Share Of Capacity Research Articles

Can Shared Mobility Compensate for Public Transport Disruptions? The Case of Milan’s Bike Sharing System During the COVID-19 Pandemic

The COVID-19 pandemic poses an unprecedented challenge for public transport systems. The capacity of transport systems has been significantly reduced because of the social distancing measures. Therefore, new avenues to increase the resilience of public urban mobility need to be explored. In this work, we investigate the integration of bike sharing and public transport systems to compensate for limited public transport capacity under the disruptive impacts of the COVID-19 pandemic. As a first step, we develop a data analysis model to integrate the demand of the two underlying systems. Next, we build an optimization model for the design and operation of hybrid mixed-fleet bike sharing systems. We analyze the case of the subway and public bike sharing systems in Milan to assess this approach. We find that the bike sharing system (in its current state) can only compensate for a minor share of the public transport capacity, as the needs in fleet and station capacity are very high. However, the resilience of public urban mobility further increases when new design concepts for the bike sharing system are considered. An extension to a hybrid free-floating bike and docked e-bike system doubled the covered demand of the system. An extension of the station capacity of about 37% yields an additional increase of the covered demand by 6.5%–7.5%. On the other hand, such a hybrid mixed-fleet bike sharing system requires many stations and a relatively large fleet to provide the required mobility capacity, even at low demand requirements.

An assessment of environmental impacts and economic benefits of multiple aluminum production methods

The booming development of the aluminum industry has greatly contributed to China's economic development, but it also imposed a burden on the environment. Recent technological development has emerged various methods for aluminum production to improve production efficiency and reduce environmental impacts, while reducing energy intensity in traditional production practices can also lower emissions and remain low production costs. However, which approach that performs better in achieving economic benefits and reducing environmental impacts is unclear. This study analyzed six major aluminum production methods based on alumina production process and energy mix. Environmental parameters were derived based on life cycle assessment, and economic cost parameters were formed by building an economic benefits model. This paper then analyzed the potential of achieving economic benefits and environmental impacts reduction for each method using life cycle assessment and principal component analysis. Finally, the greenhouse gas emissions from the aluminum industry in 2030 based on scenario analysis was analyzed. We found that Bayer process-hydropower method performs the best in reducing environmental impacts and achieving economic benefits, while the sinter process-thermal power method performs the worst. The effect of reducing emissions by changing the energy mix (75%) was more significant than that by changing the alumina production process (up to 10%). Furthermore, we used scenario analysis to expand the capacity share of the Bayer process-hydropower method with optimal comprehensive benefit increased by 22.2%, the cost of electricity decreased by 313.77 CNY/t-Al, and the global warming potential was reduced by nearly 1/3. Thus, our results reveal the significant benefits of the Chinese government's push to increase the share of clean energy applications in the aluminum industry.

COMBINED METHOD OF ELECTRIC ENERGY CONSUMPTION MANAGEMENT OF PRODUCTION FACILITIES

The article investigates the methods of power consumption control. It is shown that the power shortage during peak hours makes it difficult to maintain a balance between generation and consumption capacity, which leads to the need to introduce restrictions on the electrical load of industrial consumers and the development of methods and tools to control power consumption. The need to manage energy consumption is due to a number of reasons, including: 1) the significant difference between peak load and night failure in power systems; 2) insufficient regulatory capacity of thermal power plants and nuclear power plants to cover the variable part of load schedules; 3) unfavorable tendency to reduce the share of shunting capacity in power systems caused by the consolidation of power units; 4) significant capital and energy costs associated with the construction and operation of peak units; 5) technical feasibility and economic feasibility of artificial alignment of load schedules. It is shown that the following methods of power consumption control are currently known: instantaneous rate; at the ideal norm; management on the forecast value; control with the use of average power on a moving time interval (moving window method) and combined methods that use different combinations, as well as the distribution of control influence between consumers - regulators (resource allocation method). It is better to consider such a control method that provides for a larger number of managed consumers random time distribution of possible short-term emissions, their minimum absolute value, as well as more complete use by the consumer of the declared capacity or allocated power and energy limits. According to these criteria, the listed management methods are compared. Moreover, the method of instantaneous rate is implemented in control or automatic control using a signal proportional to the average power for 1, 2 or 3 minutes, the method of the ideal norm involves measuring the average power of the consumer for short periods of time (up to three minutes) and comparing this value with the declared ( or limit) power, control with prediction is that the control signal is formed as the difference between the amount of possible power and predicted at the end of the control cycle. To increase the efficiency of power consumption management, a combined control method is proposed, which is a synthesis of two known methods - control at the ideal norm and control over the predicted value of power consumption, which combines the advantages of both methods. The condition of management is maintenance of such mode of power consumption at which the set capacity is not exceeded and its set value is used as much as possible. Fulfillment of this condition is provided by working off of the restrictions set to each step of management. Due to the fact that different control steps have different control reactions to the real process, appropriate control methods are used for different steps. In the first steps, when there is enough time to adopt the optimal control effect and it can be adjusted, the control is based on the forecast value of electricity consumption, in the last steps, which have special responsibility for the control process; control is carried out by the ideal norm. Thus, this method combines the advantages of forecast management (control effect is justified) and the method of management at the ideal norm (in the last step of management, which allows optimal use of the remaining power limit and not exceed the specified value) with a priori justified order of consumers-regulators.

Моделювання забезпечення балансової надійності енергосистеми в умовах значних обсягів відновлюваної генерації

The problems of functioning of the IPS of Ukraine at fast growth in its structure the renewable energy source (RES)capacities such as wind and solar power plants are considered. In existing conditions, the presence of a significant share of basic nuclear generation, a small maneuverable range of TPP power units, and a limited amount of highly maneuverable hydro generation of the existing flexibility of the power system is not enough to ensure demand-supply balance of the power system with surplus RES electricity generation. The solution to this problem is currently performed by using hydro-pumped storage during uncharacteristic daytime hours of the day and limiting of electricity supply of wind and power plants into the power system. A modern solution is the use of to the battery storage systems to transfer the surplus of electricity from these RES in hours of increased consumption. The article presents the developed approach to modeling the participation of wind and solar capacities in load coverage balances of the optimization model of the forecast structure of power system generating capacities, that takes into account both curtailment and accumulation of excess generation of these RES. The modeling results showed that with significant of wind and solar power capacities, providing balance coverage load during spring floods with a significant share of nuclear generation capacity and the need for water supply is carried out as using hydro-pumped capacity during daytime hours of surplus capacity, grid battery storage systems so and battery storage systems, working together with RES, and their power curtailment. Keywords: power system, balance reliability, mathematical model, battery energy storage system, load curve, power curtailment

Analysis on Capacity Sharing with Failed Match Based on the Evolutionary Game Theory

There is a problem of capacity mismatch between different companies in the current market. In this paper, we propose a dual-channel capacity sharing supply chain consisting of two competing manufacturers (i.e. a capacity seller and a capacity buyer) and one platform. Considering the gap of matching success rates, we investigate whether the buyer and seller can benefit from capacity sharing and how the different matching success rates influence the manufacturers’ decisions on spontaneously match through a platform. Through numerical simulation, we find that (1) the seller can always benefit from capacity sharing even when the match fails, while the buyer benefits from capacity sharing only when the capacity constraint is relatively severe; (2) both the buyer and seller prefer to participate through the platform when the platform has a sufficiently high advantage in matching success rates; (3) if the capacity constraint is much severe, the capacity buyer may turn to self-match rather than capacity sharing. Besides, we also study the sustainability of the capacity-sharing system and show how the platform can improve sustainability by forgoing accumulated profits.

Life cycle assessment‐based Absolute Environmental Sustainability Assessment is also relative

AbstractOver the past years, an increasing number of scholarly papers have used the planetary boundaries (PBs) within life cycle assessment (LCA) to determine if the life cycle impacts of a product system fit within those PBs and thereby establish the absolute sustainability of the product system. This type of LCA is nowadays coined as LCA‐based Absolute Environmental Sustainability Assessment (AESA). “Absolute” thereby refers to methods enabling the comparison of environmental impacts of products, companies, nations, and so on, with an assigned share of environmental carrying capacity for various impact categories. A recent review of LCA‐based AESA methods and their applications characterized 47 studies “according to their intended application, impact categories, basis of carrying capacity estimates, spatial differentiation of environmental model and principles for assigning carrying capacity.” However, the review and the majority of studies reviewed did not, or only to a limited extent, discuss potential temporal issues of assigning carrying capacity to product systems. Several of the carrying capacity estimates have a time dimension while LCA results lack a time dimension. In this article, we show that assigning PBs to product systems is only technically possible when adopting several fundamental though unrealistic assumptions, and conclude that even product LCA‐based AESA is relative. This should not withhold scholars from developing approaches applying the PBs in LCA, but it should prevent them from claiming and using the term “absolute.”

Power flow analysis considering solar road generation

To fight against climate change and environmental pollution, the share of renewable energy capacity immensely grows worldwide, especially photovoltaic power. Meanwhile, road transportation develops quickly for the convenience of traveling. Due to abundant solar resources in road transportation and flexible installation of photovoltaic power, solar road generation with huge generation potentials will be a promising solution to alleviate environmental burden in the future. To analyze the influence of solar road integration on power flow, this paper proposes a power flow (PF) analysis method with solar road integration. Based on the photovoltaic model, the solar road generation model coupled with traffic flow is formulated. Two representative scenarios are developed to represent the uncertainties of solar road (i.e., solar irradiation, traffic flow). Finally, the simulation results performed on IEEE 33-bus system under three test cases verify the feasibility and effectiveness of the proposed solar road generation model.

ПРОБЛЕМА ОЦІНКИ ЕКОНОМІЧНИХ ВТРАТ ВІД ВІЙСЬКОВОЇ АГРЕСІЇ ДЛЯ УКРАЇНИ

Russia's war against Ukraine has caused a humanitarian, social, and economic catastrophe for Ukraine, as well as a major risk factor and uncertainty in the economic, humanitarian, social, and security spheres in Europe. These phenomena in a globalized world can cause a crisis around the world, going far beyond the continent. It is possible to estimate the amount of losses for industry, infrastructure, agriculture of Ukraine only after the cessation of the active phase of hostilities. However, data on losses are needed at the present stage to plan recovery, justify financial assistance to international agencies and donor countries, and to use the total amount of losses in lawsuits against the aggressor country. This was the reason for the urgency of such a study. The article systematizes the challenges of economic and social development in the regional and global aspects, high probability of rising food and energy prices was pointed out. The main negative consequences are expressed in the humanitarian and social spheres, rising prices and food and raw materials, as well as security risks. The authors summarize the data on losses for the Ukrainian economy from the military conflict. The analysis was conducted within certain regions of Ukraine, industries. It is noted that the most affected regions of Ukraine were the regions with the greatest production potential. The dynamics of changes in the production load of enterprises and institutions of Ukraine from the beginning of March to the end of May is analyzed. Emphasis is placed on the share of production capacity of certain industries located in the liberated and temporarily occupied regions of the country. The threatening condition of metallurgy and mechanical engineering is noted. Thus, planning the recovery of Ukraine's economy in the postwar period is impossible without careful and correct consideration of all damage to industrial, infrastructural and social facilities. Obtaining Ukraine's candidate status for accession to the European Union can facilitate the procedure for financing post-war reconstruction and the path to future membership will be the key to the European vector of development of Ukraine.

Tek Büyük Kent Kuramı Ekseninde Benin: Cotonou Örneği

Jefferson's “law of the primate city” states that the principal city of a country always disproportionately and deliberately represents the national economic capacity and the sense of nation in the population. This study examines the extent to which Cotonou, the economic capital of Benin, is fully in line with Jefferson's “law”. Some spatial and situational factors were highlighted to show how Cotonou has become the most populous city and dominant economic city in Benin. Considering that Cotonou is disproportionately large and has a significant share of the country's economic capacity, it is clear that today there is some uncertainty as to whether Cotonou is truly representative of national feeling. In order to clarify this issue, an explanation of the cultural landscape, a literature review and interviews with Beninese residents are conducted to assess the extent to which Cotonou represents national feeling. Furthermore, it is noted that as Benin modernizes, Cotonou will continue to attract more people from other parts of Benin and may therefore become more representative of the country's cultural identity.

Management extensification in oil palm plantations reduces SOC decomposition

Large scale oil palm monocultures are continuously replacing Indonesia's tropical rainforests. The impact of intensive nitrogen (N) fertilization and herbicide application on biogeochemical processes in these monocultures remains unknown. Thus, we aim to understand NPK and herbicide effects on soil carbon (C) cycle. We hypothesize that (1) increased microbial activity due to N fertilization leads to faster soil organic matter (SOM) decomposition and to increased CO2 emissions from soil. Despite this, we expect (2) that herbicide application increases soil organic carbon (SOC) sequestration, as it counteracts the fertilizer's effects by hampering soil microbial activity, by deactivating the same synthesizing pathway as in plants, leading to decreased microbial respiration. We investigated the effects of fertilization (conventional and reduced NPK) and weed control (herbicide or mechanical weeding) on SOC decomposition in the rows between the palms (interrows) and around the palm stems (weeding circles). 14C labelled glucose was added to soil to analyze the response of microbial activity and SOC mineralization during 30-day incubation. Conventional fertilization caused microbial activation and destabilized SOC by priming, resulting in increased CO2 efflux. Glyphosate application plus fertilization further increased microbial activity contradicting our hypothesis. In combination with high fertilizer amounts, glyphosate strongly increased microbial activity. NPK might occupy a greater share of sorption capacities; hence, glyphosate is still available and can act as an additional source of C and possibly N and P. Therefore, SOC decomposition was 1.5 accelerated compared to the control when glyphosate and fertilizer application were combined. In contrast, reduced SOC decomposition, i.e., a strong negative priming effect (−47.9 μg g −1), occurred under reduced NPK fertilization without herbicides suggesting positive effects on C accumulation and storage. Our results emphasize the risk of management intensification and the need for a low-impact management strategy to maintain soil fertility and the function as a C reservoir.

Profitability vs. Stability: The Choice of Trading Strategies in a Capacity Sharing Supply Chain

Supported by a third-party capacity sharing platform, manufacturers can share capacities with others to match the rapidly changing demand. Both the capacity requestor and the capacity provider can choose to seek or wait for matches, forming different trading strategies (capacity- and demand-driven strategies). Based on the game and chaos theories, this paper analyzes the preference of the capacity provider, the capacity requestor, and the capacity platform operator on different trading strategies from the aspects of profitability and stability. It finds that the platform operator values stability much more than profitability, although the latter may reach higher optimal expected profits. The preference of each supply chain member is influenced by the production cost, potential market size, and the limited capacity of the capacity requestor. A stable system can result in higher long-run profits than a profitable system. We further propose the all-win situation for the capacity provider, capacity requestor, and platform operator.

A Short-Term Power Output Forecasting Based on Augmented Naïve Bayes Classifiers for High Wind Power Penetrations

Renewable-power-generating resources can provide unlimited clean energy and emit at most minute amounts of air pollutants and greenhouse gases, whereas fossil fuels are contributing to environmental pollution problems and climate change. The share of global power capacity comprising renewable-power-generating resources is increasing. However, due to the variability and uncertainty of wind resources, predicting the power output of these resources remains a key problem that must be resolved to establish stable power system operation and planning. In this study, we propose an ensemble prediction model for wind-power-generating resources based on augmented naïve Bayes classifiers. To select the principal component that affects the wind power outputs from among various meteorological factors, such as temperature, wind speed, and wind direction, prediction of wind-power-generating resources was performed using multiple linear regression (MLR) and a naïve Bayes classification model based on the selected meteorological factors. We proposed applying the analogue ensemble (AnEn) algorithm and the ensemble learning technique to predict the wind power. To validate this proposed hybrid prediction model, we analyzed empirical data from the wind farm of Jeju Island in South Korea and found that the proposed model has lower error than the single prediction models.

A Multi-Agent Reinforcement Learning Approach for Capacity Sharing in Multi-Tenant Scenarios

5G is envisioned to simultaneously provide diverse service types with heterogeneous needs under very different application scenarios and business models. Therefore, network slicing is included as a key feature of the 5G architecture to allow sharing a common infrastructure among different tenants, such as mobile communication providers, vertical market players, etc. In order to provide the Radio Access Network (RAN) with network slicing capabilities, mechanisms that efficiently distribute the available capacity among the different tenants while satisfying their needs are required. For this purpose, this paper proposes a multi-agent reinforcement learning approach for RAN capacity sharing. It makes use of the Deep Q-Network algorithm in a way that each agent is associated to a different tenant and learns the capacity to be provided to this tenant in each cell while ensuring that the service level agreements are satisfied and that the available radio resources are efficiently used. The consideration of multiple agents contributes to a better scalability and higher learning speed in comparison to single-agent approaches. In this respect, results show that the policy learnt by the agent of one tenant can be generalised and directly applied by other agents, thus reducing the complexity of the training and making the proposed solution easily scalable, e.g., to add new tenants in the system. The proposed approach is well aligned with the on-going 3GPP standardization work and guidelines for the parametrization of the solution are provided, thus enforcing its practical applicability.

Combustion operating conditions for municipal Waste-to-Energy facilities in the U.S.

This paper reports the first known comprehensive survey of combustion operating conditions across the wide range of municipal waste-to-energy facilities in the U.S. The survey was conducted in a step-wise fashion. Once the population of 188 units operating at over 70 facilities was defined, this population was stratified by distinguishing characteristics of combustion technology. Stratum-level estimates for operating conditions were determined from data collected in the survey. These stratum-level values were weighted by corresponding design capacity share and combined to infer national-level operating parameter estimates representative of the overall population. Survey results show that typical municipal waste-to-energy combustion operating conditions in the U.S. are (1) furnace temperature above 1160°C, (2) gas residence time above 2.4s, (3) exit gas concentrations of nearly 10% for oxygen (dry basis), and (4) over 16% for moisture. These operating parameter values can serve as benchmarks for laboratory-scale studies representative of municipal waste-to-energy combustion as typically practiced in the U.S.

Identifying critical corridors during an area-wide disruption by evaluating network bottleneck capacity

This paper applies the min-cut max-flow theorem combined with a grid cell disruption method over a large transportation network, to identify the importance of network locations in providing travel capacity when a community is evacuating (say, from wildfire). We develop metrices that look at the importance and contribution of individual links to network bottleneck capacity in traveling from the evacuating community to the shelter community. The purpose of this is to determine the network location that is the most restrictive of all, and more importantly, where it is in reference to the evacuating community location. We apply this method to the highway network of Alberta, Canada, with evacuating communities identified as those that have been under wildfire threat historically and/or are expected to in the future. We find that in all cases, network locations that contribute the greatest share of bottleneck capacity, are located adjacent to these evacuating communities. Next, we look at combining the measure for several communities, finding that the highways in remote northern Alberta are important despite some of them having lower capacity than the multi-lane highways in the south. Application of this simple method can support provincial and local municipal governments in deciding which communities require more detailed emergency evacuation studies to better identify and communicate transportation network deficiencies to provincial and federal bodies that would be making infrastructure investments towards community health and resilience.

Multi-objective approach for the performance and economic optimization of the two TED sub-cooled trans-critical carbon dioxide cycle

Abstract Although a thermoelectric device (TED) sub-cooler can improve the trans-critical carbon dioxide (TCO2) cycle, the maximum heating capacity by a single TED is limited by its internal properties. This paper integrates two serially connected and independently powered TED sub-cooler devices into the trans-critical carbon dioxide (TCO2) cycle to achieve a better share of the total heating capacity amongst the TED sub-coolers. A multi-objective optimization approach is used to further optimize this new TCO2+2-TED cycle in terms of coefficient of performance (COP) and system size. A capital cost analysis is also conducted to prove that this implementation is economically feasible. In the analysis, the effect of the number of thermoelectric modules, the heating capacity ratio between the two TED sub-coolers, and the type of thermoelectric module have been studied. Furthermore, both the water heating and refrigeration case studies have been separately studied by using the NSGA-II algorithm. Results show that, in both cases, only one unique solution out of 50 in the Pareto front registered the TCO2+2-TED cycle, which offered a further 6.24% COP improvement for water heating over the common TCO2+TED cycle solutions. The TED sub-cooler costs 20% of the compressor, so the solution is reasonably economical.

Полнота использования ресурсов недр и здоровье населения горнодобывающего региона

The study of the biochemical status of the population revealed a decrease in the antiradical activity and inhibition of the oxidase activity. The dynamics of glutathione reductase activity was established, which is a consequence of metal-induced intoxication. Indicators of the health status of the population of mining areas correlate with the number of pollutants entering the environment and the size of the contaminated area. The advances development of metal-induced oxidative stress was established, which reduces the quality and duration of human life. The health of the inhabitants of the mining region and the loss of metals during the extraction of ores depend on the share of dust and fine ore fractions, which, during enrichment end up in waste and are carried by water and wind. It is shown that the minimization of chemical pollution of the environment with metals is possible with the use of technologies that limit the contact of ores with the environmental ecosystems. At the same time, aggressive small fractions do not enter the habitat, and the extraction efficiency increases due to the recovery of the previously lost metals. The technology of leaching metals in the underground blocks was industrially used for more than half a century ensuring in some cases a large share of the production capacity of the enterprises. Leaching in the disintegrators passed the stage of laboratory research on the Sadon polymetallic ores and ferruginous quartzites of the Lebedinskoye deposit. The results of study of the quality of mined ores use, including the effect of dust and fine ore fractions on the health of the population are consistent with the conclusions of the researchers. It is concluded that there is a correlation between the health of residents of residential areas and the quality of mined ores use. Therefore, expanding the scope of metal leaching technologies is the key in solving the problems of rational use of subsoil resources and ensuring the safety of workers.

Low-temperature waste heat enabling abandoning coal in Espoo district heating system

Espoo has set a goal to abandon the use of coal in its district heating system by the year 2025. The local district heating operator is producing a major share of Espoo's heat demand with combined heat and power units, but a large share of that thermal capacity will be closed by 2025. The plan is to replace the closed down capacity with renewable fuels, heat pumps and waste heat utilisation. The goal of this paper is to simulate the impacts of these emission reductive acts on the production costs and CO2 emissions of the system. The possibility of utilising waste heat from data centres in the district heating system is evaluated. The results show that abandoning coal in the city's heating system leads to a significant reduction of CO2 emissions with a small increase of annual production costs. Waste heat enables emission reductions even further, and the increase of production costs can be prevented.

Development of Solar Energy and Its Place in the Energy Sector of the Republic of Buryatia

Solar energy is one of the priority directions for the development of alternative energy. This is facilitated by climatic characteristics. Buryatia has up to 300 sunny days a year. The amount of solar radiation in Buryatia is 4-5 kWh per m2/day (Fig. 1), and the duration of sunshine is more than 2000 hours per year (Fig. 2). Three investment companies are already operating in Buryatia: LLC “Avelar Solar Technology”, LLC “Complex Industry” and LLC “Green Energy Rus” (Table 2), which in the period of 2017-2019 have already built 5 solar power plants (SPP) with a capacity of 70 MW and a total cost of 8.7 billion rubles (more than $115 mln1). To date, the share of SPP capacity of the total capacity of Buryatia is 4.81%. Until 2022, it is planned to commission another 7 SPPs with a capacity of 155 MW, thus increasing the total capacity to 225 MW (Table 2) and the share to 14%, if the situation with CHPP-2 does not change. All SPP capacities are being introduced into the general energy system of the Southern energy district of the Republic of Buryatia, and will not be isolated energy systems.

The feasibility of heavy battery electric trucks

Summary Research on the decarbonization of transport often concludes that heavy battery electric trucks are infeasible due to the incompatibility of long driving distance with high energy use and low specific energy and high costs of batteries. However, emphasis is often placed on battery electric range matching that of diesel trucks, instead of overall competitiveness. We model battery electric trucks that use high-power fast charging, enabling smaller batteries and showing that the economics of battery electric trucks per ton-kilometer improves with greater weight, driven by increasing load capacity as well as increased energy savings as a function of weight. Furthermore, we show that previous findings that the competitiveness per kilometer is worse for heavy trucks than for lighter trucks are very sensitive to assumptions about the battery cost per kWh and lifetime of the battery pack. Given the rapid development of batteries, we conclude that the economic feasibility of heavy battery electric trucks might have been generally underestimated.