, Machine Learning, Agile Teaming, Incentive Engineering},
    howpublished = {http://www.orchid.ac.uk/eprints/234/1/Modelling%2520the%2520Thermal%2520Dynamics%2520of%2520Buildings%2520-%2520A%2520Latent%2520Force%2520Model%2520Based%2520Approach.pdf} }
  • Holyhead, J., Ramchurn, S. D., & Rogers, A. (2015). Consumer targeting in residential demand response programmes. In ACM International Conference on Future Energy Systems. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid240,
      booktitle = {ACM International Conference on Future Energy Systems},
      title = {Consumer targeting in residential demand response programmes },
      author = {James Holyhead and Sarvapali D Ramchurn and Alex Rogers},
      year = {2015},
      keywords = {Energy Management, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/240/1/eEnergy2015%5fprePrint.pdf} }
  • Panagopoulos, A. A., Alam, M., Rogers, A., & Jennings, N. R. (2015). ADA-HEAT: A general adaptive intelligent agent for domestic heating control. In AAMAS-15 : 14th Int. Conf. on Autonomous Agents and Multi-Agent Systems. Get Bibtex Citation
    @inproceedings{
      orchid228,
      booktitle = {AAMAS-15 : 14th Int. Conf. on Autonomous Agents and Multi-Agent Systems },
      title = {ADA-HEAT: A general adaptive intelligent agent for domestic heating control},
      author = {Athanasios Aris Panagopoulos and Moody Alam and Alex Rogers and Nicholas R Jennings},
      year = {2015},
    keywords = {Energy Management, Human-Agent Interaction, Applications, Agile Teaming} }
  • Panagopoulos, A. A., Chalkiadakis, G., & Jennings, N. R. (2015). Towards optimal solar tracking: a dynamic programming approach.. In AAAI-15: Twenty-Ninth Conference on Artificial Intelligence. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid218,
      booktitle = {AAAI-15: Twenty-Ninth Conference on Artificial Intelligence},
      title = {Towards optimal solar tracking: a dynamic programming approach. },
      author = {Athanasios Aris Panagopoulos and G Chalkiadakis and Nicholas R Jennings},
      year = {2015},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/218/1/pcj2014.pdf} }
  • Parson, O., Ghosh, S., Weal, M., & Rogers, A. (2014). An Unsupervised Training Method for Non-intrusive Appliance Load Monitoring. Artificial Intelligence(217), 1-19. Get Bibtex Citation Download as PDF
    @article{
      orchid204,
      number = {217},
      month = {August},
      title = {An Unsupervised Training Method for Non-intrusive Appliance Load Monitoring},
      author = {Oliver Parson and Siddhartha Ghosh and Mark Weal and Alex Rogers},
      year = {2014},
      pages = {1--19},
      journal = {Artificial Intelligence},
      keywords = {Energy Management, Applications, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/204/1/nialm-aij.pdf} }
  • Alam, M., Panagopoulos, A. A., Rogers, A., Jennings, N. R., & Scott, J. (2014). Applying Extended Kalman Filters to Adaptive Thermal Modelling in Homes. In ACM BuildSys 2014. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid244,
      booktitle = {ACM BuildSys 2014},
      title = {Applying Extended Kalman Filters to Adaptive Thermal Modelling in Homes},
      author = {Moody Alam and Athanasios Aris Panagopoulos and Alex Rogers and Nicholas R Jennings and James Scott},
      year = {2014},
      keywords = {Energy Management, Applications, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/244/1/Alam-Final.pdf} }
  • Alan, A., Costanza, E., Fischer, J. E., Ramchurn, S. D., Rodden, T., & Jennings, N. R. (2014). A field study of human-agent interaction for electricity tariff switching. In 13th Int. Conf. on Autonomous Agents and Multi-Agent Systems. Get Bibtex Citation
    @inproceedings{
      orchid171,
      booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
      title = {A field study of human-agent interaction for electricity tariff switching},
      author = {Alper Alan and Enrico Costanza and J.E. Fischer and Sarvapali D Ramchurn and T Rodden and Nicholas R Jennings},
      year = {2014},
    keywords = {Energy Management, Agile Teaming} }
  • Batra, N., Kelly, J., Parson, O., Dutta, H., Knottenbelt, W., & Rogers, A., et al. (2014). NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring. In International Conference on Future Energy Systems (ACM e-Energy). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid223,
      booktitle = { International Conference on Future Energy Systems (ACM e-Energy)},
      title = {NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring },
      author = {Nipun Batra and Jack Kelly and Oliver Parson and Haimonti Dutta and William Knottenbelt and Alex Rogers and Amarjeet Singh and Mani Srivastava},
      year = {2014},
      keywords = {Energy Management, Applications, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/223/1/NILMTK.pdf} }
  • Costanza, E., Fischer, J. E., Colley, J., Rodden, T., Ramchurn, S. D., & Jennings, N. R. (2014). Doing the Laundry with Agents: a Field Trial of a Future Smart Energy System in the Home.. In ACM CHI 2014. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid181,
      booktitle = {ACM CHI 2014},
      title = {Doing the Laundry with Agents: a Field Trial of a Future Smart Energy System in the Home.},
      author = {Enrico Costanza and J.E. Fischer and J Colley and T Rodden and Sarvapali D Ramchurn and Nicholas R Jennings},
      year = {2014},
      keywords = {Energy Management, Human-Agent Interaction, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/181/1/battery%25202.2%5fb%5fauthor.pdf} }
  • Farinelli, A., Rogers, A., & Jennings, N. R. (2014). Agent-based decentralised coordination for sensor networks using the max-sum algorithm. Journal of Autonomous Agents and Multi-Agent Systems, 28(3), 337-380. Get Bibtex Citation Download as PDF
    @article{
      orchid224,
      volume = {28},
      number = {3},
      title = {Agent-based decentralised coordination for sensor networks using the max-sum algorithm. },
      author = {Alessandro Farinelli and Alex Rogers and Nicholas R Jennings},
      year = {2014},
      pages = {337--380},
      journal = {Journal of Autonomous Agents and Multi-Agent Systems},
      keywords = {Decentralised Control, Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/224/1/main.pdf} }
  • Fischer, J. E., Costanza, E., Ramchurn, S. D., Colley, J., & Rodden, T. (2014). Energy Advisors at Work: Charity Work Practices to Support People in Fuel Poverty. In ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ?14). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid205,
      booktitle = {ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ?14).},
      title = {Energy Advisors at Work: Charity Work Practices to Support People in Fuel Poverty},
      author = {J.E. Fischer and Enrico Costanza and Sarvapali D Ramchurn and J Colley and T Rodden},
      year = {2014},
      keywords = {Energy Management, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/205/1/UbiComp2014%5fEnergy-Advisors-at-Work%5fauthor-version.pdf} }
  • Jennings, N. R., Moreau, L., Nicholson, D., Ramchurn, S. D., Roberts, S. J., Rodden, T., & Rogers, A. (2014). On human-agent collectives. Communications of the ACM. Get Bibtex Citation Download as PDF
    @article{
      orchid198,
      title = {On human-agent collectives},
      author = {Nicholas R Jennings and Luc Moreau and David Nicholson and Sarvapali D Ramchurn and Stephen J Roberts and T Rodden and Alex Rogers},
      year = {2014},
      journal = {Communications of the ACM },
      keywords = {Agent-based Computing, Crowd-sourcing, Disaster Recovery, Energy Management, Human Computation, Provenance, Ubiquitous Computing, Accountable Information Infrastructure, Applications, Agile Teaming, Flexible Autonomy, Incentive Engineering},
    howpublished = {http://www.orchid.ac.uk/eprints/198/1/CACM%2520HAC%2520ARTICLE%2520%2520final.pdf} }
  • Vinyals, M., Robu, V., Rogers, A., & Jennings, N. R. (2014). Prediction-of-use games: a cooperative game theory approach to sustainable energy tariffs. In 13th Int. Conf. on Autonomous Agents and Multi-Agent Systems. Get Bibtex Citation
    @inproceedings{
      orchid170,
      booktitle = {13th Int. Conf. on Autonomous Agents and Multi-Agent Systems},
      title = {Prediction-of-use games: a cooperative game theory approach to sustainable energy tariffs},
      author = {Meritxell Vinyals and Valentin Robu and Alex Rogers and Nicholas R Jennings},
      year = {2014},
    keywords = {Energy Management, Agile Teaming} }
  • Alam, M., Ramchurn, S. D., & Rogers, A. (2013). Cooperative energy exchange for the efficient use of energy and resources in remote communities.. In Autonomous Agents and Multiagent Systems (AAMAS) Conference. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid129,
      booktitle = {Autonomous Agents and Multiagent Systems (AAMAS) Conference },
      title = {Cooperative energy exchange for the efficient use of energy and resources in remote communities.},
      author = {Moody Alam and Sarvapali D Ramchurn and Alex Rogers},
      year = {2013},
      pages = {731--738},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/129/1/aamas467-alam.pdf} }
  • Alam, M., Rogers, A., & Ramchurn, S. D. (2013). Interdependent multi-issue negotiation for energy exchange in remote communities.. In Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid130,
      booktitle = {Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13)},
      title = {Interdependent multi-issue negotiation for energy exchange in remote communities.},
      author = {Moody Alam and Alex Rogers and Sarvapali D Ramchurn},
      year = {2013},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/130/1/alam-186.pdf} }
  • Fischer, J. E., Costanza, E., Ramchurn, S. D., Rogers, A., & Rodden, T. (2013). Fuel Poverty and the Work of Energy Advisors. In DE2013: Open Digital ? The Fourth Annual Digital Economy All Hands Meeting. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid206,
      booktitle = {DE2013: Open Digital ? The Fourth Annual Digital Economy All Hands Meeting},
      title = {Fuel Poverty and the Work of Energy Advisors},
      author = {J.E. Fischer and Enrico Costanza and Sarvapali D Ramchurn and Alex Rogers and T Rodden},
      year = {2013},
      keywords = {Energy Management, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/206/1/de2013%5fsubmission%5f66.pdf} }
  • Fischer, J. E., Ramchurn, S. D., Osborne, M. A., Parson, O., Huynh, D. T., & Alam, M., et al. (2013). Recommending energy tariffs and load shifting based on smart household usage profiling. In International Conference on Intelligent User Interfaces. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid98,
      booktitle = {International Conference on Intelligent User Interfaces },
      title = {Recommending energy tariffs and load shifting based on smart household usage profiling},
      author = {J.E. Fischer and Sarvapali D Ramchurn and Michael A Osborne and Oliver Parson and T. Dong Huynh and Moody Alam and N Pantidi and Stuart Moran and Khaled Bachour and Steven Reece and Enrico Costanza and T Rodden and Nicholas R Jennings},
      year = {2013},
      pages = {383--394},
      keywords = {Energy Management, Accountable Information Infrastructure, Applications, Agile Teaming, Flexible Autonomy},
    howpublished = {http://www.orchid.ac.uk/eprints/98/1/IUI2013-agentswitch-camera-ready.pdf} }
  • Gerding, E. H., Stein, S., Robu, V., Zhao, D., & Jennings, N. R. (2013). Two-sided online markets for electric vehicle charging. In 12th Int. Conf on Autonomous Agents and Multi-Agent Systems. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid97,
      booktitle = {12th Int. Conf on Autonomous Agents and Multi-Agent Systems},
      title = {Two-sided online markets for electric vehicle charging},
      author = {Enrico H Gerding and Sebastian Stein and Valentin Robu and D Zhao and Nicholas R Jennings},
      year = {2013},
      pages = {989--996},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/97/1/fp488-gerding-eprints.pdf} }
  • Ramchurn, S. D., Osborne, M. A., Parson, O., Rahwan, T., Maleki, S., & Reece, S., et al. (2013). AgentSwitch: towards smart electricity tariff selection. In 12th Int. Conf on Autonomous Agents and Multi-Agent Systems. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid179,
      booktitle = {12th Int. Conf on Autonomous Agents and Multi-Agent Systems},
      title = {AgentSwitch: towards smart electricity tariff selection },
      author = {Sarvapali D Ramchurn and Michael A Osborne and Oliver Parson and Talal Rahwan and Sasan Maleki and Steven Reece and T. Dong Huynh and Moody Alam and J.E. Fischer and T Rodden and Luc Moreau and Stephen J Roberts},
      year = {2013},
      pages = {981--988},
      keywords = {Energy Management, Applications},
    howpublished = {http://www.orchid.ac.uk/eprints/179/1/fp454s-ramchurn.pdf} }
  • Rodden, T., Fischer, J. E., Pantidi, N., Bachour, K., & Moran, S. (2013). At Home with Agents: Exploring Attitudes Towards Future Smart Energy Infrastructures. In SIGCHI Conference on Human Factors in Computing Systems. Get Bibtex Citation
    @inproceedings{
      orchid106,
      booktitle = {SIGCHI Conference on Human Factors in Computing Systems},
      title = {At Home with Agents: Exploring Attitudes Towards Future Smart Energy Infrastructures},
      author = {T Rodden and J.E. Fischer and N Pantidi and Khaled Bachour and Stuart Moran},
      year = {2013},
      pages = {1173--1182},
    keywords = {Energy Management, Flexible Autonomy} }
  • Rogers, A., Ghosh, S., Wilcock, R., & Jennings, N. R. (2013). A Scalable Low-Cost Solution to Provide Personalised Home Heating Advice to Households. In 5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid177,
      booktitle = {5th ACM Workshop On Embedded Systems For Energy-Efficient Buildings (BuildSys)},
      title = {A Scalable Low-Cost Solution to Provide Personalised Home Heating Advice to Households },
      author = {Alex Rogers and Siddhartha Ghosh and Reuben Wilcock and Nicholas R Jennings},
      year = {2013},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/177/1/01%5fRogers.pdf} }
  • Truong, N. C., McInerney, J., Tran-Thanh, L., Costanza, E., & Ramchurn, S. D. (2013). Forecasting multi-appliance usage for smart home energy management.. In 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid133,
      booktitle = {23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), },
      title = {Forecasting multi-appliance usage for smart home energy management.},
      author = {Ngoc Cuong Truong and James McInerney and Long Tran-Thanh and Enrico Costanza and Sarvapali D Ramchurn},
      year = {2013},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/133/1/ijcai2013%5fcamera.pdf} }
  • Truong, N. C., Tran-Thanh, L., Costanza, E., & Ramchurn, S. D. (2013). Activity prediction for agent-based home energy management.. In Agent Technologies for Energy Systems (ATES 2013). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid134,
      booktitle = {Agent Technologies for Energy Systems (ATES 2013),},
      title = {Activity prediction for agent-based home energy management.},
      author = {Ngoc Cuong Truong and Long Tran-Thanh and Enrico Costanza and Sarvapali D Ramchurn},
      year = {2013},
      keywords = {Energy Management, Human-Agent Interaction, Applications, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/134/1/ates2013.pdf} }
  • Truong, N. C., Tran-Thanh, L., Costanza, E., & Ramchurn, S. D. (2013). Towards appliance usage prediction for home energy management.. In ACM E-Energy 2013. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid135,
      booktitle = {ACM E-Energy 2013},
      title = {Towards appliance usage prediction for home energy management.},
      author = {Ngoc Cuong Truong and Long Tran-Thanh and Enrico Costanza and Sarvapali D Ramchurn},
      year = {2013},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/135/1/e%5fenergy2013.pdf} }
  • Rogers, A., Wilcock, R., Ghosh, S., & Jennings, N. R. (2012). A Scalable Low-Cost Solution to Provide Personalized Home Heating Advice to Households. In BuildSys 2012. Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid87,
      booktitle = {BuildSys 2012},
      month = {November},
      title = {A Scalable Low-Cost Solution to Provide Personalized Home Heating Advice to Households},
      author = {Alex Rogers and Reuben Wilcock and Siddhartha Ghosh and Nicholas R Jennings},
      year = {2012},
      keywords = {Energy Management, Human-Agent Interaction, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/87/1/A%5fScalable%5fLow-Cost%5fSolution%5fto%5fProvide%5fPersonalized%5fHome%5fHeating%5fAdvice%5fto%5fHouseholds.pdf} }
  • Vinyals, M., Bistaffa, A., Farinelli, A., & Rogers, A. (2012). Coalitional Energy Purchasing in the Smart Grid.. In IEEE International Energy Conference & Exhibition (ENERGYCON 2012). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid72,
      booktitle = {IEEE International Energy Conference & Exhibition (ENERGYCON 2012)},
      month = {September},
      title = {Coalitional Energy Purchasing in the Smart Grid. },
      author = {Meritxell Vinyals and A Bistaffa and Alessandro Farinelli and Alex Rogers},
      year = {2012},
      keywords = {Energy Management, Flexible Autonomy},
    howpublished = {http://www.orchid.ac.uk/eprints/72/1/energycon2012.pdf} }
  • Parson, O., Ghosh, S., Weal, M., & Rogers, A. (2012). Non-intrusive load monitoring using prior models of general appliance types. In Twenty-Sixth Conference on Artificial Intelligence (AAAI-12). Get Bibtex Citation Download as PDF
    @inproceedings{
      orchid49,
      booktitle = {Twenty-Sixth Conference on Artificial Intelligence (AAAI-12)},
      month = {July},
      title = {Non-intrusive load monitoring using prior models of general appliance types},
      author = {Oliver Parson and Siddhartha Ghosh and Mark Weal and Alex Rogers},
      year = {2012},
      keywords = {Energy Management, Machine Learning, Applications, Agile Teaming},
      howpublished = {http://www.orchid.ac.uk/eprints/49/1/nialm.pdf},
    abstract = {Non-intrusive appliance load monitoring is the process of disaggregating a household's total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances can be iteratively separated from an aggregate load. Unlike existing approaches, our approach does not require training data to be collected by sub-metering individual appliances, nor does it assume complete knowledge of the appliances present in the household. Instead, we propose an approach in which prior models of general appliance types are tuned to specific appliance instances using only signatures extracted from the aggregate load. The tuned appliance models are then used to estimate each appliance's load, which is subsequently subtracted from the aggregate load. This process is applied iteratively until all appliances for which prior behaviour models are known have been disaggregated. We evaluate the accuracy of our approach using the REDD data set, and show the disaggregation performance when using our training approach is comparable to when sub-metered training data is used. We also present a deployment of our system as a live application and demonstrate the potential for personalised energy saving feedback.} }
  • Vinyals, M., Bistaffa, A., Farinelli, A., & Rogers, A. (2012). Decentralised stable coalition formation among energy consumers in the Smart grid (Demonstration). Proceedings of the 11th International Conference on Autonomous Agents and MultiAgent Systems. Get Bibtex Citation Download as PDF
    @article{
      orchid74,
      month = {June},
      title = {Decentralised stable coalition formation among energy consumers in the Smart grid (Demonstration)},
      author = {Meritxell Vinyals and A Bistaffa and Alessandro Farinelli and Alex Rogers},
      year = {2012},
      journal = {Proceedings of the 11th International Conference on Autonomous Agents and MultiAgent Systems},
      keywords = {Energy Management, Flexible Autonomy},
    howpublished = {http://www.orchid.ac.uk/eprints/74/1/aamas2012%5fdemo%5fscf.pdf} }
  • Vinyals, M., Bistaffa, A., Farinelli, A., & Rogers, A. (2012). Stable Coalition formation among energy consumers in the Smart Grid. Proceedings of the 3th International Workshop on Agent Technologies for Energy Systems (ATES 2012), 73-80. Get Bibtex Citation Download as PDF
    @article{
      orchid73,
      month = {June},
      title = {Stable Coalition formation among energy consumers in the Smart Grid},
      author = {Meritxell Vinyals and A Bistaffa and Alessandro Farinelli and Alex Rogers},
      year = {2012},
      pages = {73--80},
      journal = {Proceedings of the 3th International Workshop on Agent Technologies for Energy Systems (ATES 2012)},
      keywords = {Energy Management, Flexible Autonomy},
    howpublished = {http://www.orchid.ac.uk/eprints/73/1/ates%5f2012.pdf} }
  • Ramchurn, S. D., Vytelingum, P., Rogers, A., & Jennings, N. R. (2012). Putting the "Smarts" into the Smart Grid: A Grand Challenge for Artificial Intelligence. Communications of the ACM, 55(4), 86-97. Get Bibtex Citation Download as PDF
    @article{
      orchid88,
      volume = {55},
      number = {4},
      title = {Putting the "Smarts" into the Smart Grid: A Grand Challenge for Artificial Intelligence.},
      author = {Sarvapali D Ramchurn and Perukrishnen Vytelingum and Alex Rogers and Nicholas R Jennings},
      year = {2012},
      pages = {86--97},
      journal = {Communications of the ACM},
      keywords = {Energy Management, Agile Teaming},
    howpublished = {http://www.orchid.ac.uk/eprints/88/1/ramchurn%5fetal%5fsmart%5fgrid.pdf} }
  • Parson, O., Ghosh, S., Weal, M., & Rogers, A. (2011). Using hidden Markov models for iterative non-intrusive appliance monitoring. Neural Information Processing Systems workshop on Machine Learning for Sustainability. Get Bibtex Citation Download as PDF
    @article{
      orchid43,
      title = {Using hidden Markov models for iterative non-intrusive appliance monitoring.},
      author = {Oliver Parson and Siddhartha Ghosh and M Weal and Alex Rogers},
      publisher = {NIPS},
      year = {2011},
      journal = {Neural Information Processing Systems workshop on Machine Learning for Sustainability},
      keywords = {Energy Management, Machine Learning, Applications, Flexible Autonomy},
    howpublished = {http://www.orchid.ac.uk/eprints/43/1/MLSUST2011.pdf} }

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