Tootfinder

Price Aware Power Split Control in Heterogeneous Battery Storage Systems
Sheng Yin, Vivek Teja Tanjavooru, Thomas Hamacher, Christoph Goebel, Holger Hesse
https://arxiv.org/abs/2507.00628

Price Aware Power Split Control in Heterogeneous Battery Storage Systems
This paper presents a unified framework for the optimal scheduling of battery dispatch and internal power allocation in Battery energy storage systems (BESS). This novel approach integrates both market-based (price-aware) signals and physical system constraints to simultaneously optimize (1) external energy dispatch and (2) internal heterogeneity management of BESS, enhancing its operational economic value and performance. This work compares both model-based Linear Programming (LP) and model-fr…

Real-Time Energy Management Strategies for Community Microgrids
Moslem Uddin, Huadong Mo, Daoyi Dong
https://arxiv.org/abs/2506.22931 https://

Real-Time Energy Management Strategies for Community Microgrids
This study presents a real-time energy management framework for hybrid community microgrids integrating photovoltaic, wind, battery energy storage systems, diesel generators, and grid interconnection. The proposed approach formulates the dispatch problem as a multi-objective optimization task that aims to minimize operational costs. Two control strategies are proposed and evaluated: a conventional rule-based control (RBC) method and an advanced deep reinforcement learning (DRL) approach utilizi…

Linear and Second-order-cone Valid Inequalities for Problems with Storage
Juan M. Morales
https://arxiv.org/abs/2506.21470 https://ar…

Linear and Second-order-cone Valid Inequalities for Problems with Storage
Batteries are playing an increasingly central role as distributed energy resources in the shift toward power systems dominated by renewable energy sources. However, existing battery models must invariably rely on complementarity constraints to prevent simultaneous charging and discharging, rendering models of a disjunctive nature and NP-hard. In this paper, we analyze the disjunctive structure of the battery's feasible operational set and uncover a submodularity property in its extreme power tr…

Decarbonizing Mongolia's Energy Sector: A Techno-Economic Analysis of Hybrid Energy Solutions
Otgonpurev Nergui, Dhammawit Paisiripas, Munkhsaikhan Jargalsaikhan
https://arxiv.org/abs/2506.15749

Decarbonizing Mongolia's Energy Sector: A Techno-Economic Analysis of Hybrid Energy Solutions
To achieve carbon neutrality and enhance energy security, Mongolia is exploring a transition toward hybrid energy solutions integrating small modular reactors (SMRs) and renewable energy sources. This study assesses the feasibility of a grid-connected hybrid energy system that combines coal, solar photovoltaic (PV), wind turbines, battery energy storage systems (BESS), and SMRs to reduce greenhouse gas emissions and improve energy reliability.

Choosing the Right Battery Model for Data Center Simulations
Paul Kilian, Philipp Wiesner, Odej Kao
https://arxiv.org/abs/2506.17739 https://

Choosing the Right Battery Model for Data Center Simulations
As demand for computing resources continues to rise, the increasing cost of electricity and anticipated regulations on carbon emissions are prompting changes in data center power systems. Many providers are now operating compute nodes in microgrids, close to renewable power generators and energy storage, to maintain full control over the cost and origin of consumed electricity. Recently, new co-simulation testbeds have emerged that integrate domain-specific simulators to support research, devel…

Sequential Operation of Residential Energy Hubs
Dar\'io Slaifstein (Delft University of Technology), Gautham Ram Chandra Mouli (Delft University of Technology), Laura Ramirez-Elizondo (Delft University of Technology), Pavol Bauer (Delft University of Technology)
https://arxiv.org/abs/2507.20621…

Sequential Operation of Residential Energy Hubs
The operation of residential energy hubs with multiple energy carriers (electricity, heat, mobility) poses a significant challenge due to different carrier dynamics, hybrid storage coordination and high-dimensional action-spaces. Energy management systems oversee their operation, deciding the set points of the primary control layer. This paper presents a novel 2-stage economic model predictive controller for electrified buildings including physics-based models of the battery degradation and the…

A Spintronic Battery with Reversible Modulation of Spin Polarization through Li Charge/Discharge: A First Principles Computational Modelling Case Study for an Antiperovskite System
Sk Mujaffer Hossain, Vinila Bedekara, Priyanka Yadavb, Ram Janay Chudhary, Satishchandra Ogale
https://arxiv.org/abs/2506.14401

A Spintronic Battery with Reversible Modulation of Spin Polarization through Li Charge/Discharge: A First Principles Computational Modelling Case Study for an Antiperovskite System
A key notion defining the progress of the emergent fields of modern electronics, renewable energy, and smart systems is charge storage, which is primarily embodied in various battery chemistries and systems. In addition to the charge property, the electron also has the spin property, which is exploited in the field of spintronics to access novel magnetically controlled device actions that are not accessible to conventional electronics. An interesting question is whether the two can be fruitfull…

This https://arxiv.org/abs/2501.07121 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCE_…

The Value of Battery Energy Storage in the Continuous Intraday Market: Forecast vs. Perfect Foresight Strategies
Grid-scale battery energy storage systems (BESSs) can provide flexibility to the power system and capture shortterm price volatility by shifting energy in time through controlled charging and discharging. The highly volatile European continuous intraday (CID) market allows trading until just a few minutes before physical delivery, offering significant earning potential. However, its high trading frequency poses substantial modeling challenges. Accurate modeling of BESSs trading in the CID marke…

Approximating CCCV charging using SOC-dependent tapered charging power constraints in long-term microgrid planning
Hassan Zahid Butt, Xingpeng Li
https://arxiv.org/abs/2507.18853

Approximating CCCV charging using SOC-dependent tapered charging power constraints in long-term microgrid planning
Traditional long-term microgrid planning models assume constant power charging for battery energy storage systems (BESS), overlooking efficiency losses that occur toward the end of charge due to rising internal resistance. While this issue can be mitigated at the cell level using constant current-constant voltage (CCCV) charging, it is impractical at the pack level in large-scale systems. However, battery management systems and inverter controls can emulate this effect by tapering charging powe…

State constrained stochastic optimal control of a PV system with battery storage via Fokker-Planck and Hamilton-Jacobi-Bellman equations
Alfredo Berm\'udez, Iago Pad\'in
https://arxiv.org/abs/2506.11765

State constrained stochastic optimal control of a PV system with battery storage via Fokker-Planck and Hamilton-Jacobi-Bellman equations
With the growing global emphasis on sustainability and the implementation of contemporary environmental policies, the penetration of renewable energy sources has significantly increased --primarily due to their inexhaustible nature. In this context, integrating photovoltaic (PV) modules with energy storage systems offers a means to mitigate the inherent variability of solar energy. This paper proposes an optimal methodology for power management and market bidding strategies tailored to PV power…

Joint Scheduling of DER under Demand Charges: Structure and Approximation
Ruixiao Yang, Gulai Shen, Ahmed S. Alahmed, Chuchu Fan
https://arxiv.org/abs/2506.21510

Joint Scheduling of DER under Demand Charges: Structure and Approximation
We study the joint scheduling of behind-the-meter distributed energy resources (DERs), including flexible loads, renewable generation, and battery energy storage systems, under net energy metering frameworks with demand charges. The problem is formulated as a stochastic dynamic program aimed at maximizing expected operational surplus while accounting for renewable generation uncertainty. We analytically characterize the structure of the optimal control policy and show that it admits a threshold…

Predictive Energy Management for Mitigating Load Altering Attacks for Islanded Microgrids Using Battery Energy Storage Systems
Satish Vedula, Koto Omiloli, Ayobami Olajube, Olugbenga Anubi
https://arxiv.org/abs/2507.01852

Predictive Energy Management for Mitigating Load Altering Attacks for Islanded Microgrids Using Battery Energy Storage Systems
An increasing number of smart devices controlling loads opens a potential pathway for false data attacks which could alter the loads. The presence of energy storage with its ability to quickly respond to discrepancies in loads offers a promising solution for security by preventing further instabilities and potential blackouts. This paper proposes a control methodology for secure predictive energy management that uses batteries to mitigate the impact of load-altering attacks. To that extent, we …

Deep reinforcement learning-based joint real-time energy scheduling for green buildings with heterogeneous battery energy storage devices
Chi Liu, Zhezhuang Xu, Jiawei Zhou, Yazhou Yuan, Kai Ma, Meng Yuan
https://arxiv.org/abs/2506.06824

Deep reinforcement learning-based joint real-time energy scheduling for green buildings with heterogeneous battery energy storage devices
Green buildings (GBs) with renewable energy and building energy management systems (BEMS) enable efficient energy use and support sustainable development. Electric vehicles (EVs), as flexible storage resources, enhance system flexibility when integrated with stationary energy storage systems (ESS) for real-time scheduling. However, differing degradation and operational characteristics of ESS and EVs complicate scheduling strategies. This paper proposes a model-free deep reinforcement learning (…

Techno-economic optimization of hybrid steam-electric energy systems with excess heat utilization and reserve market participation
Olav Galteland, Jacob Hadler-Jacobsen, Hanne Kauko
https://arxiv.org/abs/2506.14252

Techno-economic optimization of hybrid steam-electric energy systems with excess heat utilization and reserve market participation
This study investigates the economic viability and optimal configuration of a hybrid industrial energy system combining an electrode boiler, steam accumulator, and battery energy storage system (BESS). This study optimizes system operation for a specific configuration to minimize net energy costs, defined as energy costs minus profits from price arbitrage and reserve markets. The optimization uses load shifting, peak shaving, and frequency containment reserve market participation with hourly 20…

BESS Participation Planning for Provision of Grid Services in Energy and Regulation Markets
Zeenat Hameed, Chresten Traeholt
https://arxiv.org/abs/2506.08472

BESS Participation Planning for Provision of Grid Services in Energy and Regulation Markets
This paper presents a stochastic optimization model for planning the participation of battery energy storage systems (BESSs) in energy and regulation markets. The proposed model quantifies and compares the business value of single and multi-market BESS services by accounting for their bid submission and acceptance procedures, pricing mechanisms and revenue streams, and penalty payments and degradation costs. By modelling the price uncertainties using market price scenarios (MPSs) and considerin…

The Economic Dispatch of Power-to-Gas Systems with Deep Reinforcement Learning:Tackling the Challenge of Delayed Rewards with Long-Term Energy Storage
Manuel Sage, Khalil Al Handawi, Yaoyao Fiona Zhao
https://arxiv.org/abs/2506.06484

The Economic Dispatch of Power-to-Gas Systems with Deep Reinforcement Learning:Tackling the Challenge of Delayed Rewards with Long-Term Energy Storage
Power-to-Gas (P2G) technologies gain recognition for enabling the integration of intermittent renewables, such as wind and solar, into electricity grids. However, determining the most cost-effective operation of these systems is complex due to the volatile nature of renewable energy, electricity prices, and loads. Additionally, P2G systems are less efficient in converting and storing energy compared to battery energy storage systems (BESs), and the benefits of converting electricity into gas ar…

Optimal Operating Strategy for PV-BESS Households: Balancing Self-Consumption and Self-Sufficiency
Jun Wook Heo, Raja Jurdak, Sara Khalifa
https://arxiv.org/abs/2506.17268

Optimal Operating Strategy for PV-BESS Households: Balancing Self-Consumption and Self-Sufficiency
High penetration of Photovoltaic (PV) generation and Battery Energy Storage System (BESS) in individual households increases the demand for solutions to determine the optimal PV generation power and the capacity of BESS. Self-consumption and self-sufficiency are essential for optimising the operation of PV-BESS systems in households, aiming to minimise power import from and export to the main grid. However, self-consumption and self-sufficiency are not independent; they share a linear relations…

Optimal BESS Scheduling for Multi-Market Participation in the Nordics
Zeenat Hameed, Chresten Traeholt
https://arxiv.org/abs/2506.02837 https://

Optimal BESS Scheduling for Multi-Market Participation in the Nordics
Battery energy storage systems BESSs can provide fast frequency reserves and energy arbitrage in Nordic electricity markets but their limited energy capacity requires accurate revenue forecasts and coordinated bidding across multiple submarkets. This paper introduces a unified framework that employs generalized additive models GAMs to generate one week ahead forecasts of spot and FCRN revenues in Denmark, Finland, and Norway using three years of hourly price and volume data. Forecast outputs fe…

Optimal Sizing and Control of a Grid-Connected Battery in a Stacked Revenue Model Including an Energy Community
Tudor Octavian Pocola, Valentin Robu, Jip Rietveld, Sonam Norbu, Benoit Couraud, Merlinda Andoni, David Flynn, H. Vincent Poor
https://arxiv.org/abs/2507.04343

Optimal Sizing and Control of a Grid-Connected Battery in a Stacked Revenue Model Including an Energy Community
Recent years have seen rapid increases in intermittent renewable generation, requiring novel battery energy storage systems (BESS) solutions. One recent trend is the emergence of large grid-connected batteries, that can be controlled to provide multiple storage and flexibility services, using a stacked revenue model. Another emerging development is renewable energy communities (REC), in which prosumers invest in their own renewable generation capacity, but also requiring battery storage for fle…

Accounting for Subsystem Aging Variability in Battery Energy Storage System Optimization
Melina Grane, Martin Cornejo, Holger Hesse, Andreas Jossen
https://arxiv.org/abs/2507.04813

Accounting for Subsystem Aging Variability in Battery Energy Storage System Optimization
This paper presents a degradation-cost-aware optimization framework for multi-string battery energy storage systems, emphasizing the impact of inhomogeneous subsystem-level aging in operational decision-making. We evaluate four scenarios for an energy arbitrage scenario, that vary in model precision and treatment of aging costs. Key performance metrics include operational revenue, power schedule mismatch, missed revenues, capacity losses, and revenue generated per unit of capacity loss. Our ana…

Optimal Co-Design of a Hybrid Energy Storage System for Truck Charging
Juan Pablo Bertucci, Sudarshan Raghuraman, Mauro Salazar, Theo Hofman
https://arxiv.org/abs/2506.01426

Optimal Co-Design of a Hybrid Energy Storage System for Truck Charging
The major challenges to battery electric truck adoption are their high cost and grid congestion.In this context, stationary energy storage systems can help mitigate both issues. Since their design and operation are strongly coupled, to make the best out of them, they should be jointly optimized. This paper presents a co-design framework for hybrid energy storage systems where their technology and sizing are optimized jointly with their operational strategies. Specifically, we consider a microgr…

Optimizing Software Defined Battery Systems for Transformer Protection
Sonia Martin, Obidike Nnorom Jr., Philip Levis, Ram Rajagopal
https://arxiv.org/abs/2506.03439

Optimizing Software Defined Battery Systems for Transformer Protection
Residential electric vehicle charging causes large spikes in electricity demand that risk violating neighborhood transformer power limits. Battery energy storage systems reduce these transformer limit violations, but operating them individually is not cost-optimal. Instead of individual optimization, aggregating, or sharing, these batteries leads to cost-optimal performance, but homeowners must relinquish battery control. This paper leverages virtualization to propose battery sharing optimizati…

Optimizing Battery and Line Undergrounding Investments for Transmission Systems under Wildfire Risk Scenarios: A Benders Decomposition Approach
Ryan Piansky, Rahul K. Gupta, Daniel K. Molzahn
https://arxiv.org/abs/2506.06687

Optimizing Battery and Line Undergrounding Investments for Transmission Systems under Wildfire Risk Scenarios: A Benders Decomposition Approach
With electric power infrastructure posing an increasing risk of igniting wildfires under continuing climate change, utilities are frequently de-energizing power lines to mitigate wildfire ignition risk, which can cause load shedding. Recent research advocates for installing battery energy storage systems as well as undergrounding risky overhead lines to reduce the load shedding during such de-energizations. Since wildfire ignition risk can exhibit substantial geographic and temporal variations,…

This https://arxiv.org/abs/2506.03439 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Optimizing Software Defined Battery Systems for Transformer Protection
Residential electric vehicle charging causes large spikes in electricity demand that risk violating neighborhood transformer power limits. Battery energy storage systems reduce these transformer limit violations, but operating them individually is not cost-optimal. Instead of individual optimization, aggregating, or sharing, these batteries leads to cost-optimal performance, but homeowners must relinquish battery control. This paper leverages virtualization to propose battery sharing optimizati…

EPC Framework for BESS Projects
Zeenat Hameed, Chresten Tr{\ae}holt
https://arxiv.org/abs/2506.13281 https://arxiv.org/pdf/2506.13281…

EPC Framework for BESS Projects
Battery Energy Storage Systems (BESS) are critical for modern power networks, supporting grid services such as frequency regulation, peak shaving, and black start. Delivering a BESS under an Engineering, Procurement, and Construction (EPC) model requires a concise methodology that balances regulatory compliance, technical details, and schedule efficiency. This paper presents a streamlined, five step EPC framework covering feasibility assessment, permitting, procurement, construction, and commis…

An Adaptive Estimation Approach based on Fisher Information to Overcome the Challenges of LFP Battery SOC Estimation
Junzhe Shi, Shida Jiang, Shengyu Tao, Jaewong Lee, Manashita Borah, Scott Moura
https://arxiv.org/abs/2507.01173

An Adaptive Estimation Approach based on Fisher Information to Overcome the Challenges of LFP Battery SOC Estimation
Robust and Real-time State of Charge (SOC) estimation is essential for Lithium Iron Phosphate (LFP) batteries, which are widely used in electric vehicles (EVs) and energy storage systems due to safety and longevity. However, the flat Open Circuit Voltage (OCV)-SOC curve makes this task particularly challenging. This challenge is complicated by hysteresis effects, and real-world conditions such as current bias, voltage quantization errors, and temperature that must be considered in the battery m…

Multi-Objective Nonlinear Power Split Control For BESS With Real-Time Simulation Feedback
Vivek Teja Tanjavooru, Prashant Pant, Thomas Hamacher, Holger Hesse
https://arxiv.org/abs/2507.04800

Multi-Objective Nonlinear Power Split Control For BESS With Real-Time Simulation Feedback
This paper presents a mixed-integer, nonlinear, multi-objective optimization strategy for optimal power allocation among parallel strings in Battery Energy Storage Systems (BESS). High-fidelity control is achieved by co-simulating the optimizer with a BESS electro-thermal simulation that models spatial thermal dynamics of the battery, providing real-time State of Charge (SOC) and temperature feedback. The optimizer prioritizes reliability by enforcing power availability as a hard constraint and…