Proton Exchange Membrane Fuel Cell (PEMFC) has attracted widespread interest. In the present work, similarity analysis is adopted for a three-dimensional single-phase isothermal model of PEMFC to derive similarity criteria. Seven kinds of input criteria (Pi(1) similar to Pi(7)) are obtained, relevant to the fluid flow, pressure drop, flow resistance in a porous medium, activity loss, diffusion mass transfer, convective mass transfer and ohmic loss in PEMFC respectively. Dimensionless voltage and dimensionless current density are defined as two output criteria. Numerical verifications show that if the seven criteria keep their individual values with their components vary in a wide range, the dimensionless polarization curves keep the same with a deviation about 1%, showing the validity and feasibility of the present analysis. From the effect on the dimensionless polarization curve, sensibility analysis shows that the seven criteria can be divided into three categories: strong (Pi(4) and Pi(7), -94.9% similar to +349.2%), mild to minor (Pi(5) and Pi(6), -4.5% similar to +5.0%), and negligible (Pi(1), Pi(2) and Pi(3), -1.2% similar to +1.1%). The similarity analysis approach can greatly save computation time in modeling the output characteristics of PEMFC. (C) 2021 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.
This study presented an experimental investigation on solidification behavior of fluid saturated in highly porous open-cell copper foams. Particular attention has been made on the effect of pore parameters (pore density and porosity) on the solidification behavior. A purposely-designed apparatus was built for experimental observations. Results showed that the copper foam had a great effect on solidification and the full solidification time can be saved up to 50%, especially preventing the decrease in solidification rate during the later stage of phase change. The smaller the porosity is, the faster the solidification rate will be. Pore density was found to have little influence upon the solidification rate. In addition, the local natural convection does exist but it has a slight effect on solidification, leading to the slant of the solid-liquid interface.
Electrification poses a promising low-carbon or even zero-carbon transportation solution, serving as a strategic approach to reducing carbon emissions and promoting carbon neutrality in the transportation sector. Along the transportation electrification pathway, the goal of carbon neutrality can be further accelerated with an increasing amount of electricity being generated from renewable energies. The past decade observed the rapid development of battery technologies and deployment of electricity infrastructure worldwide, fostering transportation electrification to expand from railways to light and then heavy vehicles on roadways. In China, a massive number of electric buses have been employed and operated in dozens of metropolises. An important daily operations issue with these urban electric buses is how to coordinate their charging activities in a cost-effective manner, considering various physical, financial, institutional, and managerial constraints. This paper addresses a general charging scheduling problem for an electric bus fleet operated across multiple bus lines and charging depots and terminals, aiming at finding an optimal set of charging location and time decisions given the available charging windows. The charging windows for each bus are predetermined in terms of its layovers at depots and terminals and each of them is discretized into a number of charging slots with the same time duration. A mixed linear integer programming model with binary charging slot choice and continuous state-of-charge (SOC) variables is constructed for minimizing the total charging cost of the bus fleet subject to individual electricity consumption rates, electricity charging rates, time-based charging windows, battery SOC bounds, time-of-use (TOU) charging tariffs, and station-specific electricity load capacities. A Lagrangian relaxation framework is employed to decouple the joint charging schedule of a bus fleet into a number of independent single-bus charging schedules, which can be efficiently addressed by a bi-criterion dynamic programming algorithm. A real-world regional electric bus fleet of 122 buses in Shanghai, China is selected for validating the effectiveness and practicability of the proposed charging scheduling model and algorithm. The optimization results numerically reveal the impacts of TOU tariffs, station load capacities, charging infrastructure configurations, and battery capacities on the bus system performance as well as individual recharging behaviors, and justify the superior solution efficiency of our algorithm against a state-of-the-art commercial solver.
Electricity Systems in europe are experiencing major changes due to targets for renewable energy integration, reducing greenhouse gas emissions, and energy efficiency. Different studies show that there is a growing need for more flexibility and active stakeholder involvement at all levels (from small consumers to pan-European networks) to ensure the efficient and reliable operation of the electricity system, particularly to deal with growing volumes of renewable energy sources, from transmission-level wind and solar farms to household-level photovoltaic generation. Other key evolutions that aim to decarbonize the energy sector beyond electricity, such as those based on the electrification of energy end uses (e.g., the development of electric vehicles and the electrification of heating), are also expected to have a substantial impact.
Electric Vehicles (EVs) have achieved a significant development because of the continuous technology revolution and policy supports in recent years, which leads to a larger demand of charging stations. Strategies about how to find the optimal location for charging facilities are urgently needed in order to further assist the development of EVs. This paper focus on the return of investments on EV charging stations and proposes a Mixed Integer Linear Programming (MILP) model based on Geographic Information System (GIS) to identify the optimal location of charging stations in cities. Traffic flow data and land-use classifications are used as important inputs, and six important constraints are included in the MILP model with the objective function of maximizing the total profits of new charging stations. The effectiveness of the proposed method is then demonstrated by implementing a case study in Västerås, Sweden.
Grassland is of strategic importance for food security of China because of the high number of livestock raised in those areas. Grassland degradation due to climate change and overgrazing is thus regarded as severe environmental and economic threat for a sustainable future development of China. Photovoltaic water pumping (PVWP) systems for irrigation can play an important role for the conservation of grassland areas, halting degradation, improving its productivity and farmers' income and living conditions. The aim of this paper is to identify the technically suitable grassland areas for the implementation of PVWP systems by assessing spatial data on land cover and slope, precipitation, potential evapotranspiration and water stress index. Furthermore, the optimal locations for installing PVWP systems have been assessed using a spatially explicit renewable energy systems optimization model based on the minimization of the cost of the whole supply chain. The results indicate that the PVWP-supported grassland areas show high potential in terms of improving forage productivity to contribute to supplying the local demand. Nevertheless, the optimal areas are highly sensitive to several environmental and economic parameters such as ground water depth, forage water requirements, forage price and CO2 emission costs. These parameters need to be carefully considered in the planning process to meet the forage yield potentials.
Grassland plays a key role for the food security of China because of the large number of livestock raised in those areas. Thus, grassland degradation due to climate change and overgrazing is considered as one of the most severe environmental and economic threat for the future sustainable development of China. Photovoltaic water pumping systems for irrigation can play a fundamental role for the conservation of grassland areas. This paper investigates the geospatial distribution of the technically suitable grassland locations for the implementation of photovoltaic water pumping systems. The technically suitable grassland areas were taken as starting point to assess the optimal locations. The assessment of the optimal locations was conducted using a spatially explicit optimization model of renewable energy systems based on the cost minimization of the whole forage supply chain. The results indicate that the photovoltaic water pumping systems provide high potential for improving forage productivity, contributing to meet the local demand. The optimal areas are highly sensitive to several environmental and economic parameters such as increased forage potential yield, forage management costs, forage water requirements, ground water depth, forage price and CO2 price. Most of the optimal areas are selected when the market forage price ranges from 300 to 500 $/tonne DM, indicating that the forage produced using PVWP technology for irrigation is already competitive compared to the imported forage.
The exploitation of solar energy in remote areas through photovoltaic (PV) systems is an attractive solution for water pumping for irrigation systems. The design of a photovoltaic water pumping system (PVWPS) strictly depends on the estimation of the crop water requirements and land use since the water demand varies during the watering season and the solar irradiation changes time by time. It is of significance to conduct dynamic simulations in order to achieve the successful and optimal design. The aim of this paper is to develop a dynamic modelling tool for the design of a of photovoltaic water pumping system by combining the models of the water demand, the solar PV power and the pumping system, which can be used to validate the design procedure in terms of matching between water demand and water supply. Both alternate current (AC) and direct current (DC) pumps and both fixed and two-axis tracking PV array were analyzed. The tool has been applied in a case study. Results show that it has the ability to do rapid design and optimization of PV water pumping system by reducing the power peak and selecting the proper devices from both technical and economic viewpoints. Among the different alternatives considered in this study, the AC fixed system represented the best cost effective solution.
Photovoltaic water pumping (PVWP) and wind power water pumping (WPWP) systems for irrigation represent innovative solutions for the restoration of degraded grassland and the conservation of farmland in remote areas of China. The present work systematically compares the technical and economic suitability of such systems, providing a general approach for the design and selection of the suitable technology for irrigation purposes. The model calculates the PVWP and WPWP systems sizes based on irrigation water requirement (IWR), solar irradiation and wind speed. Based on the lowest PVWP and WPWP systems components costs, WPWP systems can compete with PVWP systems only at high wind speed and low solar irradiation values. Nevertheless, taking into account the average specific costs both for PVWP and WPWP systems, it can be concluded that the most cost-effective solution for irrigation is site specific. According to the dynamic simulations, it has also been found that the PVWP systems present better performances in terms of matching between IWR and water supply compared to the WPWP systems. The mismatch between IWR and pumped water resulted in a reduction of crop yield. Therefore, the dynamic simulations of the crop yield are essential for economic assessment and technology selection.
Photovoltaic water pumping technology is considered as a sustainable and economical solution to provide water for irrigation, which can halt grassland degradation and promote farmland conservation in China. The appropriate design and operation significantly depend on the available solar irradiation, crop water demand, water resources and the corresponding benefit from the crop sale. In this work, a novel optimization procedure is proposed, which takes into consideration not only the availability of groundwater resources and the effect of water supply on crop yield, but also the investment cost of photovoltaic water pumping system and the revenue from crop sale. A simulation model, which combines the dynamics of photovoltaic water pumping system, groundwater level, water supply, crop water demand and crop yield, is employed during the optimization. To prove the effectiveness of the new optimization approach, it has been applied to an existing photovoltaic water pumping system. Results show that the optimal configuration can guarantee continuous operations and lead to a substantial reduction of photovoltaic array size and consequently of the investment capital cost and the payback period. Sensitivity studies have been conducted to investigate the impacts of the prices of photovoltaic modules and forage on the optimization. Results show that the water resource is a determinant factor.
ABSTRACT: Irrigation using the photovoltaic water pumping (PVWP) systems represents a sustainable and attractive solution, which can combat Chinese grassland desertification and promote a sustainable development of the agricultural sector. This paper investigates the economics of PVWP systems taking into consideration the effects of the key components on the initial capital cost (ICC), life cycle cost (LCC), and revenues. Sensitivity analyses are conducted regarding the crop yield and price, cost of photovoltaic modules, and system components included in the ICC. Results show that the cost of the PVWP system is the most sensitive parameter affecting the ICC under the assumptions made, especially the cost of the PV modules; whereas, the crop production and price affect the net present value (NPV) and payback period (PBP) clearly. The PVWP has surplus power output when the crop water demand is low or it is non-irrigation season. The potential benefit from selling the surplus electricity is also discussed. In addition, the indirect benefits of carbon sequestration and CO2 emission reduction by applying PVWP systems are addressed in this paper.
Irrigation through photovoltaic water pumping (PVWP) system represents one of sustainable and attractivesolutions regarding the problems related to the Chinese grassland desertification. This paper is to investigatethe economics of PVWP systems taking in consideration of the key parameters affecting the sizing, and furtherthe initial capital cost (ICC), the life cycle cost (LCC) and revenues. In particular photovoltaic (PV) modules cost,availability of the well and of the irrigation system, designing water-head, irrigated area and related waterdemand, fuel price and grass production are investigated for the sensitivity analysis. The possibility ofcombining water pumping with electricity production for maximizing benefits is also discussed. Both PVWP anddiesel water pumping (DWP) systems are compared in terms of ICC and LCC. LCC, sensitivity, break-even point(BEP), net present value (NPV) and payback period (PBP) analyses are used to compare and evaluate theeconomic feasibility of the different alternatives investigated. The results show that the availability of the welland the depth of the ground water resources are the most sensitive parameters affecting the initial capitalcosts whereas the grass production and incentives affect mainly the NPV and PBP. The co-benefits for carbonmitigation and carbon credit trading through implementing photovoltaic water pumping system for the Chinesegrassland are also addressed in this paper.
This paper is to describe an open-source code for optimization of clean energy technologies. The model covers the whole chain of energy systems including mainly 6 areas: renewable energies, clean energy conversion technologies, mitigation technologies, intelligent energy uses, energy storage, and sustainability. Originally developed for optimization of renewable water pumping systems for irrigation, the open-source model is written in Matlab® and performs simulation, optimization, and design of hybrid power systems for off-grid and on-grid applications. The model uses genetic algorithm (GA) as optimization technique to find the best mix among power sources, storage systems, and back-up sources to minimize life cycle cost, and renewable power system reliability.
Typically, PV water pumping (PVWP) systems for irrigation are normally designed based on the worst conditions, such as high water demand and low solar irradiation. Therefore, the installed PVWP systems become oversized in most of time. Since the conventional control systems don't optimize the water supply, the water losses are increased. To remedy the problems related to the operation of the oversized systems, a novel control system is proposed. The control unit interacts between water demand and water supply in order to pump only the amount required by crops. Moreover, the novel control system substitutes the conventional protection approach with a method based on the ground water resources availability and response. The novel control system represents an innovative solution for water savings in PV watering applications.
Energy transitions are ongoing processes all over the world. While sustainable solutions are envisioned for the future, many societies are still under high-carbon and high-pollution energy regime borne by fossil fuels. How to design pathways towards sustainable energy transition has attracted worldwide concerns. Understanding the possible transition pathways of the energy system requires the integration of new energy technologies, environmental sciences, economics and management. This Special Issue of Journal of Cleaner Production targets to collect the latest research results on sustainable energy systems, discover innovative avenues and inspiring models and share knowledge on energy system modelling and management. In this paper, we identify 4 themes on sustainable energy transition pathways including: (1)Sustainable energy economics and management; (2)Renewable energy generation and consumption; (3)Environmental impacts of energy systems; and (4)Electric vehicle and energy storage. Theories, technologies, innovative models, and successful experiences are discussed accordingly. It is suggested that creative, robust and audacious strategies in governance, management and education are needed to boost sustainable energy transition across various scales and sectors.
Peak load introduces stress to the grid as supplied electricity is inadequate during peak demand period. In order to relieve the stress of grid and ensure the electricity supply, peak load shifting is an effective option. Buildings are consuming a huge amount of energy for space heating, ventilation and cooling. Using building thermal inertia to shift peak load has attracted more and more attention. By using thermal inertia, heat supplied during off-peak periods can be stored in the construction materials, and used in peak demand hours. However, peak shaving shall not sacrifice the indoor thermal comfort. The objective of this work is to investigate the impact of demand shifting by using thermal inertia on the indoor temperature. In order to understand how the demand shifting impacts the thermal comfort. A CFD model is developed to simulate an office room in winter time. Three cases that represent different shifting strategies are studied. According the results, when increasing the heating temperature, using thermal inertia of buildings can shift peak load, guarantee indoor thermal comfort and save energy. © 2018 International Heat Transfer Conference. All rights reserved.
Lithium-ion batteries (LiB) are widely used in electric vehicles (EVs) and battery energy storage systems, and accurate state estimation relying on the relationship between battery Open-Circuit-Voltage (OCV) and State-ofCharge (SOC) is the basis for their safe and efficient applications. To avoid the time-consuming lab test needed for obtaining OCV-SOC curves, this study proposes a data-driven universal method by using operation data collected onboard about the variation of OCV with ampere-hour (Ah). To guarantee high reliability, a series of constraints have been implemented. To verify the effectiveness of this method, the constructed OCV-SOC curves are used to estimate battery SOC and State-of-Health (SOH), which are compared with data from both lab tests and EV manufacturers. Results show that a higher accuracy can be achieved in the estimation of both SOC and SOH, for which the maximum deviations are less than 3.0% and 2.9% respectively.
With the rapid progress of oil market reform in China, independent refineries (small companies) get more and more oil import/export quotas, which will bring big impacts on the whole market and society. However, whether the impacts are positive or negative is highly dependent on the quota allocation mechanism and prices in global/domestic market markets. Therefore, in the present study, considering the game relationships among the six agents including state-owned companies, independent refineries, domestic and foreign oil product consumers, and domestic and foreign crude oil producers, in order to calculate the detailed impacts, a game-theoretic analysis model was developed. The impacts of different quota mechanism are analyzed and compared, and the optimal quota mechanism in different price scenarios is obtained based on the developed model.
Developing shallow geothermal energy is expected to play an important role to supply affordable, clean and reliable heating by many countries in the world. However, the development is mainly hindered by the high upfront investment costs and various risks involved in the exploration, construction and operation phases. The present study proposed a compound options model to explore the optimal investment timing and value based on the consideration of both investment and operational flexibilities. The Least Square Monte Carlo and Markov Chain Monte Carlo methods were employed in the model to find the solutions. A case study was carried out for China, and five scenarios were simulated to understand the effects of different policies including subsidy, carbon trading mechanism, preferential taxation and preferential electricity price. The obtained results show that, (i) the incentive policies are essential for the development of shallow geothermal energy, which can attract more investment before 2030; (ii) the government is suggested to carry out a preferential electricity price for shallow geothermal development, rather than increase the subsidy; (iii) the application of compound options method increases the investment value in all five scenarios, but its impact on investment timing varies.
Transcritical CO2 refrigeration cycle integrated with mechanical subcooling (MS) cycle operating with zeotropic mixture is proposed in this study, based on the concept of Lorenz cycle. An energetic model is developed and analyses are conducted in detail. A maximum overall coefficient of performance (COP) is achieved at the optimum discharge pressure and optimum subcooling degree. The maximum overall COP, optimum subcooling degree and discharge pressure are closely related to the temperature glide of the mixtures. The energy efficiency of the transcritical CO2 refrigeration cycle can be efficiently improved, and the high pressure can be reduced when mixtures with proper temperature glide are used as MS cycle refrigerant. Compared with pure R32, the overall COP is enhanced by 4.91%, and the discharge pressure decreases by 0.11 MPa at evaporation temperature of −5 °C and ambient temperature of 35 °C when R32/R1234ze(Z) (55/45) is employed as MS refrigerant. The mixtures with proper temperature glide are recommended. The thermal performance of the overall cycle can be enhanced more significantly for hot and warm climate regions, or relative low evaporation temperature applications, though a high subcooling degree is required to meet the optimum operation condition.
A transcritical CO 2 heat pump (HP) system for residential space heating integrated with direct dedicated mechanical subcooling (DMS) is proposed, and mathematical models are developed to study the annual energetic and economic performances considering the influence of frosting. The operation characteristics by adopting different heating terminals used in five typical cities are also assessed. The results show a maximum coefficient of performance (COP) is achieved at the optimum discharge pressure and subcooling degree. The COP is promoted by 24.4% and the discharge pressure is decreased by 2.093 MPa at the ambient temperature of −10 °C and water supply/return temperature of 45/40 °C. The seasonal performance factor (SPF) is enhanced more noticeably for severe cold region. For the case of Harbin using floor-coil radiator (FCR) or normal fan-coil unit (N-FCU) as heating terminal, SPF is improved by 32.0%. The highest SPF is achieved when small temperature difference fan-coil unit (STD-FCU) is employed. The exergy efficiency can also be apparently improved, especially for the cities located in severe cold region and using FCR or N-FCU as heating terminal due to the reduction in throttling loss of CO 2 system. The purchased equipment cost and electricity cost of the CO 2 HP with DMS are both lower than those of traditional CO 2 heat pump system. The CO 2 HP DMS system using STD-FCU as heating terminal shows superior economical efficiency to traditional system, with levelized annual total cost reduced by 7.51–15.27%.
An environmental and economical assessment model is developed, in order to evaluate the performances of transcritical CO2 heat pump system with dedicated mechanical subcooling (CO2 HPDMS). Introducing DMS to traditional CO2 HP system is an efficient method to reduce the primary energy consumption, which can be further decreased by using small temperature difference fan-coil unit (STD-FCU) as heating terminal. Using CO2 heat pump system for space heating is an environmentally-friendly heating method. The corresponding pollution emissions are only inferior to those of the wall hanging gas heater. The initial capital cost and operating cost of CO2 HPDMS system are both lower than those of CO2 HPBASE system, and the CO2 compressor cost accounts for about 80% of the overall initial capital cost. In contrast to other traditional heating methods, the payback periods of CO2 HPDMS system are not more than 9 years in most cases. If the CO2 compressor and electricity price are reduced by 20% and 28.79% respectively, the life cycle cost of CO2 HPDMS will be competitive to that of coal-fired boiler. In China, it is a promising way to adopt CO2 HPDMS for space heating in the near future with the assistant of electricity price subsidy and compressor price reduction.
Biomass from forestry sector provides an important contribution to meet the government's targets for increasing bioenergy production and utilization. Characterization of forest residues is critical for exploiting and utilizing them for energy production purpose. In present work, stem wood, stem bark, branches, top of trees from downy birch forest were sampled from different sites in South Norway and subjected to heating value and ash content measurement. Properties of different parts of trees vertically along the tree trunk and radially along the branch and crown level were assessed via the statistical model. The heating value of stem wood was in range 18.14-18.57 MJ/kg, of stem bark 18.50-18.72 MJ/kg and of branch wood 18.21-18.50 MJ/kg. The vertical dependence of heating value of downy birch stem wood was similar to that of stem bark. Regular decreasing of heating value towards the tree top was observed. Significantly higher heating value at level p<0.05∗of stem bark than the one of stem wood was observed. The ash content of downy birch branch wood did vary axially along the branch whereas there are only slight differences of ash content of branch within the crown. The stem bark has the highest ash content in range 2.0-2.5%, followed by branch wood in range of 1.0-1.6% and the lowest for stem wood in range of 0.3-0.5%.
Efficient and profitable biomass combustion is often limited by ash related operational problems. Knowledge of the ash melting and sintering is of important, in terms of predict and reduce ash-related problems in biomass-fired boilers. In this study, chemical composition and melting behaviors of ashes from the four parts of P. sylvestris trees were investigated. The four parts from Pinus sylvestris trees are stem wood, bark, branch base and twigs. A simultaneous thermal analyzer (STA) was used to characterize the melting behavior of selected biomass fuels in oxidizing atmosphere. Ash melting process was identified as the distinctive endothermic peaks on recorded DSC curves. The results showed that the stem wood of pine contains higher contents of most of the ash forming matters than other tree parts. Chemical composition of ashes from four parts of the pine tree is dominated by element Ca, K, Mg, Mn, P and Si. The K, Na and P contents in the twigs are significantly higher than that of stem wood, bark, and branch base indicating high tendency of ash melting and slagging. STA experiments indicated that the melting process of the studied fuel ashes start in the temperature range of 930-965 degrees C. Scanning electron microscopy (SEM) equipped with an energy dispersive X-ray spectrometry (EDX). Analyses results showed that the stem wood ash remains loose structure even after 1000 degrees C sintering treatment. But the ashes originated from top branch show sign of sintering at 1000 degrees C. The obtained results of present work can be considered as useful information within an industry interest for a prediction of the forest biomass ash melting behavior.
Pre-combustion capture technology is a promising route to power generation with CO2 free emissions, by transforming the fossil hydrocarbon fuel into a hydrogen rich fuel with near zero Carbon containing species. This gaseous fuel also allows to use a high efficiency gas turbine into a coal based power plant. The gas turbine combustor however has to meet the challenge of high temperature flame responsible for unacceptable NOx emissions, and a highly reacting fuel impeding the use of conventional dry low NOx combustion technologies. The actual solution to this problem is to dilute the hydrogen fuel with up to 50% Nitrogen. This paper presents a concept where the exhaust gas of the gas turbine is recirculated (EGR) such as to deplete the air of oxygen to produce a low temperature combustion with undiluted hydrogen fuel while flame stability is still ensured by the highly reactive properties of hydrogen. The study compares the concept with a cycle using Selective Catalytic Reduction for NOx control.
A novel gas turbine cycle concept applicable to power plants with pre-combustion CO<inf>2</inf> capture or integrated gasification combined cycle (IGCC) is presented. These power plants use a hydrogen rich fuel with high reactive combustion properties which makes fuel dilution necessary to achieve low NOx emissions. The proposed novel gas turbine arrangement is set up as to avoid both fuel dilution and its consequent efficiency penalty, and breakthrough in low NOx combustion technology. In this concept, a high exhaust gas recirculation (EGR) rate is applied in order to generate an oxygen depleted working fluid entering the combustor, enough to reduce the high reactivity of hydrogen rich fuels. As a result, the combustion temperature in this environment is inherently limited, thus, keeping NOx formation rate low. A first order assessment of the combustion characteristics under such gas turbine operating conditions is made in the light of a numerical analysis of stability and NOx emissions potential. Both diffusion and premixed types combustor are considered according to the selected EGR rate. It is first shown that the flame stability could be maintained at EGR rates well above the maximum EGR limit found in conventional natural gas fired gas turbines. The study further shows that at these high EGR rates, considerable reductions in NOx emissions can be expected. The conclusion of this first order analysis is that there is a true potential in reducing the efficiency penalty induced by diluting the fuel in power plants with pre-combustion CO<inf>2</inf> capture.
Integrating CO2 capture with biomass/waste fired combined heat and power plants (CHPs) is a promising method to achieve negative emission. However, the use of versatile biomass/waste and dynamic operation of CHPs result in big fluctuations in the flue gas (FG) and heat input to CO2 capture. Dynamic modelling is essential to investigate the interactions between key process parameters in producing the dynamic response of the CO2 capture process. In order to facilitate developing robust control strategies for flexible operation in CO2 capture plants and optimizing the operation of CO2 capture plants, artificial intelligence (AI) models are superior to mechanical models due to the easy implementation into the control and optimization. This paper aims to develop an AI model, Informer, to predict the dynamic responses of MEA based CO2 capture performance from waste-fired CHP plants. Dynamic modelling was first developed in Aspen HYSYS software and validated against the reference. The operation data from the simulated CO2 capture process was then used to develop and verify Informer. The following variables were employed as inputs: inlet flue gas flow rate, CO2 concentration in inlet flue gas, lean solvent flow rate, heat input to CO2 capture. It was found that Informer could predict CO2 capture rate and energy consumption with the mean absolute percentage error of 6.2% and 2.7% respectively.
Integrating CO2 capture with biomass/waste fired combined heat and power (CHP) plants is a promising method to achieve negative emissions. However, the use of versatile biomass/waste and the dynamic operation of CHP plants result in bigger fluctuations in the properties of flue gas (FG), e.g. CO2 concentration (CO2vol%) and flowrates, and the heat that can be used for CO2 capture, when comparing with coal fired power plants. To address such a challenge, dynamic modelling is essential to accurately estimate the amount of captured CO2 and optimize the operation of CO2 capture. This paper compares three dynamic approaches commonly used in literature, namely using the ideal static model (IST) and using dynamic models without control (Dw/oC) and with control (DwC), for MEA based chemical absorption CO2 capture. The performance of approaches is assessed under the variations of key factors, including the flowrate and CO2vol% of FG, and the available heat for CO2 capture. Simulation results show clear differences. For example, when the CO2vol% drops from 15.7 % to 9.7 % (about 38 %) within 4 hours, DwC gives the highest amount of captured CO2, which is 7.3 % and 22.3 % higher than IST and Dw/oC, respectively. It is also found that the time step size has a clear impact on the CO2 capture amount, especially for DwC. Based on the results, suggestions are also provided regarding the selection of dynamic modelling approaches for different purposes of simulations.
The latest progress on the experimental data and theoretical models regarding PVTxy properties of CO2 mixtures has been updated. This review shows that more experimental data are available, such as the vapor liquid equilibrium (VLE) of CO2/NO and the density of CO2/O-2. But there are still some clear deficiencies: for example, there have been no data on VLE of CO2/COS and density of CO2/NH3; there are only few points on VLE of CO2/NH3 and CO2/N2O, and density of binary mixtures containing CO, N2O4, COS and H2S. Several new models exhibit advantages for calculating PVTxy properties of CO2 mixtures. For example, Equation of State for Combustion Gases and Combustion Gas-like Mixtures (EOS-CG) shows better accuracy on both phase equilibrium and density than GERG-2008 except for the critical region. Peng-Robinson+ residual Helmholtz energy-based model (PR + EOS/(E,Wilson)(ares)) displays significant improvement in the representation of high-pressure critical region (deviation decreasing from 12.6% to 1% for CO2/O-2/N-2) and wider application of polar and non-polar mixtures for VLE.
Integrating carbon dioxide (CO2) capture in biomass or waste-fired combined heat and power (CHP) plants has been considered a key measure to achieve negative emissions. To support decision-making, an accurate assessment of the potential contribution and the associated cost from the national perspective is urgently needed. This paper proposed a bottom-up approach based on a dynamic modelling to evaluate the potental of nationwide negative emissions. As heat supply is often prioritized by CHP plants, unchanged heat generation is a prerequisite of this study. Two operating modes (OMs) for the integration of CO2 capture are investigated, which can represent the upper and lower boundaries of CO2 capture: OM1 aims to maximize the amount of captured CO2, while electricity generation can be sacrificed; OM2 aims to maximize the amount of captured CO2, while the electricity generation is maintained unchanged. Sweden is employed as a case study. Results show that operating CO2 capture in OM1 can achieve 8.7 million ton CO2 nationwide negative emissions a year, while operating CO2 capture in OM2 can generate 4.3 million ton CO2 positive emissions a year, which represents a reduction of 6.3 million tonCO2 a year compared with the reference plant without CO2 capture. The levelized costs of CO2 avoided are 36.9 USD/tonCO2 and 52.0 USD/tonCO2 for OM1 and OM2, respectively. The biogenic fraction of waste has a significant influence on negative emissions. According to the Swedish climate goal about bioenergy with CO2 capture and storage (BECCS), to achieve 3 million ton negative CO2 emissions a year, the minimum biogenic fractions should be 32.8% and 84.3% for operating CO2 capture in OM1 and OM2, respectively; in contrast, to achieve 10 million ton negative emissions a year, biomass and waste-fired CHP plants have to operate CO2 capture in OM1 and the biogenic fraction needs to be over 59.9%.
Under the pressure of global environmental climate change, all countries in the world are developing renewable energy such as hydropower, wind energy, and solar energy As a result, the electricity price varies in different patterns depending on the penetration of renewable energy. In this paper, a non-parametric model is employed to analyze the historical data of electricity spot price from Danish price areas of the Nord Pool (with high percentage of wind power), Swedish price areas of the Nord Pool (with high percentage of hydropower) and PJM market (with little renewable energy penetrated). The objective is to deeply understand the influence of renewable energies on electricity price volatility. It is found that electricity prices are more stable in Swedish price areas as hydropower is a more stable energy source. The electricity price in PJM market is also comparatively stable, only more volatile than Swedish market, as fossil fuels are dominant energy resources. For Danish price areas, the volatility of electricity prices is clearly affected by wind power, which is a highly intermittent energy resource.
Using metal hydride for hydrogen storage in stationary applications and for transportation is a promising technology due to its advantages of large hydrogen storage capacity, low pressure and low energy consumption. Combining the metal hydride reactor with PCM is expected to recover the heat generated during the hydrogen absorption and use it for hydrogen desorption, thus improving the energy efficiency of the system. This paper proposes a metal hydride reactor integrated with honeycomb fins and PCM to enhance heat transfer. Based on simulations, the results show that the achieved hydrogen storage capacity is 1.326 wt%, the gravimetric and volumetric storage densities are 0.411% and 14.76 kg of H2 per m3, respectively, and the mean saturated rates are 1.222 × 10−3 g s−1 and 0.773 × 10−3 g s−1 for absorption and desorption processes. Compared with the reactor without fins, the mass and volume of the reactor using honeycomb fins are increased, resulting in a decrease in gravimetric and volumetric storage density, but a increase in reaction rate during hydrogen absorption and desorption processes. Based on this structure, we also propose a honeycomb fin reactor filled with sandwich PCM to further accelerate the heat transfer in the reaction process. Compare to the reactor with PCM only filled on the periphery of the honeycomb fins, the hydrogen absorption and desorption times are shortened by about 86.4% and 81.1%, respectively. In addition, different reactor structures are compared using multiple KPIs to provide relevant suggestions for the reactor optimization. The obtained research results can provide a reference for effective thermal management methods in MH storage systems.
It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout programmes.
In today's district heating (DH) energy market, it is common to use user functional categories in price models to determine the heat price. However, users in the same category do not necessarily have the same energy consumption patterns, which potentially leads to unfair prices and many other practical issues. Taking into account heat usage characteristics, this work proposes two data-driven methods to cluster DH users to identify similar usage patterns, using practical energy consumption data. Efforts are focused on extracting representative features of users from their daily usage profiles and duration curves, respectively. Employing clustering based on these features, the resulting typical usage patterns and user category distributions are discussed. Our results can serve as potential inputs for future energy price models, demand-side management, and load reshaping strategies.
The impact of the enhanced heat transfer performance of longitudinal fins on the entire process of melting and solidification in a phase change heat storage unit is investigated through experiments and numerical simulations in this paper. The position and structure of the longitudinal fins are optimized by using the response surface method while ensuring that the total volume of the heat storage medium remains unchanged. Studies have identified that some challenging zones in melting and solidification significantly impact the heat transfer of the entire heat storage cycle. Specifically, the challenging zone in melting primarily exists in the lower part of the unit during the charing process, while the challenging zone in solidification is mainly distributed around the unit during the discharging process. Through optimization, the optimized structure (fin spacing is 22.5 mm, fin width is 6.05 mm) can reduce the charging and discharging time by 16.94 % and 45.90 %, respectively. Additionally, the round trip time is significantly reduced by 39.19 %, and the mean heat absorption rate during the melting process is enhanced by 20.28 %. Moreover, the mean heat release rate during solidification is enhanced by 80.23 %.
Selective noncatalytic reduction (SNCR) systems have been widely used for denitrification in small capacity boilers, such as biomass- and waste-fueled boilers. However, these systems cannot meet the requirements of ultralow emission regulations, i.e., 50 mg m−3. This work proposes a new solution that combines SNCR and activated carbon (AC). To solve the problem caused by the wettability of AC, which can significantly reduce the quantity of NOx that can be adsorbed and block active cites, hydrophobic modification was employed to amend the properties of AC. The influences of the key operating parameters on the denitrification of AC, including the reaction temperature, O2 concentration, feed gas flow rate, and contents of SO2 and CO2, have been investigated experimentally. A novel solution that combines AC and SNCR was proposed for industrial applications, and the economic feasibility has been verified. The results have demonstrated that this hybrid solution can achieve a low levelized cost of denitrification, which is 59.8% and 33.7% lower than those of SCR and hybrid SNCR/SCR.
Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the “top-down” and “bottom-up” prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park’s development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks.
Uncertainty is a common and critical problem for planning the capacity and operation of integrated energy systems (IESs). This study evaluates the effects of uncertainties on the capacity and operation of an IES. To this aim, system planning and operation with uncertainties are optimized by a two-stage stochastic programming model and compared with a referencing deterministic case. Specifically, the uncertainties of photovoltaic (PV) generation and energy demand are investigated. Regarding system capacity, a larger energy storage capacity is needed to accommodate a higher uncertainty. The superimposed uncertainties have a higher effect on system capacity than the sum of the effect of each uncertainty. The uncertainty of energy demand has a higher impact than the uncertainty of PV generation. Regarding system operation, the increase in operation cost is smaller than the increase in investment cost and total cost. In addition, the average flexibility provided by the energy storage increases with uncertainty and uncertainties affect the change rate for power charging/discharging of the electric energy storage. Regarding the effect on the grid, the uncertainties increase not only the magnitude of ramping-rate, but also the frequency of power-dispatch.
The formation of high concentrations of acid gases; in combustion with large variations in fuel qualities, represents a major challenge for energy production from contaminated biomass fuels. This paper provides a comprehensive evaluation of the effects of acid gas formation and retention in the combustion of recycled wood fuels. A model has been developed based on the chemical reactions involved and empirical correlations from plant monitoring and testing. The model has been used to study the behaviour of acidic gas components in critical stages of a bubbling fluidised bed boiler process. Results indicate that the variation in type of fuel contamination is the most important issue to deal with in the combustion of recycled wood fuels. Peaks in the flue gas chlorine concentrations cannot be suppressed easily by conventional flue gas cleaning measures. Upon applying ammonium sulphate dosing for the protection of chlorine induced corrosions, it is sometimes difficult to maintain the required S/Cl ratio when large variations of fuel chlorine occur. Moreover, a high level of chlorine in the fuel can also indirectly affect the emission control of sulphur dioxide because it would require an increased level of ammonium sulphate decomposition, which results in a high level of SO2 in flue gas. The study also shows a beneficial effect of the recirculation of quench water from the flue gas condenser to the boiler. It offers opportunities for the optimisation of flue gas cleaning and flue gas condensation, for improving the efficiencies of water and wastewater treatment, as well as for emission reduction with a sustainable way.
A combined heat and power plant (CHP) has the ability to provide ancillary services and therefore, can contribute to the improvement of flexibility and reliability of the power system. To motivate CHPs to provide flexibility services, this work investigated the potential benefit for CHPs from participating simultaneously in day-ahead and frequency regulation markets. A new CHP model was proposed, which considers both heat recovery from flue gas condensation and thermal energy storage. Based on the multi-market optimization using real market prices, it can be concluded that providing the frequency regulation service in addition to day-ahead trading can increase the annual profit of CHPs, which was 2.75% for the studied CHP. Meanwhile, the benefit was clearly affected by the heat demand as both high and low heat demand seasons (e.g. in winter and summer) can limit the flexibility provided by the CHP. In addition, the sensitivity analysis was carried out to assess the impacts of key factors, including electricity price, heat demand, cost of electricity, and bid size for frequency reserve services, on the benefit from the participation in both markets. The price difference between the day-ahead and frequency regulation markets and the cost of electricity generation were found to have clear impacts on the benefit of the CHP.
Integrating power-to-heat (P2H) assets in combined heat and power plants (CHPs) is an attractive option, which can improve the flexibility in CHPs. This paper compares the potential benefits of integrating an electrical boiler (EB) and a heat pump (HP) in a CHP from providing flexibility services in both the day-ahead market and the frequency regulation market. An optimization model is developed for the operation of P2H assets and the CHP to maximize the profit. A case study is carried out using the data of a real CHP and electricity prices of Nord Pool. It is found that when an EB or a HP is integrated, the annual profit of the studied CHP from providing frequency regulation can be increased by 3.1 % (EB) or 27.7 % (HP) respectively compared to the CHP without P2H. Despite the high capital cost, a HP can increase the net present value up to 21.8 %, and achieve a payback period of 3 year, which are better than an EB (0.8 % and 5 year). Sensitivity analysis shows that prices of fuel and electricity have significant impacts on the net present value and payback period for the integration of P2H assets. Even though the increase of the fuel price decreases the NPV, it can lead to a decline in the payback period. Meanwhile, the increase of the electricity price results in a large growth in the profit and NPV, but a big reduction in payback period.
Providing ancillary services through flexible electric vehicle (EV) charging has the potential to offer extra market benefit for EVs. EV aggregator controlling a fleet of EVs can play a significant role in managing the considerable EV charging demand and bid in the electricity markets. The increasing penetration of EVs has created the feasibility of participating in both the day-ahead energy market and frequency regulation market. This article presents a multimarket optimization model for minimizing the net operation cost of EV charging considering the benefit from performing frequency regulation. A two-level optimization algorithm for EVs controlled by the aggregator is proposed to determine optimal operation strategies of EV aggregations and the charging power of each individual EV. The optimization is able to merge revenue from frequency regulation with the cost reduction objectives of traditional EV charging management. The effectiveness of optimization algorithm is demonstrated by simulating EVs charged at the workplace and residential areas. The operation of EV aggregator is studied considering the diverse charging need of individual EV and market prices acquired from Nord Pool real-time market and Swedish power system operator. The increased profitability of participation in the sequential electricity markets has been illustrated. Net operating cost of EV aggregations can be significantly reduced considering both capacity and energy remunerations in the regulation market and the charging demand in the energy market.
As the electric capacity of wind turbine increases, heat dissipation in pitch cabinets becomes challenging owing to the limited space and rotating conditions. To cool down the pitch cabinet more effectively and allow heat dissipation, we designed and implemented a pulsating heat pipe (PHP) in this study. We designed PHP parameters and conducted performance tests to compare the cooling performance of the fabricated PHP with that of an air-based cooling system in a 1.5 MW wind turbine. The results demonstrated steady PHP operation under rotating conditions (17.3 rpm). At a heat load of 1000 W, the evaporator outlet temperature was only 76.1 °C. However, increasing the ambient temperature adversely affected PHP operation, resulting in higher temperature and thermal resistance. The heat-pipe-based cooling system lowered the insulated gate bipolar transistor (IGBT) temperature by about 20.4 °C in relation to the air-based cooling system, while being suitable under varied conditions. Additionally, the system could successfully operate when the heat load of IGBT was 2350 W, corresponding to a 7 MW electric capacity of the wind turbine. Reducing the manufacturing cost of the heat pipe would further enhance the applicability of this system for pitch cabinet IGBT cooling, such as decreasing payback period.
Solar Fuels and chemicals from CO2 can be produced through two main reactions: one is CO2 photoreduction, using different catalysts and different reducing agents; the other is CO2 fixation, which is usually performed through natural photosynthesis. The research nowadays is directed on the production of fuels and chemicals with one or two atoms of carbon, for example CH4, CO, HCOOH, HCHO, CH3OH, C2H5OH, etc. The chapter aims at comparing natural photosynthesis processes and reactions with artificial photosynthesis. After taking into consideration the natural photosynthetic process, the chapter focuses on heterogeneous and homogeneous photocatalysis. Heterogeneous catalysis can be performed with semiconductors and powder catalysts. Special attention is given to TiO2 as a promising photocatalyst. Homogeneous photocatalysts are usually represented by molecular catalysts, which are dissolved in water or another solvent. Usually, homogeneous photocatalysis is performed in complex systems which are composed by: a light harvesting unit (LHU) (i.e. the photosensitizer); one catalytic site for the oxidation process, where the electrons are supplied by a sacrificial donor; one reduction site, where the electrons are transmitted to CO2. Finally, even more complex systems are represented by those based on photoelectrocatalysis. These have the main advantage to separate the oxidation and reduction reactions at the two different electrodes of the system. In principle photoelectrochemical cells can be a way to mimic artificially the working principle of natural photosynthesis.
Due to the growing global energy demand and increasingly limited availability of conventional or easy-to-produce crude oils, extensive attention is being paid to the exploitation of unconventional heavy and extra-heavy oils. However, their inherent properties, characterized by high viscosity and poor mobility, coupled with the complex reservoir configuration, make the desired recovery processes very challenging. Although several in-situ recovery techniques have been employed in oil reservoirs worldwide, most of them are still suffering from low sweep and displacement efficiencies, high capital investment, potential formation damage and negative environmental footprints. This paper aims to provide a comprehensive review of the existing in-situ heavy oil recovery techniques, which fall into three categories of thermal injection, chemical injection and gas injection. Different aspects including the fundamental principles, main features, applicability, and limitations of these recovery processes are elaborated sequentially to illustrate the current technology status. Underlying mechanisms causing the relatively low recovery factors will also be pinpointed. Furthermore, this paper focuses on the technology using novel and active catalysts for simultaneous heavy oil upgrading and recovery, especially in the case of metallic nanocatalysts. Rationales, advantages and challenges regarding this in-situ catalytic upgrading technology will be extensively described for their potential implementation in fields. It is noteworthy that many recovery techniques are still limited to the laboratory scale with needs for further investigations. Therefore, this paper also covers the evaluation standards and analytical methodologies of heavy and extra-heavy oil recovery to establish experimental screening criteria. In the end, economic and environmental aspects of the in-situ catalytic upgrading technology have been briefly discussed. The objective of this review is to present a wide range of expertise related to the in-situ heavy oil recovery processes, and to introduce the in-situ catalytic upgrading technology as an effective and environmental friendly heavy oil recovery process.