Search Results (40)

This study introduces a novel tripartite evolutionary game model to analyze the strategic interactions among electric vehicle (EV) aggregators, local governments, and EV users in vehicle–grid interaction (VGI) markets. The core novelty lies in capturing bounded rationality and dynamic decision-making across the three stakeholders, revealing how policy incentives and market mechanisms drive the transition from disordered charging to bidirectional VGI. Key findings include the following: (1) The system exhibits five stable equilibrium points, corresponding to three distinct developmental phases of the VGI market: disordered charging (V0G), unidirectional VGI (V1G), and bidirectional VGI (V2G). (2) Peak–valley price differences are the primary driver for transitioning from V0G to V1G. (3) EV aggregators’ willingness to adopt V2G is influenced by upgrade costs, while local governments’ subsidy strategies depend on peak-shaving benefits and regulatory costs. (4) Increasing the subsidy differential between V1G and V2G accelerates market evolution toward V2G. The framework offers actionable policy insights for sustainable VGI development, while advancing evolutionary game theory applications in energy systems. Full article

The large-scale integration of renewable energy and electric vehicles(EVs) into power distribution systems presents complex operational challenges, particularly in coordinating market mechanisms with grid stability requirements. This study proposes a new dispatching method based on dynamic electricity prices to coordinate the relationship between the market and the physical characteristics of the power grid. The proposed approach introduces a multi-agent transaction model incorporating voltage regulation metrics and network loss considerations into market bidding mechanisms. For EV integration, a differentiated scheduling strategy categorizes vehicles based on usage patterns and charging elasticity. The methodological innovations primarily include an enhanced scheduling algorithm for coordinated optimization of renewable energy and energy storage, and a dynamic coordinated optimization method for EV clusters. Implemented on a modified IEEE test system, the framework demonstrates improved voltage stability through price-guided energy storage dispatch, with coordinated strategies effectively balancing peak demand management and renewable energy utilization. Case studies verify the system’s capability to align economic incentives with technical objectives, where time-of-use pricing dynamically regulates storage operations to enhance reactive power support during critical periods. This research establishes a theoretical linkage between electricity market dynamics and grid security constraints, providing system operators with a holistic tool for managing high-renewable penetration networks. By bridging market participation with operational resilience, this work contributes actionable insights for developing interoperable electricity market architectures in energy transition scenarios. Full article

With the rapid development of China’s electric vehicle industry, the influence mechanism of government policies on consumers’ purchase intentions has become a research focus. This study integrates the technology acceptance model (TAM) and SOR theory to propose four key driving factors: policy incentive, perceived usefulness, perceived ease of use, and test drive experience. Through stratified random sampling of 400 valid questionnaires in Shanghai, Beijing, Shenzhen, and Guangzhou, four cities with a high penetration rate of electric vehicles, the structural equation model (SEM) was used for empirical analysis. The results show that policy incentives have a significant impact on purchase intentions and play a mediating role through perceived usefulness and perceived ease of use; driving experience moderates the effects of perceived usefulness and perceived ease of use on purchase intentions. Based on the research results, this paper proposes a three-stage policy optimization path: strengthening the accuracy of fiscal and tax incentives in the short term, improving the visual construction of the charging network in the medium term, and establishing a network of test drive experience centers in the long term. The research conclusions provide a theoretical basis for the government to formulate differentiated electric vehicle promotion strategies and propose a “policy-technology-service” three-dimensional implementation plan for enterprises to optimize product design and improve user experience, so as to help the sustainable development of China’s electric vehicle market. Full article

This study addresses the growing global concern regarding electronic waste (e-waste) management, focusing on the challenges and potential solutions within the Russian Federation. This study employs a systematic approach, statistical analysis, and comparative studies to evaluate the current state of e-waste management, including its collection, transportation, recycling, and disposal. Data from Rosprirodnadzor and other regulatory bodies were analyzed to assess the dynamics of e-waste generation, recycling rates, and the implementation of best available technologies (BATs) through integrated environmental permits (IEPs). The study findings reveal a significant increase in e-waste generation (from 87,832 tons in 2019 to 113,372 tons in 2022, but decreased to 82,965 tons in 2023), with only a fraction being properly recycled (the amount of waste processed has decreased significantly: from 79,616 tons in 2019 to 11,569 tons in 2023), and highlight the inefficiencies in existing regional waste management systems (including monopolistic operators and inefficient infrastructure, with just six certified e-waste recyclers operating nationally). This study concludes that a comprehensive, regionally tailored e-waste management system, supported by financial mechanisms such as parafiscal charges, is essential for improving recycling rates and reducing the environmental impacts of e-waste. Key recommendations include QR-code labeling for traceability, expanded collection networks, and BAT-aligned permits to meet the 65% collection target set by EU Directive 2012/19/EU. Our findings underscore the urgency of scaling recycling capacity—currently 481,935 tons/year nationally—to match annual e-waste generation (1.4 million tons). The proposed system emphasizes the prioritization of ecological over economic considerations, aiming to create an effective system for e-waste management in Russia. The proposed hypothesis includes an effective e-waste management system that can be established through BAT-based processes, financial incentives, and systemic regional integration—but it requires empirical validation under real-world conditions. To achieve this, it is necessary to conduct a pilot implementation in a selected region. A pilot with partial infrastructure exists in Moscow (e.g., Ecopolis Corporation’s facilities) and integrates disjointed processes (collection → sorting → recycling) while monitoring key metrics (e.g., volume processed, cost per ton, stakeholder compliance). A 3-year evaluation period would provide actionable data for a nationwide rollout. Full article

Energy storage technology is a critical component in supporting the construction of new power systems and promoting the low-carbon transformation of the energy system. Currently, new energy storage in China is in a pivotal transition phase from research and demonstration to the initial stage of commercialization. However, it still faces numerous challenges, including incomplete business models, inadequate institutional policies, and unclear cost and revenue recovery mechanisms, particularly on the generation and grid sides. Therefore, this paper focuses on grid-side new energy storage technologies, selecting typical operational scenarios to analyze and compare their business models. Based on the lifecycle assessment method and techno-economic theories, the costs and benefits of various new energy storage technologies are compared and analyzed. This study aims to provide rational suggestions and incentive policies to enhance the technological maturity and economic feasibility of grid-side energy storage, improve cost recovery mechanisms, and promote the sustainable development of power grids. The results indicate that grid-side energy storage business models are becoming increasingly diversified, with typical models including shared leasing, spot market arbitrage, capacity price compensation, unilateral dispatch, and bilateral trading. From the perspectives of economic efficiency and technological maturity, lithium-ion batteries exhibit significant advantages in enhancing renewable energy consumption due to their low initial investment, high returns, and fast response. Compressed air and vanadium redox flow batteries excel in long-duration storage and cycle life. While molten salt and hydrogen storage face higher financial risks, they show prominent potential in cross-seasonal storage and low-carbon transformation. The sensitivity analysis indicates that the peak–valley electricity price differential and the unit investment cost of installed capacity are the key variables influencing the economic viability of grid-side energy storage. The charge–discharge efficiency and storage lifespan affect long-term returns, while technological advancements and market optimization are expected to further enhance the economic performance of energy storage systems, promoting their commercial application in electricity markets. Full article

This research presents an innovative blockchain-based solution for the charging and energy trading of electric vehicles (EVs). By combining the strengths of two prominent consensus mechanisms, Proof of Work (PoW) and Proof of Stake (PoS), the proposed system balances security, decentralization, and energy efficiency. PoW secures the blockchain, while PoS enhances energy efficiency and scalability, key factors in meeting the growing demand for EV infrastructure. The system’s decentralized nature allows for EV owners, charging stations, and stakeholders to interact and transact transparently, without relying on centralized entities. The research conducts a comprehensive simulation to assess the performance of the proposed hybrid blockchain model, demonstrating significant improvements in cost-effectiveness, scalability, and energy management. Additionally, dynamic pricing mechanisms within the blockchain enable real-time energy trading, optimizing charging times and balancing grid demand efficiently. Through the use of smart contracts, automated pricing adjustments, and incentive-driven user behaviors, the proposed system paves the way for more sustainable, cost-effective, and efficient energy solutions in the future. Full article

With the rapid development of electric vehicles (EVs) and charging facilities, EV charging guidance is currently mainly based on charging incentives. Without an in-depth exploration of the superimposed benefits to charging guidance caused by discharging incentives, it is difficult to maximize the benefits of charging station operators and to stimulate the enthusiasm of users to participate in the guidance. In this study, firstly, a traffic network model based on the Logit model is established, and the spatiotemporal distribution characteristics of EV users’ traveling demand based on the O-D matrix and the Monte Carlo Markov method are proposed. Secondly, we analyze the impact of charging and discharging incentive levels on users’ psychological responses to charging guidance. We assess battery degradation during irregular discharging processes of electric vehicles (EVs) while considering users’ personalized travel needs and anxiety levels. We propose a dual-incentive mechanism for charging and discharging to enhance users’ active participation in charging guidance. Then, we construct a model that incorporates users’ travel and waiting time costs, as well as the economic costs of charging and discharging. Subsequently, we consider the economic benefits for users under the discharging incentive mechanism and establish a user charging decision model based on prospect theory. Finally, considering the goal of maximizing the revenue of the charging station, a charging guidance strategy considering users’ participation in the charging and discharging incentive mechanism during the traveling process is proposed. The effectiveness of the EV charging guidance strategy under three different incentive scenarios is verified with comparative results. The proposed guidance strategy enhances operator revenue while taking user interests into account, achieving a 7% increase in operator revenue compared to a strategy that only considers charging incentives. This dual-incentive mechanism promotes operators’ enthusiasm for participating in vehicle-to-grid interactions. Full article

The global electricity demand from electric vehicles (EVs) increased by 3631% over the last decade, from 2600 gigawatt hours (GWh) in 2013 to 97,000 GWh in 2023. The global electricity demand from EVs will rise to 710,000 GWh by 2030. These EVs will depend on smart grids (SGs) for their charging requirements. Like EVs, SGs are a booming market. In 2021, SG technologies were valued at USD 43.1 billion and are projected to reach USD 103.4 billion by 2026. As EVs become more prevalent, they introduce additional complexity to the SG landscape, with EVs not only consuming energy, but also potentially supplying it back to the grid through vehicle-to-grid (V2G) technologies. The entry of numerous independent sellers and buyers, including EV owners, into the market will lead to intense competition, resulting in rapid fluctuations in electricity prices and constant energy transactions to maximize profit for both buyers and sellers. Blockchain technology will play a crucial role in securing data publishing and transactions in this evolving scenario, ensuring transparent and efficient interactions between EVs and the grid. This survey paper explores key research challenges from an engineering design perspective of SG operation, such as the potential for voltage instability due to the integration of numerous EVs and distributed microgrids with fluctuating generation capacities and load demands. This paper also delves into the need for a synergistic balance to optimize the energy supply and demand equation. Additionally, it discusses policies and incentives that may be enforced by national electricity carriers to maintain grid reliability and manage the influx of EVs. Furthermore, this paper addresses emerging issues of SG technology providing primary charging infrastructure for EVs, such as incentivizing green energy, the technical difficulties in integrating diverse hetero-microgrids based on HVAC and HVDC technologies, challenges related to the speed of energy transaction processing during fluctuating prices, and vulnerabilities concerning cyber-attacks on blockchain-based SG architectures. Finally, future trends are discussed, including the impact of increased EV penetration on SGs, advancements in V2G technologies, load-shaping techniques, dynamic pricing mechanisms, and AI-based stability enhancement measures in the context of widespread SG adoption. Full article

Integrating electric vehicles (EVs) into the coupled power distribution network (PDN) and transportation network (TN) presents substantial challenges. This paper explores three key areas in EV integration: charging/discharging scheduling, charging navigation, and charging station planning. First, the paper discusses the features and importance of EV integrated traffic–power networks. Then, it examines key factors influencing EV strategy, such as user behavior, charging preferences, and battery performance. Next, the study establishes an EV charging and discharging model, with particular emphasis on the complexities introduced by factors such as pricing mechanisms and integration approaches. Furthermore, the charging navigation model and the role of real-time traffic information are discussed. Additionally, the paper highlights the importance of multi-type charging stations and the impact of uncertainty on charging station planning. The paper concludes by identifying significant challenges and potential opportunities for EV integration. Future research should focus on enhancing coupled network modeling, refining user behavior models, developing incentive pricing mechanisms, and advancing autonomous driving and automated charging technologies. Such efforts will be essential for achieving a sustainable and efficient EV ecosystem. Full article

The electric vehicle (EV) industry has emerged in response to the necessity of reducing greenhouse gas emissions and combating climate change. However, as the number of EVs increases, EV charging networks are confronted with considerable obstacles pertaining to accessibility, charging time, and the equilibrium between electricity demand and supply. In this paper, we present a techno-economic analysis of EV charging stations (EVCSs) by building type. This analysis is based on public EVCS data and considers both standalone local grid operation and integrated operation of distributed energy resources (DERs) and the local grid. The analysis has significant implications for the management of the electricity grid and the utilization of sustainable energy, and can result in economic benefits for both residential, commercial, and public buildings. The analysis indicates that integrating DERs with the local grid at EV charging stations can reduce local grid usage relative to EV demand. Nevertheless, there are also complexities, such as initial investment and maintenance costs, especially the weather-dependent performance variability of solar, which require financial support mechanisms, such as subsidies or tax incentives. Future research should focus on different DER integrations, regional and seasonal variability, user behavior, installation location, policy and regulatory impacts, and detailed capital expenditure analysis. Such research will advance DER and EVCS integration and contribute to increasing the efficiency and sustainability of urban energy systems. Full article

Volumetric-based pricing for irrigation water was introduced as part of a comprehensive reform of agricultural water prices in China. However, operational deficiencies and farmers’ lack of willingness to adopt the volumetric pricing policy (VPP) hinder the coordinated implementation of the reform. To address these practical challenges, we employed a binary logistic regression model to analyse farmers’ acceptance of the VPP for agricultural irrigation water usage in Suqian City, Jiangsu Province. A variable set was formed by selecting potential variables from four types of influencing factors: the subject (water users), the object (water supply departments), natural condition factors, and social condition factors. Our results revealed seven factors that determine whether farmers accept the VPP: irrigation water measurement at the water inlet of a lateral canal, the irrigation water-saving rewards scale, enforcement efforts of charging by volume, the irrigation water source type, the use of agricultural water-saving for trade, financial investment in water-saving technology, and the level of irrigation water pricing. We determined the degree of influence of the seven determining factors, among which the irrigation water-saving rewards scale and enforcement efforts of charging by volume most influence farmers’ decisions on the VPP for irrigation water. The results of this study can be used as a reference for innovation of the agricultural water-saving system in Suqian City, optimisation of an accurate fiscal subsidy scale, quantification of irrigation water rights, optimisation of the measurement facility layout, and effective implementation of agricultural water rights trading. More broadly, this study provides a valuable reference for solving the difficulties faced in the comprehensive reform of agricultural water pricing in China, which includes irrigation water pricing mechanisms, management systems, subsidy mechanisms, and water-saving incentive measures. Full article

In wireless sensor networks, terminal devices with restricted cost and size have limited battery life. Meanwhile, these energy-constrained devices are not easy to access, especially when the terminal devices are located in severe environments. To recharge the energy-constrained devices and extend their network service time, unmanned aerial vehicles (UAVs) equipped with wireless power chargers are leased by the third-party control center. To incent the participation of UAVs with different charging capabilities and ensure the strategy-proofness of the incentive mechanism, a hidden information based contract theory model, specifically adverse selection, is introduced. By leveraging individual rationality and incentive compatibility, a contract theory based optimization problem is then formulated. After reducing redundant constraints, the optimal contract items are derived by Lagrangian multiplier. Finally, numerical simulation results are implemented to compare the prepared algorithm with three other baselines, which validates the effectiveness of our proposed incentive mechanism. Full article

The electrification of personal transportation holds great potential for lowering greenhouse gas emissions and reducing climate change. The promise of electric vehicles (EVs) to serve these goals has resulted in a broad range of supporting policies aimed at encouraging widespread EV adoption at both the state and federal levels in the United States and around the world. While the EV revolution and prospects of a world with ubiquitous EVs are impacting various industries and many aspects of daily life, strategic interactions between the power grid and EVs are crucial for a successful energy transition. However, managing the interplay between EVs and the power grid remains a challenge. Motivated by that tension, this paper surveys a variety of solutions, policies, and incentives that are focused on effectively managing EV charging behaviors. The paper’s objective is to explore these tools to ensure that EV owners have ultimate control over their personal vehicles while simultaneously allowing the power grid to mitigate adverse network impacts. Furthermore, this paper examines the role of charging infrastructure technology and its strategic placement in facilitating the seamless integration of EVs into the grid. Additionally, the paper highlights financial mechanisms associated with EV integration and discusses the consequences of these mechanisms. Full article

Industrial facilities are seeking new strategies that help in providing savings mechanisms for demand charges. Demand charges are the charges incurred by industrial facilities as a result of power usage. Thermal energy storage has advanced significantly with lots of new applications, garnering the interest of many industrial facilities. These applications could be used to shave the industrial facilities’ peak electric demand and reduce their demand charges. This paper aims to demonstrate the efficacy of thermal energy storage in reducing demand charges and highlight new developments in the integration of smart control systems with thermal energy storage. The study compares energy consumption and peak demand for a facility equipped with and without thermal energy storage tanks using a fixed schedule for charging and discharging. Additionally, the paper examines the impact of incorporating a smart controller to determine when to charge and discharge the tank based on the facility’s real-time power usage and a given setpoint. The results indicate cost savings from the use of thermal energy storage tanks under two proposed scenarios, reflected in the reduced cost of power consumption for the studied facility. The incorporation of a smart controller with the thermal energy storage tank in the facility studied could provide estimated savings of 3.3% per year of power consumption charges, without considering the contribution of any incentives. The estimated savings provided by the fixed schedule scenario are 2.7% per year. Full article

The new retail focuses on the high integration between online and offline channels. The main problems faced by the development of the new retail are the interest balance of all decision subjects, the pricing strategy, and the coordination of online and offline channels. This paper considers the effect of the new retail firms’ delivery time and establishes a two-part tariff contract to study the decision-making and coordination of the new retail fresh products supply chain. This paper constructs cooperative and non-cooperative models and employs the cooperative model as the benchmark case to realize the coordination. It is found that when the delivery time has little effect on the market demand, the offline store often should pay more fixed charges to the new retail firm. With the increased impact of delivery time on market demand, the fixed charges paid by the offline store become smaller. Under the coordination decision model, the offline store pays fixed charges to compensate for the new retail firm’s early delivery costs, but its interests still increase compared with the decentralized decision model. This study models the time-dependent demand for fresh products and proposes an incentive mechanism to coordinate the new retail fresh products’ supply chain; further, it demonstrates that the prices can be significantly decreased with the designed contract, and all the supply chain members can benefit from Pareto improvement. Full article