Energy systems are transitioning towards a decentralized and decarbonized paradigm with the integration of distributed renewable energy sources. Blockchain smart contracts have the increasing potential to facilitate the transition of energy systems due to the natures of automation, standardization, and self-enforcement. This paper proposes a Blockchain smart contracts based platform to manage the grid connection for both large scale generation companies and individual prosumers (both producers and consumers). Through evaluating the capacity margin and carbon intensity for each substation or feeder in power networks, the incurred connection fee and low carbon incentive are formulated for incentivizing the local energy balance and connection of renewable energy sources. Case studies testify the effectiveness for encouraging the low carbon grid connection.
The possibilities to involve small-scale prosumers for ancillary services in the distribution grid through aggregators and local flexibility markets question whether it is profitable for prosumers to oversize proactively. In this analysis, a Python model is developed to identify the cost-optimal operation plan of the PV-battery system and to evaluate the device flexibility. An economic assessment is carried out to derive the cost-benefit of sizing based on the mean electricity price. A sensitivity analysis is performed with the above results to study the profitable sizing of PV battery systems with flexibility services. The results show a promising advantage of oversizing although limitations prevail with the extent of flexibility services offered.
Ammonia has become a chemical of interest for the economic distribution and storage of hydrogen. Utilization of this molecule has been conceived in systems that range from small Fuel Cells to large gas turbines and furnaces. Ammonia characteristics enable the reduction of carbon emissions whilst ensuring long term storage and distribution of hydrogen produced from renewable sources. However, the use of ammonia as a combustion fuel also presents various issues mainly related to low flame speed and elevated nitrogen-based emissions. Therefore, further understanding of this molecule and its combustion characteristics is required before replacement of fossil fuels using ammonia can be accomplished at large scale. Therefore, this work presents a series of experiments that depict the characteristic profiles of various ammonia/hydrogen/methane blends intended to serve as replacement of pure fossil-based fuelling sources. The study is approached through a generic tangential swirl burner which has been commissioned to burn a great variety of blends at various power outputs. Temperatures, operability, chemiluminescence of various species (OH*, NH2*, CH* and NH*), spectrometry profiles, and emissions were determined for comparison purposes at various equivalence ratios and blending conditions.
The feasibility of the global energy transition may rest on the ability of nations to harness hydrogen’s potential for cross-sectoral decarbonization. At the national level, hydrogen can help mitigate the carbon footprint of the residential sector, especially in countries historically reliant on natural gas for heating and cooking. Despite cause for optimism, the domestic hydrogen transition faces multiple barriers, which reflect the broader challenges of deploying hydrogen technologies at scale across the industrial, commercial, and residential sectors. However, to date, scholars have scarcely examined how barriers such as safety, costs, and regulation may converge and interact. This deficit is especially pronounced in the case of Hydrogen Homes (HHs), which has a brief research history limited mostly to the UK context. Adopting a sociotechnical transition approach grounded in multi-level thinking, this paper proposes a theoretical framework for addressing the multi-dimensional challenges of the domestic hydrogen transition. Applying this framework to the UK context, this paper highlights distinct interrelationships that cut across sociotechnical dimensions, which will need to be confronted if ‘hydrogen hopes’ are to be realized.
As a result of global warming, the frequency of bad weather events has increased raptly, but so has the demand for more reliable power supply. This study investigates the Swedish power distribution system’s resilience towards certain weather conditions such as wind, lightning, rain etc. The input data is all unplanned disturbances gathered from the Swedish energy companies (Energiföretagen Sverige) between 2015 and 2019. After sorting and analyzing the data, the results are then compared to the weather data from SMHI (Swedish Meteorological and Hydrological Institute). The results show that on average 21% of unplanned outages are related to weather conditions in Sweden. Of the weather phenomena studied, wind and lightning are significantly affecting the resilience of the power system. One way to prevent outages, especially in lower voltage distribution systems, where most disturbances occur, is to improve the maintenance of the system.
Demand side management (DSM) and demand
response (DR) is an area of the smart grid paradigm that
helps utilities shape the demand according to a predetermined load profile. In this paper, the state-of-theart of DR in literature is overviewed. This paper discusses
the various DR programmes, DR benefits and challenges,
new smart grid technologies for DR and recent DR
mathematical models in literature.
With the increasing demand for cooling systems for electronic devices, nanofluid-microchannel heat sinks (MCHSs) have emerged as a hot topic. However, solving the problem of nanoparticle deposition is key to bringing this technology to an industrial scale. Traditional research focuses on the chemical characters of stationary nanofluids. However, thermophysical factors also affect the deposition of flowing fluid. In order to analyse thermophysical characteristics of an Al2O3-water nanofluid in a straight microchannel, Brownian force was simulated using a discrete phase model (DPM). The results indicate that Brownian motion has a great impact on particle deposition. However, the influence of temperature on the mean free path could be ignored for nanofluids in the MCHS. The deposition rate decreased with increasing particle diameter, but the deposition rate reduced as the velocity increased. These results have a guiding significance when designing new microchannel structures and inform the best conditions to reduce deposition.
The present study numerically investigates the effects of the variations of thermal conductivity and viscosity with temperature on velocity and temperature fields. The simulation is performed in a two-dimensional steady channel flow. The velocity profile is first validated against its analytical solution for the case of constant properties. A good agreement between numerical and analytical solutions is observed. From a physical point of view, it is revealed that by increasing the temperature in liquids, the fluid elements near the high-temperature wall are moving faster compared to those adjacent to the low-temperature one.
Reducing the fluctuations of distributed energy grid connection, improving power grid stability together with the effective utilization of energy, is a key issue that needs to be solved urgently in the large-scale development of renewable energy. This paper establishes a three-level game model of a distributed energy trading network, including Nash bargaining game, cooperative game and Stackelberg game, to study the energy trading mechanism between prosumers within and between energy communities. At the same time, based on the Shapley value and Core value methods via the cooperative game theory, a profit distribution model for the cooperation of multiple energy communities alliance has been established. Further, two power grid stability indicators are proposed to quantitatively measure the role of the three-level game model in improving power grid stability. Furthermore, this study uses three distributed energy communities of Jiangsu Province in China as study cases to verify the effectiveness of the three-level game model. The results show that the establishment of a three-level game model in the distributed energy trading network can not only reduce the impact of distributed energy grid connection on the grid, improve the stability of the power grid and the effective utilization of energy, but also bring economic and environmental benefits to all prosumers and the whole distributed energy system. In addition, under the profit distribution mechanism of the alliance, the participants of the alliance can obtain the greatest economic benefits, ensuring the stability of the alliance and the fairness of the income distribution.
The conversion of biomass waste into bioenergy is one of the most important renewable energy production
strategies. However, the energy inputs and outputs for different conversion technologies have not been fully
comparatively evaluated. Herein, we developed a data-driven framework to optimize the process conditions of
conversion technologies, including hydrothermal carbonization, hydrothermal liquefaction, and hydrothermal gasification, anaerobic digestion (AD), pyrolysis, and gasification. Then the predictive properties of products from conversions based on optimal conditions were employed for following life-cycle energy profiles evaluation. The results showed that the developed machine learning models performed well with most of the R2 > 0.80 for all the targets from the six technologies. Energy profile evaluation indicated that the AD was the most potential one with respect to the energy return of investment by comparing with thermal conversions. The energy requirements from thermal conversions were mainly caused by the reactor heating
and feedstock drying for the hydrothermal and dry-thermal conversions, respectively.