Tootfinder

"EV battery recycling key to easing future lithium supply constraints, modeling study shows"
#EV #ElectricVehicle #Cars

EV battery recycling key to easing future lithium supply constraints, modeling study shows
Lightweight, powerful lithium-ion batteries are crucial for the transition to electric vehicles, and global demand for lithium is set to grow rapidly over the next 25 years. A new analysis from the University of California, Davis, published May 29 in Nature Sustainability, looks at how new mining operations and battery recycling could meet that demand. Recycling could play a big role in easing supply constraints, the researchers found.

Production Planning Under Demand and Endogenous Supply Uncertainty
Mike Hewitt, Giovanni Pantuso
https://arxiv.org/abs/2506.23780 https://

Production Planning Under Demand and Endogenous Supply Uncertainty
We study the problem of determining how much finished goods inventory to source from different capacitated facilities in order to maximize profits resulting from sales of such inventory. We consider a problem wherein there is uncertainty in demand for finished goods inventory and production yields at facilities. Further, we consider that uncertainty in production yields is endogenous, as it depends on both the facilities where a product is produced and the volumes produced at those facilities. …

Critical demand in a stochastic model of flows in supply networks
Yannick Feld, Marc Barthelemy
https://arxiv.org/abs/2505.24813 https://

Critical demand in a stochastic model of flows in supply networks
Supply networks are essential for modern production, yet their critical properties remain understudied. We present a stochastic model with random production capacities to analyze material flow to a root node, focusing on topology and buffer stocks. The critical demand, where unsatisfied demand diverges, is examined mostly through numerical simulations. Without stocks, minimal production dictates behavior, making topology irrelevant. With stocks, memory effects arise, making topology crucial. In…

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Ronny Ko, Jiseong Jeong, Shuyuan Zheng, Chuan Xiao, Taewan Kim, Makoto Onizuka, Wonyong Shin
https://arxiv.org/abs/2505.23847

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership. Yet, cross-domain collaboration shatters the unified trust assumptions behind current alignment and containment techniques. An agent benign in isolation may, when receiving messages from an untrusted peer, leak secrets or viola…

This https://arxiv.org/abs/2505.22862 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Allocation of goods and services often involves both stochastic supply and stochastic demand. Motivated by applications such as cloud computing, gig platforms, and blockchain auctions, we study the design of optimal selling mechanisms in an environment where buyers with private valuations arrive stochastically and are assigned goods that also arrive stochastically, and either buyers or goods can be held in a queue at costs until allocation. The optimal mechanism dynamically leverages competitiv…

Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way
Chido Onyeze, Sean R. Sinclair, Chamsi Hssaine, Siddhartha Banerjee
https://arxiv.org/abs/2508.21753

Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way
We study the trade-off between envy and inefficiency in repeated resource allocation settings with stochastic replenishments, motivated by real-world systems such as food banks and medical supply chains. Specifically, we consider a model in which a decision-maker faced with stochastic demand and resource donations must trade off between an equitable and efficient allocation of resources over an infinite horizon. The decision-maker has access to storage with fixed capacity $M$, and incurs effici…

A Deep Learning Algorithm Based on CNN-LSTM Framework for Predicting Cancer Drug Sales Volume
Yinghan Li, Yilin Yao, Junghua Lin, Nanxi Wang
https://arxiv.org/abs/2506.21927

A Deep Learning Algorithm Based on CNN-LSTM Framework for Predicting Cancer Drug Sales Volume
This study explores the application potential of a deep learning model based on the CNN-LSTM framework in forecasting the sales volume of cancer drugs, with a focus on modeling complex time series data. As advancements in medical technology and cancer treatment continue, the demand for oncology medications is steadily increasing. Accurate forecasting of cancer drug sales plays a critical role in optimizing production planning, supply chain management, and healthcare policy formulation. The data…

#Copper #Mining and Vehicle Electrification | IEF Report
"To meet ... trends, 115% more copper must be mined in the next 30 years than has been mined historically until now. To electrify the global vehicle fleet requires bringing into production 55% more new mines than would otherwise be needed. On…

Copper Mining and Vehicle Electrification | IEF Report
Many studies have raised concerns that copper supply cannot meet the copper demands of both the green energy transition and equitable global development. This report addresses this issue by projecting copper supply and demand from 2018 to 2050 and placing both in the historical context of copper mine output.

A Wide-Input 0.25 um BCD LDO with Dual-Stage Amplifier and Active Ripple Cancellation for High PSRR and Fast Transient Response
Yi Zhang, Zhuolong Chen, Zhenghao Xu, Yujin He
https://arxiv.org/abs/2507.20522

A Wide-Input 0.25 um BCD LDO with Dual-Stage Amplifier and Active Ripple Cancellation for High PSRR and Fast Transient Response
Demand for on-chip low-dropout regulators (LDOs) with both high power-supply rejection ratio (PSRR) and fast transient response is growing as system-on-chip (SoC) integration increases. However, conventional LDO architectures face difficulty achieving these performance metrics simultaneously over wide input voltage ranges. This paper presents a wide-input linear regulator implemented in 0.25 um BCD technology that attains high PSRR and swift load-transient performance while maintaining low quie…

Daring project by my former colleague @…, in his spare time: compiling a European grid capacity (scarcity) map! https://www.gridcapacitymaps.eu/
Still …

One of the many interesting pages in the Future Energy Scenarios 2025, published today by NESO (🇬🇧 National Energy System Operator).
It focuses on the why, how and what of demand side flexibility.
Key: reward consumers, build trust, automate and smart tariffs.
EV smart charging gateway to more residential flex.
#EV

Adaptive Inventory Strategies using Deep Reinforcement Learning for Dynamic Agri-Food Supply Chains
Amandeep Kaur, Gyan Prakash
https://arxiv.org/abs/2507.16670

Adaptive Inventory Strategies using Deep Reinforcement Learning for Dynamic Agri-Food Supply Chains
Agricultural products are often subject to seasonal fluctuations in production and demand. Predicting and managing inventory levels in response to these variations can be challenging, leading to either excess inventory or stockouts. Additionally, the coordination among stakeholders at various level of food supply chain is not considered in the existing body of literature. To bridge these research gaps, this study focuses on inventory management of agri-food products under demand and lead time u…

LVMH says AI and AI agents will be key to navigating a broad slowdown and waning demand in luxury goods, and is using AI in supply chains, pricing, and more (Isabelle Bousquette/Wall Street Journal)
https://www.wsj.com/artic…

£13.2bn fund to fix draughty homes and install heat pumps and solar panels.
Nothing else that I can see on reduction of energy demand.
And here is the money being wasted:
'£30bn in investment in nuclear power, about half on the Sizewell C reactor'
Small tidal schemes in the Mersey, Severn and other estuaries would give a better, and safer, approach to "always on" energy supply.

Cost allocations in interval inventory situations: the SOC and Shapley approaches
J. C. Gon\c{c}alves-Dosantos, A. Meca, I. Ozcan
https://arxiv.org/abs/2507.21603 https://

Cost allocations in interval inventory situations: the SOC and Shapley approaches
Uncertainty in demand and supply conditions poses critical challenges to effective inventory management, especially in collaborative environments. Traditional inventory models, such as those based on the Economic Order Quantity (EOQ), often rely on fixed parameters and deterministic assumptions, limiting their ability to capture the complexity of real-world scenarios. This paper focuses on interval inventory situations, an extension of classical models in which demand is represented as interval…

JobPulse: A Big Data Approach to Real-Time Engineering Workforce Analysis and National Industrial Policy
Karen S. Markel, Mihir Tale, Andrea Belz
https://arxiv.org/abs/2508.11014

JobPulse: A Big Data Approach to Real-Time Engineering Workforce Analysis and National Industrial Policy
Employment on a societal scale contributes heavily to national and global affairs; consequently, job openings and unemployment estimates provide important information to financial markets and governments alike. However, such reports often describe only the supply (employee job seeker) side of the job market, and skill mismatches are poorly understood. Job postings aggregated on recruiting platforms illuminate marketplace demand, but to date have primarily focused on candidate skills described i…

Grid-Edge Energy-Flexible Technologies: A Comparative Analysis Across Generators, Loads, and Energy Storage Systems
Jesus Silva-Rodriguez, Tianxia Zhao, Ran Mo, Xingpeng Li
https://arxiv.org/abs/2508.14297

Grid-Edge Energy-Flexible Technologies: A Comparative Analysis Across Generators, Loads, and Energy Storage Systems
This review analysis presents a comprehensive exploration of energy flexibility in modern power systems. It examines the roles and mechanisms of flexible technologies across three main categories: generators, energy storage systems (ESS), and loads. Energy flexibility is defined as the ability to dynamically adjust supply and/or demand in response to grid conditions to maintain balance and stability. This is of particular importance to facilitate the integration of the growing variable renewabl…

A Simulation-Based Conceptual Model for Tokenized Recycling: Integrating Blockchain, Market Dynamics, and Behavioral Economics
Atta Ul Mustafa
https://arxiv.org/abs/2507.19901 h…

A Simulation-Based Conceptual Model for Tokenized Recycling: Integrating Blockchain, Market Dynamics, and Behavioral Economics
This study develops a conceptual simulation model for a tokenized recycling incentive system that integrates blockchain infrastructure, market-driven pricing, behavioral economics, and carbon credit mechanisms. The model aims to address the limitations of traditional recycling systems, which often rely on static government subsidies and fail to generate sustained public participation. By introducing dynamic token values linked to real-world supply and demand conditions, as well as incorporating…

Micromobility Flow Prediction: A Bike Sharing Station-level Study via Multi-level Spatial-Temporal Attention Neural Network
Xi Yang, Jiachen Wang, Song Han, Suining He
https://arxiv.org/abs/2507.16020

Micromobility Flow Prediction: A Bike Sharing Station-level Study via Multi-level Spatial-Temporal Attention Neural Network
Efficient use of urban micromobility resources such as bike sharing is challenging due to the unbalanced station-level demand and supply, which causes the maintenance of the bike sharing systems painstaking. Prior efforts have been made on accurate prediction of bike traffics, i.e., demand/pick-up and return/drop-off, to achieve system efficiency. However, bike station-level traffic prediction is difficult because of the spatial-temporal complexity of bike sharing systems. Moreover, such level …

Resource-Splitting Games with Tullock-Based Lossy Contests
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
https://arxiv.org/abs/2507.13853 https://…

Resource-Splitting Games with Tullock-Based Lossy Contests
This paper introduces a novel class of multi-stage resource allocation games that model real-world scenarios in which profitability depends on the balance between supply and demand, and where higher resource investment leads to greater returns. Our proposed framework, which incorporates the notion of profit loss due to insufficient player participation, gives rise to a Tullock-like functional form of the stage payoff structure when weighted fair proportional resource allocation is applied. We e…

"UK government abandons energy ‘zonal pricing’ plan"
#UK #UnitedKingdom #Energy

A Lightweight Incentive-Based Privacy-Preserving Smart Metering Protocol for Value-Added Services
Farid Zaredar, Morteza Amini
https://arxiv.org/abs/2508.14703 https://

A Lightweight Incentive-Based Privacy-Preserving Smart Metering Protocol for Value-Added Services
The emergence of smart grids and advanced metering infrastructure (AMI) has revolutionized energy management. Unlike traditional power grids, smart grids benefit from two-way communication through AMI, which surpasses earlier automated meter reading (AMR). AMI enables diverse demand- and supply-side utilities such as accurate billing, outage detection, real-time grid control, load forecasting, and value-added services. Smart meters play a key role by delivering consumption values at predefined …

Peer-to-Peer Energy Markets With Uniform Pricing: A Dynamic Operating Envelope Approach
Zeinab Salehi, Yijun Chen, Ian R. Petersen, Guodong Shi, Duncan S. Callaway, Elizabeth L. Ratnam
https://arxiv.org/abs/2506.19328

Peer-to-Peer Energy Markets With Uniform Pricing: A Dynamic Operating Envelope Approach
The recent widespread adoption of rooftop solar backed by battery storage is enabling energy customers to both produce and consume electricity (i.e., prosumers of electricity). To facilitate prosumer participation in the electric grid, new market mechanisms are required. In this paper, we design peer-to-peer energy markets where prosumers trade their excess energy with peers to gain profit while satisfying the overall balance in electricity supply and demand. We first consider a market structur…

Dynamic access pricing control for fair and stable resource sharing
Chris King, Homayoun Hamedmoghadam, Christos Cassandras, Fabian Wirth, Robert Shorten
https://arxiv.org/abs/2507.17939

Dynamic access pricing control for fair and stable resource sharing
In this paper we consider the use of pricing as a regulatory mechanism when an unknown number of autonomous agents compete for access to a scarce shared resource. In standard dynamic pricing systems, an increasing price is used to balance supply and demand for a resource in a constrained environment. A major drawback of dynamic pricing is that it is socially regressive as such systems favour price-insensitive traffic (inelastic) and control the demand at the expense of price-sensitive traffic (…

Subgame Perfect Nash Equilibria in Large Reinsurance Markets
Maria Andraos, Mario Ghossoub, Michael B. Zhu
https://arxiv.org/abs/2506.07291 https://…

Subgame Perfect Nash Equilibria in Large Reinsurance Markets
We consider a model of a reinsurance market consisting of multiple insurers on the demand side and multiple reinsurers on the supply side, thereby providing a unifying framework and extension of the recent literature on optimality and equilibria in reinsurance markets. Each insurer has preferences represented by a general Choquet risk measure and can purchase coverage from any or all reinsurers. Each reinsurer has preferences represented by a general Choquet risk measure and can provide coverag…

"For the approximate one-third of households across these countries without driveways, the running costs of an EV remain a major barrier to widespread adoption.
Dynamic pricing, where electricity prices vary based on supply and demand, presents an opportunity to allow households to access cheaper electricity when renewables are abundant."
#EV

An advanced reliability reserve incentivizes flexibility investments while safeguarding the electricity market
Franziska Klaucke, Karsten Neuhoff, Alexander Roth, Wolf-Peter Schill, Leon Stolle
https://arxiv.org/abs/2506.14664

An advanced reliability reserve incentivizes flexibility investments while safeguarding the electricity market
To ensure security of supply in the power sector, many countries are already using or discussing the introduction of capacity mechanisms. Two main types of such mechanisms include capacity markets and capacity reserves. Simultaneously, the expansion of variable renewable energy sources increases the need for power sector flexibility, for which there are promising yet often under-utilized options on the demand side. In this paper, we analyze how a centralized capacity market and an advanced reli…

Climate2Energy: a framework to consistently include climate change into energy system modeling
Jan Wohland, Luna Bloin-Wibe, Erich Fischer, Leonhard G\"oke, Reto Knutti, Francesco De Marco, Urs Beyerle, Jonas Savelsberg
https://arxiv.org/abs/2508.09531

Climate2Energy: a framework to consistently include climate change into energy system modeling
Supply and demand in future energy systems depend on the weather. We therefore need to quantify how climate change and variability impact energy systems. Here, we present Climate2Energy (C2E), a framework to consistently convert climate model outputs into energy system model inputs, covering all relevant types of renewable generation and demand for heating and cooling. C2E performs bias correction, uses established open-source tools where possible, and provides outputs tailored to energy system…

Digital Twin-based Smart Manufacturing: Dynamic Line Reconfiguration for Disturbance Handling
Bo Fu, Mingjie Bi, Shota Umeda, Takahiro Nakano, Youichi Nonaka, Quan Zhou, Takaharu Matsui, Dawn M. Tilbury, Kira Barton
https://arxiv.org/abs/2506.07332

Digital Twin-based Smart Manufacturing: Dynamic Line Reconfiguration for Disturbance Handling
The increasing complexity of modern manufacturing, coupled with demand fluctuation, supply chain uncertainties, and product customization, underscores the need for manufacturing systems that can flexibly update their configurations and swiftly adapt to disturbances. However, current research falls short in providing a holistic reconfigurable manufacturing framework that seamlessly monitors system disturbances, optimizes alternative line configurations based on machine capabilities, and automate…

This https://arxiv.org/abs/2205.10538 has been replaced.
link: https://scholar.google.com/scholar?q=a

Automated machine learning: AI-driven decision making in business analytics
The realization that AI-driven decision-making is indispensable in today's fast-paced and ultra-competitive marketplace has raised interest in industrial machine learning (ML) applications significantly. The current demand for analytics experts vastly exceeds the supply. One solution to this problem is to increase the user-friendliness of ML frameworks to make them more accessible for the non-expert. Automated machine learning (AutoML) is an attempt to solve the problem of expertise by providin…

Techno-Economic Planning of Spatially-Resolved Battery Storage Systems in Renewable-Dominant Grids Under Weather Variability
Seyed Ehsan Ahmadi, Elnaz Kabir, Mohammad Fattahi, Mousa Marzband, Dongjun Li
https://arxiv.org/abs/2508.12526

Techno-Economic Planning of Spatially-Resolved Battery Storage Systems in Renewable-Dominant Grids Under Weather Variability
The ongoing energy transition is significantly increasing the share of renewable energy sources (RES) in power systems; however, their intermittency and variability pose substantial challenges, including load shedding and system congestion. This study examines the role of the battery storage system (BSS) in mitigating these challenges by balancing power supply and demand. We optimize the location, size, and type of batteries using a two-stage stochastic program, with the second stage involving …

Identifying high-impact consumers' behavioural changes for flexibility and demand reduction in a net-zero energy system
Parisa Rahdan, Mirko Sch\"afer, Ana Bel\'en Crist\'obal L\'opez, Marta Victoria
https://arxiv.org/abs/2508.04414

Identifying high-impact consumers' behavioural changes for flexibility and demand reduction in a net-zero energy system
Achieving decarbonization across energy sectors requires demand-side transformation such as behavioural changes and end-use efficiency improvements to complement supply-side technological shifts. However, changing consumption patterns is challenging, and implementing efficiency measures requires time and investment, highlighting the need to prioritize strategies. We address this prioritization using a high-resolution model of the European energy system under net-zero emissions, assessing the sy…

Social Welfare in Battery Charging Games
Simon Krogmann, Pascal Lenzner, Alexander Skopalik, Tobias Str\"aubig
https://arxiv.org/abs/2508.06320 https://

Social Welfare in Battery Charging Games
The recent rise of renewable energy produced by many decentralized sources yields interesting market design challenges for electrical grids. Balancing supply and demand in such networks is both a temporal and spatial challenge due to capacity constraints. The recent surge in the number of household-owned batteries, especially in regions with rooftop solar adoption, offers mitigation potential but often acts misaligned with grid-level objectives. In fact, the decision to charge or discharge a ho…

Preparing for the worst: Long-term and short-term weather extremes in resource adequacy assessment
Aleksander Grochowicz, Hannah C. Bloomfield, Marta Victoria
https://arxiv.org/abs/2508.05163

Preparing for the worst: Long-term and short-term weather extremes in resource adequacy assessment
Security of supply is a common and important concern when integrating renewables in net-zero power systems. Extreme weather affects both demand and supply leading to power system stress; in Europe this stress spreads continentally beyond the meteorological root cause. We use an approach based on shadow prices to identify periods of elevated stress called system-defining events and analyse their impact on the power system. By classifying different types of system-defining events, we identify cha…

Impact of COVID-19 on The Bullwhip Effect Across U.S. Industries
Alper Saricioglu, Mujde Erol Genevois, Michele Cedolin
https://arxiv.org/abs/2506.06368 ht…

Impact of COVID-19 on The Bullwhip Effect Across U.S. Industries
The Bullwhip Effect, describing the amplification of demand variability up the supply chain, poses significant challenges in Supply Chain Management. This study examines how the COVID-19 pandemic intensified the Bullwhip Effect across U.S. industries, using extensive industry-level data. By focusing on the manufacturing, retailer, and wholesaler sectors, the research explores how external shocks exacerbate this phenomenon. Employing both traditional and advanced empirical techniques, the analys…

This https://arxiv.org/abs/2505.23847 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership. Yet, cross-domain collaboration shatters the unified trust assumptions behind current alignment and containment techniques. An agent benign in isolation may, when receiving messages from an untrusted peer, leak secrets or viola…

Virtual Trading in Multi-Settlement Electricity Markets
Agostino Capponi, Garud Iyengar, Bo Yang, Daniel Bienstock
https://arxiv.org/abs/2508.11979 https://

Virtual Trading in Multi-Settlement Electricity Markets
In the Day-Ahead (DA) market, suppliers sell and load-serving entities (LSEs) purchase energy commitments, with both sides adjusting for imbalances between contracted and actual deliveries in the Real-Time (RT) market. We develop a supply function equilibrium model to study how virtual trading-speculating on DA-RT price spreads without physical delivery-affects market efficiency. Without virtual trading, LSEs underbid relative to actual demand in the DA market, pushing DA prices below expected …

Integrating Upstream Supply Chains into Generation Expansion Planning
Boyu Yao, Andrey Bernstein, Yury Dvorkin
https://arxiv.org/abs/2508.03001 https://arx…

Integrating Upstream Supply Chains into Generation Expansion Planning
Rising electricity demand underscores the need for secure and reliable generation expansion planning that accounts for upstream supply chain constraints. Traditional models often overlook limitations in materials, manufacturing capacity, lead times for deployment, and field availability, which can delay availability of planned resources and thus to threaten system reliability. This paper introduces a multi-stage supply chain-constrained generation expansion planning (SC-GEP) model that optimize…

Robust Vehicle Rebalancing with Deep Uncertainty in Autonomous Mobility-on-Demand Systems
Xinling Li, Xiaotong Guo, Qingyi Wang, Gioele Zardini, Jinhua Zhao
https://arxiv.org/abs/2507.04520

Robust Vehicle Rebalancing with Deep Uncertainty in Autonomous Mobility-on-Demand Systems
Autonomous Mobility-on-Demand (AMoD) services offer an opportunity for improving passenger service while reducing pollution and energy consumption through effective vehicle coordination. A primary challenge in the autonomous fleets coordination is to tackle the inherent issue of supply-demand imbalance. A key strategy in resolving this is vehicle rebalancing, strategically directing idle vehicles to areas with anticipated future demand. Traditional research focuses on deterministic optimization…

This https://arxiv.org/abs/2503.23604 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

The optimum mix of storage and backup in a highly renewable, highly reliable European electricity grid
We estimate the variability of solar and wind energy generation potential in Europe over a 43 year period between 1980-2022 with the MERRA-2 reanalysis datasets. We compare the estimated supply potential to hourly demand data from 36 European countries to calculate the reliability of a highly renewable electricity grid in Europe. We find that in cost-optimised scenarios with onshore wind, solar and storage, but no natural gas, reliably meeting the last 1% of demand represents 36% of the entire …

Mean-Field-Type Game Theory with Rosenblatt Noise
Hamidou Tembine, Tyrone E. Duncan, Bozenna Pasik-Duncan
https://arxiv.org/abs/2506.08025 https://

Mean-Field-Type Game Theory with Rosenblatt Noise
We study the integration of Rosenblatt noise into stochastic systems, control theory, and mean-field-type game theory, addressing the limitations of traditional Gaussian and Markovian models. Empirical evidence from various domains, including water demand, e-commerce, power grid operations, wireless channels, and agricultural supply chains, demonstrates the prevalence of non-Gaussian characteristics such as skews, heavy tails and strong long-range dependencies. The Rosenblatt process, a non-Gau…

Quantitative Indices for Improving Metro Load Curve, Using Distributed Generation
Masoud Behbahani, Alireza Fereidunian
https://arxiv.org/abs/2506.08975 ht…

Quantitative Indices for Improving Metro Load Curve, Using Distributed Generation
This paper promises the idea of using DG (Distributed Generation) to improve the Metro load curve. Public transportation systems are often based on gasoline and diesel. However, with the gradual development in usage of the Metro and monorail, a new load with heavy demand, inappropriate load curve and middle LF (Load factor) is added to the electricity grid. In addition to supply problem of this massive consumer, the Metro load curve is another problem, which has a relatively low LF. Furthermore…

Consumption Stimulus with Digital Coupons
Ying Chen, Mingyi Li, Jiaming Mao, Jingyi Zhou
https://arxiv.org/abs/2507.01365 https://arx…

Consumption Stimulus with Digital Coupons
We study consumption stimulus with digital coupons, which provide time-limited subsidies contingent on minimum spending. We analyze a large-scale program in China and present five main findings: (1) the program generates large short-term effects, with each $\yen$1 of government subsidy inducing $\yen$3.4 in consumer spending; (2) consumption responses vary substantially, driven by both demand-side factors (e.g., wealth) and supply-side factors (e.g., local consumption amenities); (3) The larges…