arXiv subjects

Xinyi Yi

Publications and source records attributed to Xinyi Yi.

8 recordsLinked to original sources

arXiv2026

A Mixed $H_{\infty}$--Passivity Approach for Leveraging Heat-Pump-Connected District Heating Systems as Frequency Support in Electric Power Systems

Heat-pump (HP)-connected district heating systems (DHSs) can support grid frequency by rapidly modulating HP electrical consumption while accommodating the resulting heat imbalance. Thermal-state-informed HP control improves EPS--DHS coordination, but introduces slower DHS dynamics and heat-side disturbance propagation at the electrical interface on the time scale of secondary frequency control. This paper formulates the regulated DHS as a grid-facing dynamic port and develops a mixed $H_\infty$--passivity framework for disturbance-independent temperature regulation while preserving a clean electrical response during secondary frequency control. Sufficient conditions guarantee local asymptotic stability of the EPS--HP--DHS interconnection across primary frequency control, secondary frequency control, and DHS regulation. These stability conditions are integrated with multi-channel $H_\infty$ attenuation of DHS-state-dependent electrical dynamics, heat-disturbance propagation, and DHS-regulation errors, yielding a tractable convex LMI program for controller synthesis. Cross-model validation deploys controllers synthesized on control-oriented EPS--DHS models, without retuning, on an open-source electromechanical IEEE 39-bus model coupled with four high-fidelity finite-volume DHS models retaining thermal transport, storage, and heat-loss dynamics. The resulting controller improves EPS--DHS coordination without compromising the grid-facing electrical response.

eess.SY↗

arXiv2026

TRACE: A Reproducible Benchmark for Electricity Price Forecasting with Official Operational Text

Electricity price forecasting (EPF) supports scheduling, bidding, and risk management in electricity markets, yet existing benchmarks focus mainly on numerical inputs, leaving the forecasting value of forecast-time textual context insufficiently evaluated. We introduce TRACE, a reproducible benchmark of 7,300 zone--day instances pairing prices from five zones in a major U.S. market with official operational text available at the forecast cutoff. TRACE reconstructs official operational text at each cutoff, preventing post-cutoff information leakage. We evaluate TRACE for semantic alignment and forecasting value. Semantic assessments align with central movement and both tail risks in ground-truth prices, most consistently for upper-tail price risk. Forecasting value is reflected in a median 7.4\% reduction in upper-tail pinball loss across time-series foundation models. A controlled cross-day text-mismatch ablation reverses the gains, falling below the no-text baseline.

cs.LG↗

arXiv2026

LiFT-MPC: Language-in-the-Loop Feedback Tuning of Cost Previews for MPC

In model predictive control (MPC) with time-varying objectives, predicted signals need to be often incorporated in the cost function, such as prices in energy system operation. These are, however, often difficult to predict from the historical trajectory of these signals alone, as they may depend on other contextual events. We propose LiFT-MPC, an MPC framework that integrates a LiFT (Language-in-the-Loop Feedback Tuning) correction scheme to refine such predictions within the MPC loop. The prediction mechanism is updated online via a control-performance loss function, and we establish a performance guarantee for the resulting closed loop system. Numerical experiments using a realistic example of energy-storage management with real prices and news context to improve predictions, demonstrate an improved economic performance

math.OC↗

arXiv2026

Data-driven online control for real-time optimal economic dispatch and temperature regulation in district heating systems

District heating systems (DHSs) require coordinated economic dispatch and temperature regulation under uncertain operating conditions. Existing DHS operation strategies often rely on disturbance forecasts and nominal models, so their economic and thermal performance may degrade when predictive information or model knowledge is inaccurate. This paper develops a data-driven online control framework for DHS operation by embedding steady-state economic optimality conditions into the temperature dynamics, so that the closed-loop system converges to the economically optimal operating point without relying on disturbance forecasts. Based on this formulation, we develop a Data-Enabled Policy Optimization (DeePO)-based online learning controller and incorporate Adaptive Moment Estimation (ADAM) to improve closed-loop performance. We further establish convergence and performance guarantees for the resulting closed-loop system. Simulations on an industrial-park DHS in Northern China show that the proposed method achieves stable near-optimal operation and strong empirical robustness to both static and time-varying model mismatch under practical disturbance conditions.

eess.SY↗

arXiv2026

A mixed Hinfty-Passivity approach for Leveraging District Heating Systems as Frequency Ancillary Service in Electric Power Systems

This paper introduces a mixed H-infinity-passivity framework that enables district heating systems (DHSs) with heat pumps to support electric-grid frequency regulation. The analysis illustrates how the DHS regulator influences coupled electro-thermal frequency dynamics and provides LMI conditions for efficient controller design. We also present a disturbance-independent temperature regulator that ensures stability and robustness against heat-demand uncertainty. Simulations demonstrate improved frequency-control dynamics in the electrical power grid while maintaining good thermal performance in the DHS.

eess.SY↗

arXiv2025

On-Policy Reinforcement-Learning Control for Optimal Energy Sharing and Temperature Regulation in District Heating Systems

We address the problem of temperature regulation and optimal energy sharing in district heating systems (DHSs) where the demand and system parameters are unknown. We propose a temperature regulation scheme that employs data-driven on-policy updates that achieve these objectives. In particular, we show that the proposed control scheme converges to an optimal equilibrium point of the system, while also having guaranteed convergence to an optimal LQR control policy, thus providing good transient performance. The efficiency of our approach is also demonstrated through extensive simulations.

eess.SY↗

arXiv2022

Energy-Grade Double Pricing Rule in the Heating Market

The problem of heat system pricing is considered. A direct extension of locational marginal prices (LMP) in electricity markets to heat systems may lead to revenue inadequate issues. The underlying reason for such a problem is that, unlike electric power, heat has different grades and cannot be considered as homogenized commodity. Accordingly, an energy-grade double pricing rule is proposed in this paper. Heat energy and grade prices are explained as the shadow prices related to the nodal heat balance constraints and temperature requirements constraints at the optimal solution. The resulting merchandise surplus at each dispatch interval can be decomposed into several explainable parts, namely, congestion rent, impact from the last period, and impact from the upcoming period. And the total merchandise surplus over all dispatch intervals can be decomposed into several non-negative interpretable parts, including congestion rent and impact from the initial state, thus guaranteeing the revenue adequacy for the heat system operator. Simulations verify the effectiveness of the proposed mechanism.

eess.SY↗

arXiv2022

Energy-grade double pricing mechanism for a combined heat and power system using the asynchronous dispatch method

The problem of heat and electricity pricing in combined heat and power systems regarding the time scales of electricity and heat, as well as thermal energy quality, is studied. Based on the asynchronous coordinated dispatch of the combined heat and power system, an energy-grade double pricing mechanism is proposed. Under the pricing mechanism, the resulting merchandise surplus of the heat system operator at each heat dispatch interval can be decomposed into interpretable parts and its revenue adequacy can be guaranteed for all heat dispatch intervals. And the electric power system operator's resulting merchandise surplus is composed of non-negative components at each electricity dispatch interval, also ensuring its revenue adequacy. In addition, the effects of different time scales and cogeneration are analyzed in different kinds of combined heat and power units' pricing.

eess.SY↗