Publications by Colin Neil Jones

A multi-modal nocturnal radiative cooling and solar-assisted heating system with model predictive control

Heating and cooling of buildings account for around 15% of all global energy consumption. In light of the ongoing energy transition, we aim to improve the efficiency of both in a European single-family house by using photovoltaic-thermal collectors with a ...

2025

Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

Colin Neil Jones, Yuning Jiang

This paper introduces a distributed operational solution for integrated transmission-distribution (ITD) system management. A fundamental challenge in designing distributed approaches for AC optimal power flow (OPF) problems in ITD systems is the nonconvexi ...

IEEE COMPUTER SOC2025

A commissioning-oriented approach to data-driven modeling of buildings with heat pumps for predictive demand response

Colin Neil Jones

As the share of electricity generation from non-dispatchable sources like wind and photovoltaics grows, so does the need for demand response to stabilize the grid. Since the electricity consumption of heat pumps in buildings is both substantial and flexibl ...

Elsevier BV2025

Adaptive data-driven prediction in a building control hierarchy: A case study of demand response in Switzerland

Christophe Salzmann, Colin Neil Jones, Yingzhao Lian, Jicheng Shi

By providing various services, such as Incentive-based Demand Response (IBDR), buildings can play a crucial role in the energy market due to their significant energy consumption. However, effectively commissioning buildings for such desired functionalities ...

2025

Robustly Learning Regions of Attraction From Fixed Data

Colin Neil Jones

While stability analysis is a mainstay for control science, especially computing regions of attraction of equilibrium points, until recently most stability analysis tools always required explicit knowledge of the model or a high-fidelity simulator represen ...

2025

Brunovsky Riccati Recursion for Linear Model Predictive Control

Colin Neil Jones

In almost all algorithms for Model Predictive Control (MPC), the most time-consuming step is to solve some form of Linear Quadratic (LQ) Optimal Control Problem (OCP) repeatedly. The commonly recognized best option for this is a Riccati recursion based sol ...

IEEE2025

Model predictive building climate control for mitigating heat pump noise pollution

Colin Neil Jones, Jicheng Shi

Noise pollution from heat pumps (HPs) has been an emerging concern to their broader adoption, especially in densely populated areas. This paper explores a model predictive control (MPC) approach for climate control of buildings, aimed at minimizing the noi ...

2025

Data-driven adaptive building thermal controller tuning with constraints: A primal-dual contextual Bayesian optimization approach

Colin Neil Jones, Wenjie Xu

We study the problem of tuning the parameters of a room temperature controller to minimize its energy consumption, subject to the constraint that the daily cumulative thermal discomfort of the occupants is below a given threshold. We formulate it as an onl ...

Elsevier Sci Ltd2024

Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization

Colin Neil Jones, Yuning Jiang

This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as power consumers and suppliers, coupled wi ...

IEEE2024

SOStab: A Matlab toolbox for transient stability analysis

Colin Neil Jones

This paper presents a new Matlab toolbox, aimed at facilitating the use of polynomial optimization for stability analysis of nonlinear systems. In the past decade several decisive contributions made it possible to recast this type of problems as convex opt ...

Elsevier2024

Decentralized Over-the-Air Federated Learning by Second-Order Optimization Method

Colin Neil Jones, Yuning Jiang

Federated learning (FL) is an emerging technique that enables privacy-preserving distributed learning. Most related works focus on centralized FL, which leverages the coordination of a parameter server to implement local model aggregation. However, this sc ...

2024

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Colin Neil Jones, Wenjie Xu, Bratislav Svetozarevic

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Elsevier Sci Ltd2024

Ensuring data privacy in AC Optimal Power Flow with a distributed co-simulation framework

Colin Neil Jones, Yuning Jiang

During the energy transition, the significance of collaborative management among institutions is rising, confronting challenges posed by data privacy concerns. Prevailing research on distributed approaches, as an alternative to centralized management, ofte ...

Elsevier2024

SIMBa: System Identification Methods Leveraging Backpropagation

Colin Neil Jones, Loris Di Natale, Giancarlo Ferrari Trecate, Muhammad Zakwan

This manuscript details and extends the system identification methods leveraging the backpropagation (SIMBa) toolbox presented in previous work, which uses well-established machine learning tools for discrete-time linear multistep-ahead state-space system ...

2024

On identifying the non-linear dynamics of a hovercraft using an end-to-end deep learning approach

Colin Neil Jones, Roland Schwan

We present the identification of the non-linear dynamics of a novel hovercraft design, employing end-to-end deep learning techniques. Our experimental setup consists of a hovercraft propelled by racing drone propellers mounted on a lightweight foam base, a ...

Elsevier B.V.2024

Lower Bounds on the Noiseless Worst-Case Complexity of Efficient Global Optimization

Colin Neil Jones, Yuning Jiang, Wenjie Xu

Efficient global optimization is a widely used method for optimizing expensive black-box functions. In this paper, we study the worst-case oracle complexity of the efficient global optimization problem. In contrast to existing kernel-specific results, we d ...

2024

Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling

Colin Neil Jones, Yuning Jiang

This paper proposes a real-time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all ...

Elsevier2024

Risk-aware scheduling and dispatch of flexibility events in buildings

Colin Neil Jones

Residential and commercial buildings, equipped with systems such as heat pumps (HPs), hot water tanks, or stationary energy storage, have a large potential to offer their consumption flexibility as grid services. In this work, we leverage this flexibility ...

2024

Stable Linear Subspace Identification: A Machine Learning Approach

Colin Neil Jones, Giancarlo Ferrari Trecate

Machine Learning (ML) and linear System Identification (SI) have been historically developed independently. In this paper, we leverage well-established ML tools - especially the automatic differentiation framework - to introduce SIMBa, a family of discrete ...

Institute of Electrical and Electronics Engineers Inc.2024

Data-Driven Joint Distributionally Robust Chance-Constrained Operation for Multiple Integrated Electricity and Heating Systems

Colin Neil Jones, Yuning Jiang

Integrating heating and electricity networks offers extra flexibility to the energy system operation while improving energy utilization efficiency. This paper proposes a data-driven joint distributionally robust chance-constrained (DRCC) operation model fo ...

2024