The introduction of the off-grid electrification program in South Africa using the Solar Home System (SHS) was a central component of the government policy aimed at bringing development to un-electrified households. An assessment of the performance of SHS in many countries provided little evidence to support the development impact of the system. The general perception is that the SHS program is wasting government funds and has no hope of achieving the set objectives. Previous scientific reports have concluded that SHS is the most viable technology for bringing about socio-economic development to rural households. Most of these conclusions have been based on one sided arguments and largely on anecdotal evidence. This study provides a pluralistic view of the subject from the perspective of the energy service companies (ESCOs) and the households using the equipment. The development impact of SHS is subjected to scientific analysis by investigating the economic and social dimensions of the program. Additionally, the sustainability of the South African SHS program is assessed by investigating the challenges facing the ESCOs and the households. The study reveals that illumination provided by SHS electricity has profound impact on the livelihoods of rural households. Due to the limited capacity of SHS for productive and thermal use, there are limited direct economic benefits to the households. The associated economic impact is peripheral to the secondary usage of SHS electricity. SHS has improved the productivity of small scale business owners who utilize the light from SHS to do business at night. Irregularities in payment of subsidy funds and energy bills, high operation cost, non-optimal use of SHS, grid encroachment, and lack of customer satisfaction contribute to make the business unsustainable for the ESCOs.
One of the challenges to the sustainability of the Solar Home System (SHS) electrification program in South Africa is equipment theft. In response to this, communities susceptible to solar panel theft resort to mounting their panels flat on the ground so they can be looked after during the day and taken indoors at night for safe keeping. Other households use their security lights to illuminate their environment and provide security for pole and roof mounted solar panels at night. These actions have consequential effects on the performance of the SHS. Several studies have detected resentment from households regarding the low power quality from these systems. Most scientific contributions on the issue of low power from SHS have focused on the challenges based on the technical designs of the systems. The power losses due to the usage pattern of the system has not received much attention. This study therefore reports on the technical losses as a result of the deviation from the designed and installed specification of the system by the users in order to protect their systems. It also investigates the linkage between the technical and economic losses which affects the sustainability of SHS program. A case study was performed in Thlatlaganya village within Limpopo province in South Africa. Technical analysis using PVSYST solar software revealed that the energy output and performance of the battery is compromised as a result of these practices. Economic analysis indicates that the battery life and the economics of owning and operating SHS are affected negatively. The study recommends solutions to mitigate these losses, and proposes a cost effective way of optimizing the operation of SHS using a Bench-Rack system for mounting solar panels.
With the growing frequency and extent of extreme weather events, the resilient operation of multi-energy systems (MESs) has drawn attention nowadays. However, there is little study on the methodology with a set of key indicators to quantify the resilience of MESs with the consideration of the impacts of extreme weather. To address the problem, this paper proposes a framework to evaluate the time-dependent resilience of MESs considering energy interactions during extreme weather events, such as windstorms. Firstly, the multi-phase performance curve is utilized to describe the response behavior of MESs at different phases under the impacts of windstorms. Secondly, a service-based optimal energy flow model is developed to minimize the consequences caused by windstorms through the coordination among different energy subsystems. In order to model the chaotic failures and restoration of components, the Monte-Carlo simulation technique is applied. Furthermore, nodal resilience metrics for different energy carriers are proposed to quantify the resilience in MESs. Numerical studies demonstrate the capability of the proposed technique to quantify the resilience of MESs under windstorms. The results show that the resilience performance level of MESs can differ in different regions with the impacts of windstorms. The findings can provide a useful reference for system operators to constitute targeted resilience improvement measures.
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.
Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.
Nitrogen recovery is the next step in the improvement of the wastewater treatment process, utilizing this important nutrient for fertilizers to decrease use of energy, petrochemicals, and impact on the environment. The majority of wastewater treatment plants currently employ methods to remove nitrogen which are energy intensive and have no additional benefits besides complying with effluent concentration limits. Instead, recovering nitrogen allows simultaneous treatment of wastewater while collecting a concentrated ammonia product, creating a circular economy solution. This review acts to compile current research regarding nitrogen recovery and compare different techniques' recovery efficiencies and energy requirements. One outcome of this review is that more than one third of the techniques reviewed had little comments around the energy question, and thus more research needs to take place as these recovery systems continue to evolve towards full scale implementation. Additionally, a basic economic analysis was completed to demonstrate potential investment opportunities to implement these technologies. From this investigation, gas permeable membrane technology has the potential to recover ammonia from wastewater using little energy and may provide a small income with the sale of the product. Other techniques such as vacuum membrane distillation with acid absorption need further validation to determine the energy costs, as the amount of heat recycling has a great impact on the overall energy and economic balances. Finally, a discussion of the misalignment of products from recovery techniques and fertilizers in use today highlights the lack of communication and information sharing between the research community and the end users.
NH4-N-loaded biochars are suitable candidates for soil amendment and fertilization. Sewage sludge-based biochar and biochar from the invasive species black wattle were used as sorbents for the adsorption of ammonia from a concentrated solution to mimic the wastewater treatment plant reject water stream. To increase ammonium recovery efficiency, two post-pyrolysis activation techniques were compared: steam activation and hydrogen peroxide treatment. It was found that the success of the treatment options was material dependent; therefore, post-pyrolysis treatments will require optimization for different applications based on feedstock. A simplified version of an adsorption process simulated in Aspen Tech predicts that NH4-N may be recovered at an energy cost lower than that of the Haber-Bosch process for black wattle biochar yields of below 19.5%. The biooil and syngas produced during pyrolysis can be used to lessen the energy requirements of the process, so that the solid portion may be utilized as an adsorbent and soil fertilizer. The energy-based sustainability of this technology warrants a more in-depth investigation for evaluation of the techno-economic feasibility for this class of loaded sorbents, and whether this method of nitrogen capture from wastewater is a suitable replacement of the costly Haber-Bosch process.
The present article proposes a novel smart building energy system utilizing deep geothermal resources through naturally-driven borehole thermal energy storage interacting with the district heating network. It includes an intelligent control strategy for lowering operational costs, making better use of renewables, and avoiding CO2 emissions by eliminating heat pumps and cooling machines to address the heating and cooling demands of a commercial building in Uppsala, a city near Stockholm, Sweden. After comprehensively conducting techno-environmental and economic assessments, the system is fine-tuned using artificial neural networks (ANN) for optimization. The study aims to determine which ANN design and training procedure is the most efficient in terms of accuracy and computing speed. It also assesses well-known optimization algorithms using the TOPSIS decision-making technique to find the best trade-off among various indicators. According to the parametric results, deeper boreholes can collect more geothermal energy and reduce CO2 emissions. However, deep drilling becomes more expensive overall, suggesting the need for multi-objective optimization to balance costs and techno-environmental benefits. The results indicate that Levenberg-Marquardt algorithms offer the optimum trade-off between computation time and error minimization. From a TOPSIS perspective, while the dragonfly algorithm is not ideal for optimizing the suggested system, the non-dominated sorting genetic algorithm is the most efficient since it yields more ideal points rated below 100. The optimization yields a higher energy production of 120 kWh/m2, as well as a decreased levelized cost of energy of 57 $/MWh, a shorter payback period of two years, and a reduced CO2 index of 1.90 kg/MWh. The analysis reveals that despite the high investment costs of 382.50 USD/m2, the system is financially beneficial in the long run due to a short payback period of around eight years, which aligns with the goals of future smart energy systems: reduce pollution and increase cost-effectiveness.
In this study, a framework to compare the performances of different agrivoltaic systems, or agriphotovoltaic systems, in a range of environments was developed and tested. A set of key performance indicators derived from simulations was combined in a multi criteria decision analysis approach. The agriphotovoltaic systems were then ranked based on their similarity to the optimal solution for a specific environment. Main key performance indicators were crop ratio, energy conversion per hectare, specific energy yield, water use efficiency, and initial capital expenditure. Four agriphotovoltaics, namely vertical, interspace mono -axial, overhead mono -axial, and an overhead bi-axial, with five pitch width for each agriphotovoltaic and cultivated with processing tomato, were modelled across five sites (from the North to the South of Italy) during a ten-year period. The different scenarios were simulated in Scilab, in which a radiation model and GECROS crop model were coded. Global irradiation distribution beneath modules, and thus crop yield, were more homogeneous in vertical and overhead mono -axial than in the other agriphotovoltaic. Processing tomato demonstrated high adaptability to shading and yield was marginally affected in most of the agriphotovoltaic system alternatives. Vertical and overhead mono -axial accounted for the least yield reduction when the same pitch is compared. Overall, overhead mono -axial APV with 6 m pitch ranked first in each site when a 0.7 crop ratio threshold was considered. This framework could serve as a valuable tool for assessing the performance of different solution of agriphotovoltaics systems and their compliance with national regulation, and economic and technical targets.
Rural electrification programs usually do not consider the impact that the increment of demand has on the reliability of off-grid photovoltaic (PV)/battery systems. Based on meteorological data and electricity consumption profiles from the highlands of Bolivian Altiplano, this paper presents a modelling and simulation framework for analysing the performance and reliability of such systems. Reliability, as loss of power supply probability (LPSP), and cost were calculated using simulated PV power output and battery state of charge profiles. The effect of increasing the suppressed demand (SD) by 20% and 50% was studied to determine how reliable and resilient the system designs are. Simulations were performed for three rural application scenarios: a household, a school, and a health centre. Results for the household and school scenarios indicate that, to overcome the SD effect, it is more cost-effective to increase the PV power rather than to increase the battery capacity. However, with an increased PV-size, the battery ageing rate would be higher since the cycles are performed at high state of charge (SOC). For the health centre application, on the other hand, an increase in battery capacity prevents the risk of electricity blackouts while increasing the energy reliability of the system. These results provide important insights for the application design of off-grid PV-battery systems in rural electrification projects, enabling a more efficient and reliable source of electricity.
Over the past decades a variety of different approaches to realize Compressed Air Energy Storage (CAES) have been undertaken. This article gives an overview of present and past approaches by classifying and comparing CAES processes. This classification and comparison is substantiated by a broad historical background on how CAES has evolved over time from its very beginning until its most recent advancements. A broad review on the variety of CAES concepts and compressed air storage (CAS) options is given, evaluating their individual strengths and weaknesses. The concept of exergy is applied to CAES in order to enhance the fundamental understanding of CAES. Furthermore, the importance of accurate fluid property data for the calculation and design of CAES processes is discussed. In a final outlook upcoming R&D challenges are addressed.
Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. From an engineering and architecture perspective it is mandatory to design cities taking into account energy and water issues to achieve high living and sustainability standards. The aim of this paper is to develop an optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability through dynamic simulations. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint.
The optimization results show that the reliability of the hybrid renewables based power system can vary between 40 and 95% depending on the scenarios considered regarding the built environment area and on the cases concerning the overall electric load. The levelized cost of electricity vary between 0.096 and 0.212 $/kW h. The maximum water harvesting system reliability vary between 30% and 100% depending on the built environment area distribution. For reliabilities below 20% the levelized cost of water is kept below 1 $/m3 making competitive with the network water tariff.
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.
Transforming the road public transport to run on renewable energy is vital solution to achieve carbon neutral and net zero goals. This paper evaluates the potential of using solar radiation-generated electricity as an auxiliary power supplementary for the battery of electric buses, based on a developed framework that using publicly street-view panoramas, GPS trajectory data and DEM data as input parameters of solar radiation model. A case study of Qingdao, China with 547 bus routes, 28,661 street-view panoramas shows that the solar-radiation electricity generated at noon during the operation accounts for about one-fifth, one-eighth of the total elec-tricity consumption of a bus traveling one kilometer in a sunny day and a cloudy day, respectively. Spatial variability shows significant solar-radiation power generation advantages in newly-launched areas and expressway. The solar power generated in a sunny day can make a bus half of passengers and with air conditioner off at least one extra trip in 2:1 replacement schedule, and nearly close to one extra trip in 4:3 replacement schedule. A correlated relation between the solar-radiation power generation benefit and the operation schedule of electric buses is observed, implying that the high cost of 2:1 replacement schedule for long-distance routes during summer or winter can be reduced. The proposed framework can help us evaluate and understand the feasibility of solar radiation-generated electricity energy of electric bus fleets covering the large-scale urban areas at different times, locations, and weather conditions, so as to support effective decisions at better planning of PV-integrated electric buses.
Ever-increasing energy demands pose huge environmental challenges globally. The strategies and methods that are chosen to address the energy crisis will, in part, determine the possibility of fulfilling the 1.5-degree global warming target set by the Paris Agreement, and of achieving the United Nations Sustainable Developmental Goals, two vital and ambitious objectives for humans in the coming decades. While numerous inventory and modelling approaches have been developed to evaluate direct and indirect energy requirements at multiple scales from industries to cities and to the global economy, a discussion on their implications for environmental sustainability is long overdue. In this study, we provide an overview of the research paradigm and the important approaches that have been developed to address energy sustainability and review the papers included in this Special Issue, which are representative of some of the major advancements in energy, carbon, and other hybrid footprint approaches. This Special Issue aims to gather and harmonize state-of-the-art energy accounting frameworks, models, and metrics that benefit the promotion of global sustainability.
With the development of information technology, the scale and quantity of internet data centers (IDCs) are expanding rapidly. IDCs have emerged as the major electricity consumers in active distribution networks (ADNs), which dramatically increase the electricity load and have a significant impact on the operational flexibility of ADNs. Geographically distributed IDCs can participate in the operation of ADNs with the potential for spatio-temporal load regulation. This paper proposes flexible dispatch strategies of data centers to improve the operational flexibility of ADNs. First, a data-power model of IT equipment is proposed based on piecewise linearization to describe the power consumption characteristics of data centers. The flexible dispatch strategies for the delay-tolerant workload are further proposed from two aspects of temporal transfer and spatial allocation. Then, considering the potential for spatio-temporal load regulation, the operational flexibility analysis model with data centers is formulated to adapt to the operational requirements of ADNs in complex environments. Case studies show that through the spatio-temporal regulation of workload, the energy efficiency of IDCs can be effectively improved. The flexible dispatch of IDCs can also reduce the voltage violation and feeder load imbalance of ADNs, which can facilitate providing the high-quality power supply for IDCs.
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.
Air conditioning is essential for maintaining thermal comfort in indoor environments, particularly for hot and humid climates. Today, air conditioning, comprising cooling and dehumidification, has become a necessity in commercial and residential buildings and industrial processes. It accounts for a major share of the energy consumption of a building or facility. In tropical climates, the energy consumed by heating, ventilation and air-conditioning (HVAC) can exceed 50% of the total energy consumption of a building. This significant figure is primarily due to the heavy duty placed on cooling technologies to remove both sensible and latent heat loads. Therefore, there is tremendous potential to improve the overall efficiency of the air-conditioning systems in buildings. Based on today's practical technology for cooling, the major components of a chiller plant are (I) compressors, (2) cooling towers, (3) pumps (chilled and cooling water) and (4) fans in air handling units. They all consume mainly electricity to operate. When specifying the kW/R ton of a plant, there are two levels of monitoring cooling efficiency: (1) at the efficiency of the chiller machines or the compressors which consume a major amount of electricity; and (2) at the overall efficiency of cooling plants which include the cooling towers, pumps for moving coolant (chilled and cooling water) to all air-handling units. Pragmatically, a holistic approach is necessary towards achieving a low energy input per cooling achieved such as 0.6 kW/R ton cooling or lower by considering all aspects of the cooling plant. In this paper, we present a review of recent innovative cooling technology and strategies that could potentially lower the kW/R ton of cooling systems - from the existing mean of 0.9 kW/R ton towards 0.6 kW/R ton or lower. The paper, broadly divided into three key sections (see Fig. 2), begins with a review of the recent novel devices that enhances the energy efficiency of cooling systems at the component level. This is followed by a review of innovative cooling systems designs that reduces energy use for air conditioning. Lastly, the paper presents recent developments in intelligent air-control strategies and smart chiller sequencing methodologies that reduce the primary energy utilization for cooling. The energy efficient cooling technology, innovative systems designs, and intelligent control strategies described in the paper have been recently researched or are on-going studies. Several have been implemented on a larger scale and, therefore, are examples of practical solutions that can be readily applied to suit specific needs. (C) 2012 Elsevier Ltd. All rights reserved.
The coupling of a pressurized solid oxide fuel cell (SOFC) and a gas turbine has been proven to result in extremely high efficiency and reduced emissions. The presence of the gas turbine can improve system durability compared to a standalone SOFC, because the turbomachinery can supply additional power as the fuel cell degrades to meet the power request. Since performance degradation is an obstacles to SOFC systems commercialization, the optimization of the hybrid system to mitigate SOFC degradation effects is of great interest. In this work, an optimization approach was used to innovatively study the effect of gas turbine size on system durability for a 400 kW fuel cell stack. A larger turbine allowed a bigger reduction in SOFC power before replacing the stack, but increased the initial capital investment and decreased the initial turbine efficiency. Thus, the power ratio between SOFC and gas turbine significantly influenced system economic results.
It is vital to perform system analysis on integrated biomass gasification in chemical recovery systems in pulp and paper and heat and power plants for polygeneration applications. The proposed integration complements existing pulp and paper and heat and power production systems with production of chemicals such as methane and hydrogen. The potential to introduce gasification-based combined cycles comprising gas turbines and steam turbines to utilize black liquors and wood pellets also merits investigation. To perform such analysis, it is important to first build knowledge on expected synthesis gas composition by gasifying at smaller scale different types of feed stock. In the present paper, the synthesis gas quality from wood pellets gasification has been compared with black liquor gasification by means of numerical simulation as well as through pilot-scale experimental investigations. The experimental results have been correlated into partial least squares models to predict the composition of the synthesis gas produced under different operating conditions. The gas quality prediction models are combined with physical models using a generic open-source modelling language for investigating the dynamic performance of large-scale integrated polygeneration plants. The analysis is further complemented by considering potential gas separation using modern membrane technology for upgrading the synthesis gas with respect to hydrogen content. The experimental data and statistical models presented in this study form an important literature source for future use by the gasification and polygeneration research community on further integrated system analysis.
The share of renewable liquid fuels (ethanol, fatty acid methyl ester, biogas, and renewable electricity) in the total transportation fuel in Sweden, has increased by the end of 2009 to such level that e.g. domestic bioethanol production is unable to satisfy current ethanol fuel demand. Regional small-scale ethanol production can assist the region in covering the regional needs in transport fuel supply.
Current case study system includes the production of ethanol, biogas, heat and power from locally available cereals straw. A mixed integer programming (MIP) model is developed for cost optimization of regional transport fuel supply (ethanol, biogas and petrol). The model is applied for two cases, one when ethanol production plant is integrated with an existing CHP plant (polygeneration), and one with a standalone ethanol production plant.
The optimization results show that for both cases the changes in ethanol production costs have the biggest influence on the costs for supplying regional passenger car fleet with transport fuel. Petrol fuel price and straw production costs have also a significant effect on costs for supplying cars with transport fuel for both standalone ethanol production and integrated production system.
By integrating the ethanol production process with a CHP plant, the costs for supplying regional passenger car fleet with transport fuel can be cut by 31%, from 150 to 104 €/MW h fuel, which should be compared with E5 costs of 115 €/MW h (excl VAT).
The increasing atmospheric CO2 concentration has caused a transformative shift in global energy systems, which is contributing to an increased use of renewables. Sweden is among the countries trying to shift to a fossil-fuel-free system in all energy sectors. This paper addresses the fuel demand and supply in the transportation sector in the county of Västmanland in Sweden. A Mixed Integer Linear Programming optimization model is developed to minimize cost in the studied system. The model is further used to investigate the influence of three different scenarios on production planning of regional Combined Heat and Power (CHP) plants: (1) straw-based biofuel production integrated with existing CHP plants to fuel combustion engine vehicles, (2) use of electric vehicles, and (3) use of hybrid vehicles fueled by both electricity and bioethanol. Potential solar power generation from rooftop solar cells is also included in the model. The energy system in scenario 2 is found to have the highest overall system efficiency; however, a large amount of power needs to be imported to the system. Hybrid vehicles can potentially reduce the electricity import and CO2 emissions compared to the current situation. Electricity production from rooftop solar collectors could provide the energy needs of the vehicles during summer, while regionally produced straw-based bioethanol integrated with CHP plants can satisfy the fuel needs of the vehicles in winter. This approach could affect the production planning of CHP plants, result in less fuel use and increase the share of renewable resources in the regional transportation system.
The authors regret that there is a typo mistake in Table 3 in the paper. The value of “Hydropower” in the table was incorrectly written 831 GWh; however, it shall be 83 GWh. The revised table is as follows: The authors would like to apologize for any inconvenience caused.
The growing share of intermittent renewable energy sources for power generation indicates an increasing demand for flexibility in the energy system. Energy storage technologies ensure a balance between demand and supply and increase the system flexibility. This study investigates increased application of renewable energy resources at a regional scale. Power-to-gas storage that interacts with a large-scale rooftop photovoltaic system is added to a regional energy system dominated by combined heat and power plants. The study addresses the influence of the storage system on the production planning of the combined heat and power plants and the system flexibility. The system is modeled and the product costs are optimized using the Mixed Integer Linear Programming method, as well as considering the effects on CO2 emissions and power import into the regional system. The optimization model is investigated by developing different scenarios for the capacity and cost of the storage system. The results indicate that the proposed storage system increases the system flexibility and can reduce power imports and the marginal emissions by around 53%, compared with the current energy system. There is a potential to convert a large amount of excess power to hydrogen and store it in the system. However, because of low efficiency, a fuel cell cannot significantly contribute to power regeneration from the stored hydrogen. Therefore, for about 70% of the year, the power is imported to the optimized system to compensate the power shortfalls rather than to use the fuel cell.
Solar energy is a source, which can be exploited in two main ways to generate power: direct conversion into electric energy using photovoltaic panels and by means of a thermodynamic cycle. In both cases the amount of energy, which can be converted, is changing daily and seasonally, causing a discontinuous electricity production. In order to limit this drawback, concentrated solar power plants (CSP) and photovoltaic plants (PV) can be equipped with a storage system that can be configured not only for covering peak-loads but also for the base-load after the sunset or before the sunrise. In CSP plants it is the sun's thermal energy to be stored, whereas in PV applications it is the electrical energy to be stored in batteries, although this is not economically and environmentally feasible in large-scale power plants.The main aim of this paper is to study the performance of concentrated solar power plants equipped with molten salts thermal storage to cover a base load of 3MWel. In order to verify the possibility of storing effectively the thermal energy and to design a plant for base load operation, two locations were chosen for the study: Gela in southern Italy, and Luxor in Egypt. The electricity production of the CSP facilities has been analyzed and then compared with the electricity production of PV plants. Two different comparisons were done, one by sizing the PV plant to provide the same peak power and one using the same collectors surface. This paper has also highlighted some important issues in site selection and in design criteria for CSP plants used for base load operation.The high variability of the direct normal radiation during the year in southern Italy may cause several problems in CSP facilities, mainly related to the wide range of energy input from the sun. The more uniform and higher values of the solar radiation in the Egyptian location mitigates this problem and allows achieving higher efficiencies than in southern Italy. In most cases the electricity produced by the CSP plant is higher than that produced by a similar PV plant, because the presence of the storage system guarantees the continuity of electricity production even without solar radiation. An economic analysis based on the estimation of the levelized electricity cost (LEC) for both CSP and PV power plants located both in south of Italy and Egypt was carried out in order to investigate which is the most cost effective solution. In all the cases considered, the CSP facilities resulted the best option in terms of cost of electricity produced due to the continuity of energy production during the night hours.
Molten carbonate salts have received particular attention for high-temperature thermal energy storage and heat Molecular dynamics simulation transfer applications due to desirable thermal characteristics, such as wide operating temperature range, low Molten alkali carbonates causticity and excellent thermal stability. In this study, molecular dynamics (MD) simulations were performed Local structures on molten alkali carbonate K2CO3 based on an effective pair potential model, a Born-Mayer type combined with Thermodynamic properties a Coulomb term. The radial distribution functions (RDF) and coordination number curves of the molten salt were characterized to explore the temperature dependences of macroscopic properties from microscopic view. The results suggest that the distance between K2CO3 particles is getting larger with temperature increasing, resulting in the increase of molar volume and the diminished ability of resistance to shear deformation and heat transfer by vibration between ions. Besides, it can be concluded that the structure of CO32- is inferred reasonably to be ortho-triangular pyramid from the comprehensive analysis of local structures including the angular distribution functions (ADF). Moreover, the thermodynamic properties were simulated in detail from 1200 to 1600 K including the density, thermal expansion coefficient, specific heat capacity, sheer viscosity, thermal conductivity and ion self-diffusion coefficient, which was hard to be measured from experiments under high-temperature extreme conditions, All the simulation results are in satisfactory agreement with available experimental data with high accuracy, and the minimum simulation error is as low as 1.42%.
The inherent stochastic nature of wind power requires additional flexibility during power system operation. Traditionally, conventional generation is the only option to provide the required flexibility. However, the provision of the flexibility from the conventional generation such as coal-fired generating units comes at the cost of significantly additional fuel consumption and carbon emissions. Fortunately, with the development of the technologies, energy storage and customer demand response would be able to compete with the conventional generation in providing the flexibility. Give that power systems should deploy the most economic resources for provision of the required operational flexibility, this paper presents a detailed analysis of the economic characteristics of these key flexibility options. The concept of “balancing cost” is proposed to represent the cost of utilizing the flexible resources to integrate the variable wind power. The key indicators are proposed respectively for the different flexible resources to measure the balancing cost. Moreover, the optimization models are developed to evaluate the indicators to find out the balancing costs when utilizing different flexible resources. The results illustrate that exploiting the potential of flexibility from demand side management is the preferred option for integrating variable wind power when the penetration level is below 10%, preventing additional fuel consumption and carbon emissions. However, it may require 8% of the customer demand to be flexible and available. Moreover, although energy storage is currently relatively expensive, it is likely to prevail over conventional generation by 2025 to 2030, when the capital cost of energy storage is projected to drop to approximately $ 400/kWh or lower.
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.
The 6th Dubrovnik Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES Conference), attended by 418 scientists from 55 countries representing six continents. It was held in 2011 and dedicated to the improvement and dissemination of knowledge on methods, policies and technologies for increasing the sustainability of development, taking into account its economic, environmental and social pillars, as well as methods for assessing and measuring sustainability of development, regarding energy, transport, water and environment systems and their many combinations.
Amid the increasing electricity demand, energy crisis and pollution, the transition to renewable energy (RE) is becoming a preoccupation and major global challenge due to the multidimensional and intricate problem of RE planning. In Egypt, about 90% of gross power generation comes from carbon-intensive power plants (natural gas and coal). Here, we propose a novel geospatial-decision-making model aimed at geographical-technical–economic potential mapping and assessment of solar photovoltaic (PV) and onshore wind turbine (WT) power plants at a high level of resolution (1 km2) in Egypt. We identify the locations suitable for PV and WT development considering sixteen restrictive and contradictory evaluation criteria. These locations have been further analyzed to estimate how much energy generation is available and at what energy cost. The analysis identifies Middle-Upper Egypt and Suez Canal as hosting the majority of highly suitable locations for PV and WT power plants, respectively. Our finding reveals that the proper planning on RE projects at the proposed optimum locations could support the country's energy mix with a sizable 32% share of the projected country's electricity consumption from PV and 50% share from WT, by 2030. Furthermore, we show that the investment opportunities of PV and WT generation are potentially attractive with affordable competitive prices estimated at 57.84 $/MWh and 32.36 $/MWh, respectively, against conventional generation for today and the future. We anticipate that our results will provide valuable support in realizing Egypt's vision for sustainable electricity generation and in keeping abreast of the global transformation in power systems being witnessed. Ultimately, the method's relevance extends beyond the geographical boundaries of the present territory; it features a strategic, clear and reproducible approach that may be applied to a larger area or continent, provided the necessary input data and criteria are introduced.
The use of hybrid renewable energy system (HRES) holds great promise for sustainable electrification and support countries reaching their energy access goals. The site selection and design of HRES are strategic stages towards ensuring an affordable, sustainable, and well-performing project. However, both are multidimensional and intricate issues that involve multiple conflicting assessment criteria and alternatives, which are not yet investigated comprehensively and simultaneously in many of the existing literature. In this context, the paper aims to develop a systematic and conceptual decision-making framework for site suitability and optimal design of HRESs, with an application on a regional scale in Kenya, Sub-Saharan Africa. The suggested framework is applied through three consecutive phases. First, a geographical information system (GIS) is combined with Best Worst Method (BWM) decision-making approach to spatially investigate and analyze the potential sites of solar, wind, and hybrid solar/wind systems. Within the spatial investigation, 9 different climatology, environment, location, and orography criteria are considered. Second, energy-economy-ecology (E3) design optimization is conducted to determine the list of feasible alternatives among grid-extension, autonomous HRES, and stand-alone diesel genset electrification schemes for powering a representative remote rural village in Kenya. Third, a post-optimality multi-criteria decision-making (MCDM) analysis is applied to decide and assess the optimal energy access design against 12 key sustainability indicators. In the third phase, the BWM is employed to define the weights of each indicator. Then, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) decision making approaches are used for the final ranking of feasible alternatives. The obtained site suitability maps of Kenya show that 0.91% (5322 km2) and 1.5% (8828.4 km2) of the land is highly suitable, 10.25% (59687 km2) and 33.04% (192360 km2) is suitable, and 80.5% (470313 km2) and 65% (378407 km2) is permanently unsuitable for establishing solar and wind systems, respectively. Also, E3-MCDM results indicate that the development of solar/wind/diesel/battery HRES is the best sustainable solution to supply the studied region as compared to other feasible alternatives. The system does not only guarantee a reliable operation with an unmet load of 552 kWh/yr, but it also has the lowest net present and energy costs at 2.6 M$ and 0.28 $/kWh, respectively, meanwhile avoiding annual CO2 of 804 tons compared with diesel system.
Agrivoltaic systems represent an intelligent solution combining electricity production from solar photovoltaic technology with agricultural production to avoid land use conflicts. Geographic Information System technologies can support the implementation and spread of agrivoltaic systems by identifying the most suitable areas using useful spatially explicit information concerning techno-agro-socio-economic criteria. In this study, we have developed a procedure to identify and classify suitable areas for agrivoltaic systems in Sweden. An Ordinal Priority Approach based multi-criteria decision-making algorithm is established to calculate the weights of the selected evaluation criteria through expert interviews. The land use data refers to the Corine Land Cover 2018 product. The results show that about 8.6% of the Swedish territory, approximately 38,485 km2, is suitable for installing agrivoltaic systems. Among this area, about 0.2% is classified as “excellent”, about 15% as “very good”, about 72% as “good”, about 13% as “moderate”, and about 0.1% as “poor”. Most “excellent”-classified areas are in Kalmar, Skåne, and Gotland. In contrast, most “very good” sites are in Skåne, Kalmar, and Östergötland. By deploying vertically mounted agrivoltaic systems with bifacial photovoltaic modules, the total potential installed capacity for “excellent” areas is about 2.5 GWp, while for areas classified “excellent” and “very good” is about 221 GWp. The total “excellent” areas can potentially supply about 2.4 TWh of electricity against the electricity consumption in 2021 of about 143 TWh. On the other hand, the land classified as “excellent” and “very good” could potentially provide about 207 TWh. The County of Västra Götaland shows the greatest potentials in terms of total potential electricity supply from agrivoltaic systems with about 227 TWh, followed by Skåne with a total potential of 206 TWh.
Industrial park shoulders heavy responsibilities for economic development, and in the meantime, acts the role as energy consumer and carbon emitter. Under the background of holding the average global temperature increase limited in 2 °C compared to the pre-industrial level, which was proposed in the Paris Agreement, the development of zero carbon emission at the industrial park level is of great importance. This study investigated how to realize zero carbon emission at an industrial park level. In addition, a practical case study of the Southern China Traditional Chinese Medicine Industrial Park located in the Zhongshan City, Guangdong Province of China was conducted. Scenario analyses were projected to realize zero carbon emission in this industrial park and the results show that zero carbon emission can be realized under all the three scenarios. Economic assessments found that purchasing carbon offsets get the minimum cost effectiveness under current market situation. However, purchasing carbon offset may not be the best choice from the aspect of absolute reduction. Sensitivity analyses illustrate that the cost effectiveness of carbon reduction is remarkably influenced by the carbon price and solar energy cost reduction ratio. Meanwhile, applying large-scale renewable energy and producing more carbon offset can harvest more economic and carbon reduction benefits when the current solar energy cost has been reduced by 90%. Moreover, challenges of building zero-carbon industrial park as well as the corresponding solution schemes were discussed.
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.
Greenhouse gas (GHG) emissions from industrial sectors are increasing, particularly in the developing world where pursuing industrialization has been highly addressed. This calls for further studies to learn and share experiences for developing countries. In order to fill in such a research gap, this special issue focuses on examining the recent trend of industrial emissions in developing countries. Among the manuscripts submitted to the Special Issue, twelve papers have been accepted after review, covering assessment indicators, tools and methods, and policies. Key industrial sectors, including cement, lime, aluminum, coal, mining, glass, soda ash, etc, have been investigated. Valuable policy insights have been raised, including wide scale upgrading, replacement and deployment of best available technologies, integrated information platforms, cross-cutting technologies and measures, a shift to low carbon electricity, radical product innovations, carbon dioxide capture and storage (CCS), demand on new and replacement products, systematic approaches and collaboration among different industries. These useful suggestions could be shared or learned by industrial policy makers or managers in the developing world so that the overall GHG emissions from their industrial sectors can be mitigated by considering the local realities.
An increase in environmental awareness in both the aviation industry and the wider global setting has led to large bodies of research dedicated to developing more sustainable technology with a lower environmental impact and lower energy usage. The goal of reducing environmental impact has necessitated research into revolutionary new technologies that have the potential to be significantly more energy efficient than their predecessors. However, for innovative technologies in any industry, there is a risk that adoption will be prohibitively expensive for commercial application. It is therefore important to model the economic factors of the new technology or policy at an early stage of development. This research demonstrates the application of a Techno-economic Environmental Risk Assessment framework that may be used to identify the economic impact of an energy-efficient aircraft concept and the impact that environmental policy would have on the viability of the concept. The framework has been applied to a case study aircraft designed to achieve an energy saving of 60% in comparison to a baseline 2005 entry-into-service aircraft. The model compares the green aircraft concept to a baseline conventional aircraft using a sensitivity analysis of the aircraft direct operating cost to changes in acquisition and maintenance cost. The research illustrates an economically viable region for the technology. Cost margins are identified where the increase in operating cost due to expensive novel technology is counterbalanced by the reduction in cost resulting from low energy consumption. Viability was found to be closely linked to fuel price, with a low fuel price limiting the viability of energy-efficient aviation technology. In contrast, a change in environmental taxation policy was found to be beneficial, with the introduction of carbon taxation incentivising the use of an environmentally optimised aircraft.
Agrivoltaic is a strategic and innovative approach that combines photovoltaic (PV) energy conversion with agricultural production, enabling synergies in the production of food, energy, and water, as well as the preservation of the ecological landscape. Shading management, intensity adjustment, and spectral distribution allow innovative PV systems to generate significant amounts of electricity without affecting agricultural production. Demonstration projects have already been developed around the world and there is a wealth of experience with various design solutions for commercial use. One of these new technologies is concentrator photovoltaics (CPV). The CPV has excellent spectral processing capabilities and highly concentrated power generation efficiency, which makes it a perfect solution for integrating with photosynthesis. This study aims to present the working principle of CPV modules considering agricultural applications and discuss the recent advancements in concentrating agrivoltaics. In this method, the problem of shading is mitigated by two main strategies: (i) parabolic glasses covered with a multilayer dichroic polymer film that reflects near-infrared (NIR) radiation onto the solar cells installed at the focal area and transmits photons in the range of photosynthetically active radiation (PAR), and (ii) highly transparent sun-tracking louvers or Fresnel lenses that concentrate direct sunlight onto the solar cells to generate electricity. In the latter solution, the remaining diffuse sunlight is directed to the ground for use by growing plants. Although the CPV development trend has been slow due to the lower cost of crystalline silicon, the development of CPV for agriculture with accurate spectral separation could revitalize this industry. In this regard, more research and development are needed to evaluate the suitability of materials that split solar radiation and their impacts on the electrical performance of CPV modules, taking into account the physiology of plants.
In this paper, the melting and solidification behaviours of the PCM in an indirect contact mobilized thermal energy storage (ICM-TES) container were numerically investigated to facilitate the further understanding of the phase change mechanism in the container. A 2D model was built based on the simplification and assumptions of experiments, which were validated by comparing the results of computations and measurements. Then, three options, i.e., a high thermal conductivity material (expanded graphite) addition, the tube diameter and the adjustment of the internal structure of the container and fin installation, were analyzed to seek effective approaches for the improvement of the ICM-TES performance. The results show that the optimal parameters of the three options are 10vol.% (expanded graphite proportion), 22mm (tube diameter) and 0.468m2 (fin area). When the three options are applied simultaneously, the charging time is reduced by approximately 74% and the discharging time by 67%.