All Outputs (73)

The role of ‘living laboratories’ in accelerating the energy system decarbonization (2022)
Journal Article

To decarbonize the energy system by the year 2050, it is crucial that innovations are trialled in a ‘real world’ setting for the purpose of increasing public adoption and support, and for providing insights to decision-makers to ensure their decision... Read More about The role of ‘living laboratories’ in accelerating the energy system decarbonization.

Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning (2022)
Journal Article

To reduce global greenhouse gas emissions, the world must find intelligent solutions to maximise the utilisation of carbon-free renewable energy sources. In this paper, multi-agent reinforcement learning is used to control a microgrid in a mixed coop... Read More about Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning.

Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints (2022)
Journal Article

In this paper, we investigate an energy cost minimization problem for prosumers participating in peer-to-peer energy trading. Due to (i) uncertainties caused by renewable energy generation and consumption, (ii) difficulties in developing an accurate... Read More about Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints.

Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning (2022)
Journal Article

As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy. In this paper, the model-free deep reinforcement learning algorithm Rainbow Deep Q-Networks is used to control a battery... Read More about Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning.

Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters (2021)
Presentation / Conference

In this proposal paper we highlight the need for privacy preserving energy demand forecasting to allay a major concern consumers have about smart meter installations. High resolution smart meter data can expose many private aspects of a consumer's ho... Read More about Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters.

Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints (2021)
Journal Article

In this paper, we investigate an energy cost minimization problem for prosumers participating in peer-to-peer energy trading. Due to (i) uncertainties caused by renewable energy generation and consumption, (ii) difficulties in developing an accurate... Read More about Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints.

A Review of Privacy-preserving Federated Learning for the Internet-of-Things (2021)
Book Chapter

The Internet-of-Things (IoT) generates vast quantities of data, much of it attributable to individuals' activity and behaviour. Gathering personal data and performing machine learning tasks on this data in a central location presents a significant pr... Read More about A Review of Privacy-preserving Federated Learning for the Internet-of-Things.

Federated learning with hierarchical clustering of local updates to improve training on non-IID data (2020)
Journal Article

Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion -- as is typi... Read More about Federated learning with hierarchical clustering of local updates to improve training on non-IID data.

Digital Twin: Enabling Technologies, Challenges and Open Research (2020)
Journal Article

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry... Read More about Digital Twin: Enabling Technologies, Challenges and Open Research.

A Decade On, How Has the Visibility of Energy Changed? Energy Feedback Perceptions from UK Focus Groups (2020)
Journal Article

The Smart Meter Rollout Programme in the UK has required energy suppliers to offer new smart meters to customers to provide near real-time energy use information and enable two-way communication between the meter and the central system. The provision... Read More about A Decade On, How Has the Visibility of Energy Changed? Energy Feedback Perceptions from UK Focus Groups.

Visualising the Invisible: Augmented Reality and Virtual Reality as Persuasive Technologies for Energy Feedback (2020)
Conference Proceeding

In the last fifteen years, the outlook for engaging direct energy feedback as a method of effectively curtailing domestic energy consumption has grown more pessimistic. Continuing studies and reviews suggest the impact of such techniques on consumers... Read More about Visualising the Invisible: Augmented Reality and Virtual Reality as Persuasive Technologies for Energy Feedback.

Deep Reinforcement Learning Based Energy Storage Arbitrage With Accurate Lithium-ion Battery Degradation Model (2020)
Journal Article

Accurate estimation of battery degradation cost is one of the main barriers for battery participating on the energy arbitrage market. This paper addresses this problem by using a model-free deep reinforcement learning (DRL) method to optimize the bat... Read More about Deep Reinforcement Learning Based Energy Storage Arbitrage With Accurate Lithium-ion Battery Degradation Model.

Smart world systems, applications, and technologies (2020)
Journal Article

Cell equalisation circuits: A review (2020)
Journal Article

Large Li-ion battery packs are an enabling technology for electric vehicles, smart homes and the smart grid. Keeping the individual cells that make up the battery pack balanced reduces the loss of capacity over time and reduces the chances of damagin... Read More about Cell equalisation circuits: A review.

Anomaly Detection for IoT Time-Series Data: A Survey (2019)
Journal Article

Abstract—Anomaly detection is a problem with applications for a wide variety of domains, it involves the identification of novel or unexpected observations or sequences within the data being captured. The majority of current anomaly detection method... Read More about Anomaly Detection for IoT Time-Series Data: A Survey.

Optimal Design and Operation of a Low Carbon Community based Multi-energy Systems Considering EV Integration (2019)
Journal Article

Hybridization of electricity, heat power and transportation energy combines the advantages of multi-energy sources. This paper proposes the combined use of fuel cell, combined heat and power units (CHP), hot water tank storage, gas boiler and photovo... Read More about Optimal Design and Operation of a Low Carbon Community based Multi-energy Systems Considering EV Integration.

Deep Learning-Based Online Small Signal Stability Assessment of Power Systems with Renewable Generation (2018)
Presentation / Conference

Distributed Caching in Wireless Cellular Networks Incorporating Parallel Processing (2018)
Journal Article

Distributed caching is a promising technique for reducing redundant data traffic and user content access delay in telecommunications systems. This article explores caching technologies with a focus on the processing of content requests in today’s hie... Read More about Distributed Caching in Wireless Cellular Networks Incorporating Parallel Processing.

Enhanced Collision Avoidance for Distributed LTE Vehicle to Vehicle Broadcast Communications (2018)
Journal Article

In this letter, we investigate the distributed autonomous resource selection for LTE vehicle to vehicle (V2V) broadcast. The effectiveness of collision avoidance and location based resource allocation enhancements is examined. It is found that collis... Read More about Enhanced Collision Avoidance for Distributed LTE Vehicle to Vehicle Broadcast Communications.

Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks (2017)
Journal Article

The electricity production and distribution is facing two major changes. First, the production is shifting from classical energy sources such as coal and nuclear power towards renewable resources such as solar and wind. Secondly, the consumption in t... Read More about Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks.