Peak Demand Research Articles

Techno-economic impact analysis for renewable energy-based hydrogen storage integrated grid electric vehicle charging stations in different potential locations of Malaysia

This study investigates the techno-economic impacts analysis of renewable energy-based hybrid energy storage system integrated grid electric vehicles charging station (EVCS) in Malaysia. Focusing on three potential locations namely Pulau Pinang, Johor Bharu and Kuala Terengganu, the research aims to address the increasing electricity demand from the expanding electric vehicle (EV) infrastructure while mitigating grid instability issues caused by sudden load surges, increased electrical losses, and overload of high voltage devices that leads to power quality issues. Using the HOMER Pro platform, the study models and optimises an EVCS configuration-based hybrid energy storage system that incorporates renewable energy sources (RES) such as photovoltaic (PV), wind turbines (WT), lithium-ion (Li-ion) batteries, hydrogen (H2) tank, fuel cell (FC) and electrolysers considering various geographical and meteorological conditions. The hybrid energy storage configuration offers a long-term energy storage solution, surpassing current batteries' capabilities while providing a stable electricity supply for a sustainable EVCS system. The results demonstrated favourable outcomes, with the total Net Present Cost (NPC) ranging from $1.4 million to $3.4 million across all locations, and the Cost of Energy (COE) ranging from $0.03/kWh to $0.16/kWh. These findings suggest that the optimization methodology is adaptable for implementation in diverse locations with different meteorological conditions. This innovation is beneficial for developing renewable-based EVCS infrastructures, which can support economic growth in Malaysia. In addition, the study emphasizes the necessity of advanced control algorithms to manage power quality issues during peak demand and suggests future field trials to validate the system's real-world performance. Additionally, the optimized EVCS-based hybrid energy storage system contributes to reducing carbon dioxide (CO2) emissions, promoting a cleaner environment and an eco-friendly energy ecosystem.

Alternating direction method of multipliers based distributed energy scheduling of grid connected microgrid by considering the demand response

Global warming, environmental degradation, clean energy production, intermittent, volatile, and unpredictable renewable energy sources (RES’s), occasional peak demand on the system necessitates energy management (EM). Demand response (DR) programs in the distribution network can be seen as one of the foundation stones in the future of EM. This article illustrates the need for EM using DR, its benefits, types of loads, clustering techniques, price-based demand response (PBDR) etc. To accomplish the EM goals and to attain the economic benefit, DR employs peak shifting, peak clipping, valley filling and load growth. However, the accumulation of large loads at low electricity prices creates local peaks, this phenomenon is referred to as payback or rebound effect (RE). The occurrence of RE at low price zone heightens the volatility of market clearing price (MCP) and the operational cost of the microgrid. Inherently, the scheduled inelastic consumers at low price zone suffer from increased MCP and therefore, the total consumer tariff (TCT). The occurrence of RE depends on the load curve, peak to average ratio, electricity price and the percentage of interruptible loads present in the system. Unclear pricing methods impede the participation of customers in DR events. Moreover, majority of techniques presented in literature are of centralized frameworks that needs complex communication technologies. To fill these glitches the proposed work uses a simple distributed scheduling approach based on alternating direction method of multipliers (ADMM) to alleviate the energy management using an IEEE-18 bus system. The load factor increases from 0.79 to 0.83. Using DR lowers the peak power demand on the MG from 82 to 78 kW without compromising customer comfort or satisfaction. The TCT was lowered from scenario 1 to scenario 4 from 3058 to 2254 euros. The system's average demand dropped from 65.54 kW to 64.8 kW. IEEE-33 bus system was considered to assess the impact of RE on the MCP and TCT. Additionally, the marginal generator provides 72.51 kW of electricity in sub case 3 and 166.26 kW of power in sub case 2. Due to a decrease in power dispatch from the marginal generator, TCT increased from sub case 2 to sun case 3 by 11,046.41 rupees to 12,912.75 rupees. In contrast, TOC decreased from 6495.45 rupees to 6150.75 rupees from sub case 2 to sun case 3.

Why should imminent international funds for solar photovoltaics go to families and the private sector and not to the government to stop the electricity crisis in Lebanon?

In Lebanon, the failure to supply oil-based electricity was mostly due to flawed management, increasing costs of bills of private generators, the rise of fuel prices, and the absence of subsidies. In response, individuals have started funding small-scale rooftop PV (RPV) to increase the solar share beyond the national target while the government has struggled for years to pass bidding phases for 12 utility-scale PV (USPV). In addition to publicly unavailable details, specifications, assessments, and termination plans about the 12 solar farms, their geographical sitting was not technically evaluated. Therefore, this study mapped USPV suitability in Lebanon using a multi-criteria decision-making algorithm. Although the highly suitable lands can supply 40% of the total land needed to cover the peak demand, the areas were not equally distributed throughout the governorates. Even if USPV can help reach national solar targets, investing in public-related projects can be perilous, especially with historical patterns of inappropriate allocation of funding, political instability, and absence of accountability. Thus, investing in RPV can be more attractive due to its efficiency, grid independence, and flexibility and should be oriented primarily towards low-income families and small entrepreneurs and later to wealthier people to ensure social equity and welfare.

An empirical analysis of electric vehicle charging behavior based on real Danish residential charging data

In the last two years there has been a significant increase in the global adoption of electric vehicles (EVs). Particularly in Denmark, 40% of new vehicle registrations in 2023 were electric, marking a notable shift towards e-mobility. As a result, EV loading begins to constitute a large part of residential electricity demand. The concurrent increase in the interest for reduction in charging costs via demand response leads to a growing need for better understanding of charging behavior and its impact on consumption profiles. This works addresses the lack of up-to-date large-scale empirical studies on residential EV charging behavior. It presents a thorough analysis of all important charging characteristics based on a large set of 5534 Danish residential chargers between 2021 and 2023, providing unique insight in the effect of user-induced controlled charging. Our analysis shows the difference between actual charging profiles and those commonly used by distribution system operators in Denmark, and reveals the significant change over the span of one year with the doubling of peak demand per charger from 1.25 kW to 2.5 kW.

The potential of utilizing vertical borehole heat exchangers in residential buildings for the various climate zones of Saudi Arabia

Most of the literature concerning geothermal energy in Saudi Arabia has focused on power generation applications. This paper investigates the potential of utilizing ground-source heat pump (GSHP) with vertical borehole heat exchangers in residential buildings in the various climate zones and subsurface geologies of Saudi Arabia. Thermal loads of a typical residential building in Saudi Arabia were generated using eQuest software, then used in a model of GSHP system in TRNSYS. The performance and economics of the GSHP system was evaluated and compared with a typical air-source heat pump (ASHP) system for each location. The total borehole lengths in all zones were determined using the cooling load (the dominant load). The potential for employing GSHP systems was found to be not uniform across Saudi Arabia. The required length of the GHE ranged between 12 and 148 m/kW of cooling. The annual energy saving when employing GSHP instead of ASHP systems varied between 3 % to 19 %, and the building's electricity peak demand could be reduced between 5 % to 43 %. Although GSHPs reduced electrical and maintenance costs, their high drilling cost makes them economically unattractive under the present electric utility charge in Saudi Arabia.

Three-tier integrated demand-supply energy management for optimized energy usage in institutional building

Sustainable Energy Plan is an indispensable field of study in the context of Building Energy Management (BEM) which yearns for a cutting-edge technique to raise consumers’ level of contentment with energy usage. This paper introduces a three-tier strategic approach for demand cum supply side management at the prosumer end named TID-SEM (Three-tier Integrated Demand cum Supply Energy Management) framework. The framework commences with data collection, machine learning, and Random Forest classifier-based Demand side management to reduce peak demand. Followingly, a feasibility study on available sources (Solar PV + Battery + Diesel Generator + Grid) was done using the HOMER simulator. The quality techno-enviro-economic shows distinguished optimal one under each criterion. Ultimately to overcome, an ideal computative multicriteria decision-making approaches Fuzzy Analytic Hierarchy Process, the Fuzzy Preference Ranking Organization Method for Enrichment Evaluations, and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution employed to highlight the most optimal configuration. The study focuses on a department building within a higher education institution in the Madurai district, Tamil Nadu, India. On implementing the TID-SEM, ‘PV + Grid’ after DSM configuration was ranked as the most optimum. Lastly, a sensitivity analysis was conducted to evaluate the techno-enviro-economic impact of uncertain parameters on the optimal configuration, ensuring the robustness of the proposed framework.

The effects of climate and climate change on electric vehicle charging demand in Toronto, Canada

Battery electric vehicles (BEVs) influence total and peak electricity demand, but few studies account for climate when studying these effects. This study quantifies BEV charging demand in the Greater Toronto and Hamilton Area using a detailed trip level approach, accounting for the effect of present and future temperatures on BEV energy consumption. The impact of temperature on charging demand was largest in winter. In 2019, charging demand increases by 52% on an average January day, and up to 82% on extreme days (relative to mild weather conditions). At 30% penetration, BEVs increase peak demand on January’s coldest day by 600–3600 MW (3%–5%), of which 300–700 MW is driven by temperature, depending on the charging scenario. Climate change introduces small changes, increasing summer and decreasing winter charging demand. These results highlight the importance of adjusting for regional climate variation and temperature extremes when analyzing the impact of BEVs on the grid.

A deep learning approach for fairness-based time of use tariff design

Time of use (TOU) tariffs aim to shape demand by reducing peak demand. This is significant given the increasing pressure on peak energy supply, particularly in Europe, where peak gas prices have dramatically increased bills. This study defines fairness as a reform measure that carries both distributional and transitional effects on different income users and utilities. A flexible fairness-driven TOU tariff design is proposed, which (1) assigns households to different tariffs by income and estimated price responsiveness calculated from a long short-term memory (LSTM)-based counterfactual electricity consumption model and (2) filters potential tariffs to simultaneously lower total costs, distribute cost savings progressively, and maintain constant utility profitability. Using the 2009-10 Irish Smart Metering Trial based on more than 2000 users, under the proposed frameworks (b) and (c) with fairness constraints, no lower-income users have been observed to pay a higher bill than the higher-income users on average. Specifically, lower-income groups can achieve 8% and 10% bill reduction, respectively, under framework (b) partial bill protection and framework (c) full bill protection for the lower-income users. Our fairness-based TOU framework has successfully achieved fairness of distribution and transition, paving the way for a more equitable and sustainable electricity system.

Enabling industrial decarbonization: A MILP optimization model for low-carbon hydrogen supply chains

This study develops a an optimization model focused on the layout and dispatch of a low-carbon hydrogen supply chain. The objective is to identify the lowest Levelized Cost of Hydrogen for a given demand. The model considers various elements, including electricity supply from the local grid and renewable sources (photovoltaic and wind), alongside hydrogen production, compression, storage, and transportation to end users. Applied to an industrial case study in Sweden, the findings indicate that the major cost components are linked to electricity generation and investment in electrolyzers, with the LCOH reaching 5.2 EUR/kgH2 under typical demand conditions. Under scenarios with higher peak demands and greater demand volatility, the LCOH increases to 6.8 EUR/kgH2 due to the need for additional renewable energy capacity. These results highlight the critical impact of electricity availability and demand fluctuations on the LCOH, emphasizing the complex interdependencies within the hydrogen supply chain. This study provides valuable insights into the feasibility and cost-effectiveness of adopting hydrogen as an energy carrier for renewable electricity in the context of decarbonizing industrial processes in the energy system.

Optimizing Grid Performance in Trinidad and Tobago: The Role of Vehicle-to-Grid (V2G) Technology

This study investigates the impact of integrating 10,000 battery electric vehicles (BEVs) into the electrical grid of Trinidad and Tobago through three charging scenarios: non-incentivized charging, charging at work, and a Vehicle-to-Grid (V2G) program. The results reveal that non-incentivized charging exacerbates peak demand and grid strain, while workplace charging provides only modest peak demand mitigation. In contrast, the V2G scenario significantly reduces peak load impacts and enhances grid stability by leveraging BEVs as dynamic energy storage units that contribute to grid services during high-demand periods. The study proposes a V2G tariff scheme that includes compensation for battery degradation, aiming to incentivize participation and offset potential costs. Economic analysis shows that while V2G involves higher per-MWh costs than conventional storage technologies, it avoids the need for substantial capital investment in static energy infrastructure, presenting a cost-effective solution for energy management in island nations. The findings highlight the potential of V2G technology to facilitate sustainable energy transitions, emphasizing its role in enhancing grid resilience, optimizing renewable energy usage, and reducing carbon emissions. This research underscores the transformative potential of V2G systems as critical enablers of sustainable energy strategies in regions facing similar challenges to Trinidad and Tobago.

From PV to EV: Mapping the Potential for Electric Vehicle Charging with Solar Energy in Europe

The electrification of the transport sector is a key element in decarbonizing our societies. However, energy systems will have to cope with additional electricity demand due to the charging needs of electric vehicles (EVs) together with the integration of fluctuating renewable energy sources. Shifting EV charging during the day can contribute to absorbing photovoltaic (PV) production peaks and limiting the additional demand during peak periods. The EV batteries can then be discharged to the grid or home during the evening or other demand peaks. We developed a new methodology to quantify the flexibility gained from the EV-PV coupling from local mobility habits and local (or decentralized) photovoltaic production. Our approach first focuses on the geospatial modelling of mobility habits across Europe to quantify energy demand for charging. The charging demand is then distributed between residential areas, workplaces and points of interest (shopping, leisure, etc.) to model the spatiotemporal distribution of energy needs. We show and discuss a practical case in Copenhagen illustrating the impact of charging behaviour for three different scenarios. The methodology is implemented as a calculation module in the open-source online geographic tool for energy transition planning, Citiwatts.

Optimal Placement and Capacity of BESS and PV in EV Integrated Distribution Systems: The Tenth Feeder of Phitsanulok Substation Case Study

Installing a battery energy storage system (BESS) and renewable energy sources can significantly improve distribution network performance in several aspects, especially in electric vehicle (EV)-integrated systems because of high load demands. With the high costs of the BESS and PV, optimal placement and capacity of them must be carefully considered. This work proposes a solution for determining the optimal placement and capacity of a BESS and photovoltaic (PV) in a distribution system by considering EV penetrations. The objective function is to reduce system costs, comprising installation, replacement, and operation and maintenance costs of the BESS and PV. The replacement cost is considered over 20 years, and the maintenance and operation costs incurred in the distribution system include transmission line loss, voltage regulation, and peak demand costs. To solve the problem, two metaheuristic algorithms consisting of particle swarm optimization (PSO) and the African vulture optimization algorithm (AVOA) are utilized. The tenth feeder of Phitsanulok substation 1 (PLA10), Thailand, which is a 91-bus distribution network, is tested to evaluate the performance of the proposed approach. The results obtained from the considered algorithms are compared based on distribution system performance enhancement, payback period, and statistical analysis. It is found from the simulation results that the installation of the BESS and PV could significantly minimize system cost, improve the voltage profile, reduce transmission line loss, and decrease peak demand. The voltage deviation could be reduced by 86%, line loss was reduced by 0.78 MW, and peak demand could be decreased by 5.706 MW compared to the case without BESS and PV installations.

The Role of Domestic Heat Pumps in Providing Flexibility to the UK Electricity System

Widespread adoption of residential heat pumps is predicted to create challenges for national and local electricity systems. Flexible operation of heat pumps could help smooth peak demand and better utilise renewables. Achieving these benefits involves many stakeholders from the heat pump and electricity sectors with different perspectives and expectations. This work brought together 52 experts from different parts of the UK system to discuss and debate the role of heat pump flexibility in a decarbonised electricity system in 2035. A co-production research model was adopted, designed to integrate diverse forms of knowledge and perspectives in the co-production of knowledge on heat pump flexibility. A series of participatory activities were undertaken including a one-day workshop. Elements of a common vision emerged, such as the anticipated widespread flexible operation of heat pumps as the cheapest way of running a heat pump and the likelihood of a highly automated and remote-controlled manner of operation. Disagreements and unknowns also emerged. This work aims to support stakeholders in planning for the social, technical and economic aspects of flexible heat pump operation in their own organisations.

Frequency and intensity of maximal and submaximal demanding scenarios in U19 professional soccer players

ABSTRACT This study examined the frequency of the most demanding scenarios (MDS) during official soccer matches using rolling averages over 1, 5, and 10 min. Forty-two Under-19 players from different positions (central defenders, full-backs, central midfielders, wide midfielders, offensive midfielders, and forwards) were monitored across 27 matches using GPS to track distance covered, high-speed running, sprint distance, accelerations, and decelerations. Intensity thresholds were established based on percentiles (0–25, 25–50, 50–75, 75–100, and ≥100). The main findings suggest that: (i) Peak Demands occur in less than 1% of all time windows and variables for all positions; (ii) Most efforts occur below peak demands, with around 95% for high-speed running and sprint distance, and 85% for accelerations, decelerations, and total distance; (iii) Significant differences in intensity distributions were found between positions, particularly at medium-low and high intensities. Regarding training prescription, relying solely on MDS may be limited, highlighting the need to supplement MDS with other metrics for a comprehensive understanding of match demands. This approach ensures better-informed training programs for soccer players.

Smart Operation Control of Power and Heat Demands in Active Distribution Grids Leveraging Energy Flexibility

Demand flexibility plays a crucial role in mitigating the intermittency of renewable power sources. This paper focuses on an active distribution grid that incorporates flexible heat and electric demands, specifically heat pumps (HPs) and electric vehicles (EVs). Additionally, it addresses photovoltaic (PV) power generation facilities and electrical batteries to enhance demand flexibility. To exploit demand flexibility from both heat and electric demand, along with the integration of PVs and batteries, Control and Communication Mechanisms (CCMs) are formulated. These CCMs integrate demand flexibility into the distribution grids to obtain economic benefits for private households and, at the same time, facilitate voltage control. Concerning EVs, the paper discusses voltage-based droop control, scheduled charging, priority charging, and up-/down-power regulation to optimize the charging and discharging operations. For heat demands, the on-off operation of the HPs integrated with phase change material (PCM) storage is optimized to unlock heat-to-power flexibility. The HP controllers aim to ensure as much self-consumption as possible and provide voltage support for the distribution grid while ensuring the thermal comfort of residents. Finally, the developed CCMs are implemented on a small and representative community of an active distribution grid with eight houses using Power Factory software and DIgSILENT simulation language (DSL). This scalable size of the active distribution network facilitates the careful study of symbiotic interaction among the flexible load, generation, and different houses thoroughly. The simulation results confirm that the integration of flexible demands into the grid using the designed CCMs results in the grid benefiting from stabilized voltage control, especially during peak demand hours.

PEMFC Electrochemical Degradation Analysis of a Fuel Cell Range-Extender (FCREx) Heavy Goods Vehicle after a Break-In Period

With the increasing focus on decarbonisation of the transport sector, it is imperative to consider routes to electrify vehicles beyond those achievable using lithium-ion battery technology. These include heavy goods vehicles and aerospace applications that require propulsion systems that can provide gravimetric energy densities, which are more likely to be delivered by fuel cell systems. While the discussion of light-duty vehicles is abundant in the literature, heavy goods vehicles are under-represented. This paper presents an overview of the electrochemical degradation of a proton exchange membrane fuel cell integrated into a simulated Class 8 heavy goods range-extender fuel cell hybrid electric vehicle operating in urban driving conditions. Electrochemical degradation data such as polarisation curves, cyclic voltammetry values, linear sweep voltammetry values, and electrochemical impedance spectroscopy values were collected and analysed to understand the expected degradation modes in this application. In this application, the proton exchange membrane fuel cell stack power was designed to remain constant to fulfil the mission requirements, with dynamic and peak power demands managed by lithium-ion batteries, which were incorporated into the hybridised powertrain. A single fuel cell or battery cell can either be operated at maximum or nominal power demand, allowing four operational scenarios: maximum fuel cell maximum battery, maximum fuel cell nominal battery, nominal fuel cell maximum battery, and nominal fuel cell nominal battery. Operating scenarios with maximum fuel cell operating power experienced more severe degradation after endurance testing than nominal operating power. A comparison of electrochemical degradation between these operating scenarios was analysed and discussed. By exploring the degradation effects in proton exchange membrane fuel cells, this paper offers insights that will be useful in improving the long-term performance and durability of proton exchange membrane fuel cells in heavy-duty vehicle applications and the design of hybridised powertrains.

Current State and Future Potential of Energy Efficiency and Demand Side Management in the South African Context

This paper explores the current state and future potential of Energy Efficiency and Demand Side Management (EEDSM) in South Africa. With a heavy reliance on coal for electricity generation, South Africa faces significant environmental and sustainability challenges. Integrating renewable energy sources like wind, water, and solar (WWS) is crucial for reducing greenhouse gas emissions and ensuring energy security. The study highlights the importance of demand-side management in optimising energy consumption and mitigating peak demand pressures. The South African government has implemented various policies and regulatory frameworks to promote EEDSM, focusing on reducing energy consumption through technological innovations and strategic planning. Models such as the Five-Stage Model for Computer Technology Integration, the E-Capacity Model, and the Systemic Planning Model for ICT Integration provide structured approaches to integrating advanced technologies and practices into energy systems. The research includes a comprehensive analysis of South Africa's current energy mix, predominantly coal and nuclear, and projects a shift towards a diversified portfolio dominated by renewable sources by 2050. This transition is expected to create substantial employment opportunities and enhance energy efficiency. Case studies and success stories from both the public and private sectors underscore the economic and environmental benefits of EEDSM initiatives. South Africa can significantly improve its energy efficiency and sustainability by leveraging innovative energy technologies, such as smart grids and smart metering. The findings emphasise the need for continued investment in renewable energy and demand- side management to achieve a more resilient and efficient energy sector.

Optimal design of a hinge-spring-friction device for enhancing wind induced structural response of onshore wind turbines

Wind turbines are subjected to fluctuating wind loads leading to considerable forces and structural fatigue to the towers, ultimately affecting costs, performances, and lifespan, for the tower as well as for the foundation. To mitigate these issues, both in terms of peak and fatigue structural demand, this paper presents the development and optimization of a Hinge-Spring-Friction Device (HSFD) designed for onshore wind turbines. A decoupled numerical model of the wind turbine system incorporating the HSFD is first established. The wind load is modelled by means of the open-source software QBlade© accounting for different wind conditions. These loads are then applied to a FEM structural model of the wind turbine developed in Simulink© and optimized for computational efficiency. The optimal design parameters (strength and stiffness of the frictional and elastic part, respectively) of the HSFD are determined through a multi-objective constrained optimization algorithm, minimizing the peak base moment and total damage fatigue. The proposed framework is then applied to a NREL 5 MW wind turbine to provide an applicative example. The results show that the optimized HSFD can significantly reduce the fatigue damage and the base moment demand to the tower, so providing a really promising solution for the effective design of wind turbines as well as for the repowering of existing plants.

Development and performance evaluation of active insulation systems using solid-state thermal switches

Traditional building envelopes have passive insulation systems that cannot respond to dynamic changes in the environment. An Active Insulation System (AIS) consists of Active Insulation Materials (AIMs) that dynamically vary the thermal conductivity of the insulation system. Several researchers have evaluated the impact of AIS on building thermal and energy performance by using simulation tools. Up to 70% savings in annual heating and cooling energy and significant reductions in peak demand have been predicted for some climates with wall systems employing AIS. However, materials and assembly development still need a cost-effective product that achieves the required performance. In this study, we present the process of developing an AIS that we will install in a test hut for its performance evaluation. Minimum performance criteria of the AIS system are developed based on R-low/R-high ratio, required time and efficiency to switch states, and cost estimates. The following steps during this study are creating the concept to meet the requirements, predicting the performance via simulations, developing the experimental setup for bench-scale testing, and finally, constructing a full-scale wall assembly and monitoring the performance when exposed to environmental chamber tests. The selected approach uses off-the-shelf products to create an AIS that can switch R-value between 0.98 ft2·°F·h/BTU (0.173 m2·K/W) and 5.81 ft2·°F·h/BTU (1.02 m2·K/W) and have a switching time of less than one minute between R-high and R-low.

Vehicle-to-Vehicle Energy Trading Framework: A Systematic Literature Review

As transportation evolves with greater adoption of electric vehicles (EVs), vehicle-to-vehicle (V2V) energy trading stands out as an important innovation for managing energy resources more effectively as it reduces dependency on traditional energy infrastructures and, hence, alleviates the pressure on the power grid during peak demand times. Thus, this paper conducts a systematic review of the V2V energy trading frameworks. Through the included article analysis (n = 61), this paper discusses the state-of-the-art energy trading frameworks’ structure, employed methodologies, encountered challenges, and potential directions for future research. To the best of the authors’ knowledge, this is the first review explicitly focused on V2V energy trading. We detail four critical challenges to face while establishing the framework in current research, providing an overview of various methodologies, including auctions, blockchain, game theory, optimisation, and demand forecasting, that are used to address these challenges and explore their integration within the research landscape. Additionally, this paper forecasts the evolution of V2V energy trading, highlighting the potential incorporation of advanced and established technologies like artificial intelligence (AI), digital twins, and smart contracts. This review aims to encapsulate the existing state of V2V energy trading research and stimulate future advancements and technological integration within the field.