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Shaun Sweeney

Publications and source records attributed to Shaun Sweeney.

6 recordsLinked to original sources

Stateful Pricing and Allocation for Repeated Constrained DER Coordination in Distribution Networks

Distribution networks with high penetrations of distributed energy resources (DERs) must repeatedly allocate limited network capability in two directions: under import scarcity, which flexible demand is served, and under export congestion, which generation is curtailed. Dynamic operating envelopes (DOEs) enforce hard feasibility bounds but lack intertemporal correction, while dynamic network prices (DNPs) provide an allocative signal but cannot guarantee constraint satisfaction. This paper develops a stateful cyber-physical coordination mechanism, termed an Automatic Market Maker (AMM), as an additive coordination layer for machine-to-machine DER access. The mechanism combines dual fairness states for import and export, bounded bilateral prices driven by a voltage-aware deficit signal, and feasibility-constrained matching within a two-tier MV/LV architecture. Experiments on the CSIRO MV+33LV feeder dataset compare five mechanisms and benchmark the fair-over-time DOE formulations of Moring et al. (FET, FOT, FUH). Relative to equal-allocation DOE, the AMM reduces unserved flexible demand by 76% (96.0 MWh to 23.2 MWh) with zero thermal violations and reduces export curtailment from 85.4 MWh to 64.5 MWh. Near-identical DOE and DOE-GREEDY performance confirms that heuristic choice alone does not improve repeated constrained outcomes. The AMM reaches an annual inter-feeder Jain index of 0.9998, outperforming all DOE variants from month 6 onwards. Direct benchmarking against FET/FOT/FUH shows that these mechanisms achieve higher worst-feeder equity through an explicit max-min MV objective, but operate offline over predetermined horizons and do not provide bilateral scarcity signals, real-time operation, or participant-level intertemporal correction. The two approaches address different objectives and may be combined in future work.

eess.SY

A Fair, Flexible, Zero-Waste Digital Electricity Market: A First-Principles Approach Combining Automatic Market Making, Holarchic Architectures and Shapley Theory

This thesis presents a fundamental rethink of electricity market design at the wholesale and balancing layers. Rather than treating markets as static spot clearing mechanisms, it reframes them as a continuously online, event driven dynamical control system: a two sided marketplace operating directly on grid physics. Existing energy only, capacity augmented, and zonal market designs are shown to admit no shock robust Nash equilibrium under realistic uncertainty, instead relying on price caps, uplift, and regulatory intervention to preserve solvency and security. In response, the thesis develops a holarchic Automatic Market Maker (AMM) in which prices are bounded, exogenous control signals derived from physical tightness rather than emergent equilibrium outcomes. The AMM generalises nodal and zonal pricing through nested scarcity layers, from node to cluster to zone to region to system, such that participant facing prices inherit from the tightest binding constraint. Nodal and zonal pricing therefore emerge as special cases of a unified scarcity propagation rule. Beyond pricing, the AMM functions as a scarcity aware control system and a digitally enforceable rulebook for fair access and proportional allocation under shortage. Fuel costs are recovered through pay as bid energy dispatch consistent with merit order, while non fuel operating and capital costs are allocated according to adequacy, flexibility, and locational contribution. Large scale simulations demonstrate bounded input bounded output stability, controllable procurement costs, zero structural waste, and improved distributional outcomes. The architecture is climate aligned and policy configurable, but requires a managed transition and new operational tools for system operators and market participants.

eess.SY

Embracing Fairness in Consumer Electricity Markets using an Automatic Market Maker

As consumer flexibility becomes expected, it is important that the market mechanisms which attain that flexibility are perceived as fair. We set out fairness issues in energy markets today, and propose a market design to address them. Consumption is categorised as either essential or flexible with different prices and reliability levels for each. Prices are generated by an Automatic Market Maker (AMM) based on instantaneous scarcity and resource is allocated using a novel Fair Play algorithm. We empirically show the performance of the system over 1 year for 101 UK households and benchmark its performance against more classical approaches.

eess.SY

A smart electric bike for smart cities

This is a Masters Thesis completed at University College Dublin, Ireland in 2017 which involved augmenting an off-the-shelf electric bike with sensors to enable new services to be delivered to cyclists in cities. The application of primary interest was to control the cyclist's ventilation rate based on the concentration of local air pollutants. Detailed modelling and system design is presented for our Cyberphysical system which consisted of a modified BTwin e-bike, Cycle Analyst sensors, the cyclist themselves, a Bluetooth connected smartphone and our algorithms. Control algorithms to regulate the proportion of power the cyclist provided as a proxy for their ventilation rate were proposed and validated in a basic way, which were later proven significantly further in Further Work (see IEEE Transactions on Intelligent Transportation Systems paper: https://ieeexplore.ieee.org/abstract/document/8357977). The basic idea was to provide more electrical assistance to cyclists in areas of high air pollution to reduce the cyclist ventilation rate and thereby the amount of air pollutants inhaled. This presents an interesting control challenge due to the human-in-the-loop characteristics and the potential for impactful real life applications. A background literature review is provided on energy as it relates to cycling and some other applications are also discussed. A link to a video which demonstrates the system is provided, and also to a blog published by IBM Research about the system.

cs.MA

Pitchfork-bifurication-based competitive and collaborative control of an E-bike system

This paper is concerned with the design of a human-in-the-loop system for deployment on a smart pedelec (e-bike). From the control-theoretic perspective, the goal is not only to use the power assistance of the e-bike to reject disturbances along the route but also to manage the possibly competitive interactions between a human and the motor intervention. Managing the competitive/cooperative nature of the interactions is crucial for applications in which we wish to control physical aspects of the cycling behavior (e.g. heart rate and breathing rate). The basis of the control is a pitchfork bifurcation system, modeling the interactions, augmented using ideas from gain-scheduling. In vivo experiments have been conducted, showing the effectiveness of the proposed control strategy.

math.OC

A context-aware e-bike system to reduce pollution inhalation while cycling

The effect of transport-related pollution on human health is fast becoming recognised as a major issue in cities worldwide. Cyclists, in particular, face great risks, as they typically are most exposed to tail-pipe emissions. Three avenues are being explored worldwide in the fight against urban pollution: (i) outright bans on polluting vehicles and embracing zero tailpipe emission vehicles; (ii) measuring air-quality as a means to better informing citizens of zones of higher pollution; and (iii) developing smart mobility devices that seek to minimize the effect of polluting devices on citizens as they transport goods and individuals in our cities. Following this latter direction, in this paper we present a new way to protect cyclists from the effect of urban pollution. Namely, by exploiting the actuation possibilities afforded by pedelecs or e-bikes (electric bikes), we design a cyber-physical system that mitigates the effect of urban pollution by indirectly controlling the breathing rate of cyclists in polluted areas. Results from a real device are presented to illustrate the efficacy of our system.

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