Search arXiv⌕ Search

arXiv · 2610.02830

On BESS-Backed Trading on the Continuous Intraday Electricity Market

Abstract

Battery energy storage systems (BESS) on the continuous intraday market (IDC) often trade according to a rolling intrinsic algorithm, a myopic strategy which repeatedly opens and unwinds positions according to current prices throughout the trading session, before dispatching as delivery approaches. This paper introduces a novel trading strategy for storage, in which forecast-driven round trip trading takes priority and the BESS supplies a second route for closing out positions that the market would otherwise close at a distressed price. The agent uses price quantile forecasts to open positions on the IDC, and closes these positions closer to delivery. The market can move against these trades, and the BESS intervenes only when a position would have to be settled at a price that the forecast predicts to be highly improbable, absorbing or serving that volume physically and restoring its state of charge at ordinary prices afterwards. The position itself remains loss-making; what the asset changes is the price at which it is closed, by transferring the terminal settlement price through time. Four quantile forecasting models of increasing complexity supply the thresholds, and all strategies are backtested on realised EPEX SPOT transactions for the German market area in 2024. A 40 MWh BESS in this role earns EUR 2.06m against EUR 1.77m for a rolling intrinsic benchmark and EUR 1.37m for a perfect-foresight day-ahead benchmark, while consuming 167 instead of 365 available equivalent full cycles. Hence, the novel backstop strategy yields higher profits, while using the underlying BESS less, leaving capacity for other trading opportunities.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Leo Semmelmann, Runyao Yu, Joseph Cary, Derek Bunn. 2026-10-02. On BESS-Backed Trading on the Continuous Intraday Electricity Market. https://arxiv.org/abs/2610.02830

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

From Inference to Control: Structure-Guided Control of Hypergraph Dynamics

Controllability determines whether a system's state can be guided toward any desired configuration, making it a fundamental prerequisite for designing effective control strategies. In the context of networked systems, controllability is a well-established concept. However, many real-world systems, from biological collectives to engineered infrastructures, exhibit higher-order interactions that cannot be captured by simple graphs. Moreover, the interaction structures might be unknown and difficult to measure directly. Here, we close this gap by combining hypergraph inference with the identification of controllable nodes. Building on the inferred structure, we design a controller that, given a set of controllable nodes, steers the system toward a desired configuration. We formulate analytical controllability guarantees for polynomial systems. For non-polynomial dynamics on hypergraphs, we propose a heuristic method for identifying controllable nodes and validate the proposed approach using Kuramoto oscillators.

eess.SY↗

Input Dexterity and Output Negotiation in Feedback-Linearizable Nonlinear Systems

We introduce a task-relative taxonomy of actuator inputs for nonlinear systems within the input-output feedback-linearization framework. Given a flat output specifying the task, inputs are classified as essential, redundant, or dexterity: essential inputs are required for exact linearization, redundant inputs can be removed without effect, and dexterity inputs can be deactivated while preserving exact linearization of a reduced task. We show that a subset is dexterity if and only if, under a suitable dynamic prolongation, it can appear as additional output channels (flat-input complement) on a common validity set. Whenever a family of systems obtained by (de)activating dexterity inputs admits a common prolongation, the family can be interpreted as a single prolonged system endowed with different output selections. This enables a unified linearizing controller that negotiates between full and reduced tasks without transients on shared outputs under compatibility and dwell-time conditions. Simulations on a fully actuated aerial platform illustrate graceful task downgrades from six-dimensional pose tracking as lateral-force channels are deactivated.

eess.SY↗

Input-to-state stabilization of linear systems under data-rate constraints

We study feedback stabilization of linear systems under data-rate constraints in the presence of completely unknown disturbances. A communication and control strategy is proposed based on sampled and quantized state measurements, where the quantization range is dynamically adjusted using reachable-set approximations and a disturbance estimate derived from quantization parameters. The strategy alternates between stabilizing and searching stages to recapture the state after escapes from the quantization range. Under a data-rate condition, it guarantees input-to-state stability (ISS) with respect to the disturbance. An additional quantization symbol is introduced to establish ISS near the equilibrium. A simulation example illustrates the effectiveness of the proposed approach.

eess.SY↗