能源与电网

2022
Haiyang Lin, Caiyun Bian, Yu Wang, Hailong Li, Qie Sun, and Fredrik Wallin. 2022. “Optimal planning of intra-city public charging stations.” Energy, 238, Part C, January, Pp. 121948. Publisher's VersionAbstract
Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.
2021
Xi Lu, Chris P. Nielsen, Chongyu Zhang, Jiacong Li, Xu He, Ye Wu, Shuxiao Wang, Feng Song, Chu Wei, Kebin He, Michael P. McElroy, and Jiming Hao. 2021. “Combined solar power and storage as cost-competitive and grid-compatible supply for China’s future carbon-neutral electricity system.” Proceedings of the National Academy of Sciences, 118, October, Pp. 42. Publisher's VersionAbstract
As the world’s largest CO2 emitter, China’s ability to decarbonize its energy system strongly affects the prospect of achieving the 1.5 °C limit in global, average surface-temperature rise. Understanding technically feasible, cost-competitive, and grid-compatible solar photovoltaic (PV) power potentials spatiotemporally is critical for China’s future energy pathway. This study develops an integrated model to evaluate the spatiotemporal evolution of the technology-economic-grid PV potentials in China during 2020 to 2060 under the assumption of continued cost degression in line with the trends of the past decade. The model considers the spatialized technical constraints, up-to-date economic parameters, and dynamic hourly interactions with the power grid. In contrast to the PV production of 0.26 PWh in 2020, results suggest that China’s technical potential will increase from 99.2 PWh in 2020 to 146.1 PWh in 2060 along with technical advances, and the national average power price could decrease from 4.9 to 0.4 US cents/kWh during the same period. About 78.6% (79.7 PWh) of China’s technical potential will realize price parity to coal-fired power in 2021, with price parity achieved nationwide by 2023. The cost advantage of solar PV allows for coupling with storage to generate cost-competitive and grid-compatible electricity. The combined systems potentially could supply 7.2 PWh of grid-compatible electricity in 2060 to meet 43.2% of the country’s electricity demand at a price below 2.5 US cents/kWh. The findings highlight a crucial energy transition point, not only for China but for other countries, at which combined solar power and storage systems become a cheaper alternative to coal-fired electricity and a more grid-compatible option.
Lu et al. is the cover article of this October issue of PNAS
Xinyu Chen, Yaxing Liu, Qin Wang, Jiajun Lv, Jinyu Wen, Xia Chen, Chongqing Kang, Shijie Cheng, and Michael McElroy. 2021. “Optimized pathways towards carbon neutrality in China with negative CO2 abatement costs informed by high-resolution system modeling.” Joule, 5, 10 (20 October), Pp. 2715-2741. Publisher's Version
Yu Fu, Haiyang Lin, Cuiping Ma, Bo Sun, Hailong Li, Qie Sun, and Ronald Wennersten. 2021. “Effects of uncertainties on the capacity and operation of an integrated energy system.” Sustainable Energy Technologies and Assessments, 48, December, Pp. 101625. Publisher's VersionAbstract

Uncertainty is a common and critical problem for planning the capacity and operation of integrated energy systems (IESs). This study evaluates the effects of uncertainties on the capacity and operation of an IES. To this aim, system planning and operation with uncertainties are optimized by a two-stage stochastic programming model and compared with a referencing deterministic case. Specifically, the uncertainties of photovoltaic (PV) generation and energy demand are investigated.

Regarding system capacity, a larger energy storage capacity is needed to accommodate a higher uncertainty. The superimposed uncertainties have a higher effect on system capacity than the sum of the effect of each uncertainty. The uncertainty of energy demand has a higher impact than the uncertainty of PV generation.

Regarding system operation, the increase in operation cost is smaller than the increase in investment cost and total cost. In addition, the average flexibility provided by the energy storage increases with uncertainty and uncertainties affect the change rate for power charging/discharging of the electric energy storage. Regarding the effect on the grid, the uncertainties increase not only the magnitude of ramping-rate, but also the frequency of power-dispatch.

Minghao Zhuang, Xi Lu, Wei Peng, Yanfen Wang, Jianxiao Wang, Chris P. Nielsen, and Michael B. McElroy. 2021. “Opportunities for household energy on the Qinghai-Tibet Plateau in line with United Nations’ Sustainable Development Goals.” Renewable and Sustainable Energy Reviews, 144, July 2021, Pp. 110982. Publisher's VersionAbstract
Approximately seven million population in the Qinghai-Tibet Plateau of China, a global climate sensitive region, still rely primarily on yak dung for household cooking and heating. The treatment and combustion of yak dung result in a variety of negative impacts in terms of local alpine grassland degradation, indoor air pollution, public health risk, as well as global climate change. There is an urgent need to explore alternative pathway for affordable and clean energy as indicated in the United Nations’ Sustainable Development Goals for 2030. This perspective has analyzed the key challenges rooted in yak dung use on the Qinghai-Tibet Plateau region. Based on this, this perspective has further proposed a new complementary energy system to take advantage of locally available, clean and sustainable energy sources of wind and solar power, and have provided economic analyses. Meanwhile, this perspective has pointed out the potential barriers to promoting the new complementary energy system in the Qinghai-Tibet Plateau region due to traditional habits, economic factors and policies. Finally, strategies for transitioning from yak dung to the proposed alternative energy system is discussed at the end. Successful energy transition for the Qinghai-Tibet Plateau region offers an important option to achieving many other sustainable development goals related to climate change, economic development, and environment. The perspective is expected to shed light on the development of sustainable energy in other developing region or countries in the world to address multiple societal goals.
Jaume Freire-González and Mun S. Ho. 2021. “Voluntary actions in households and climate change mitigation.” Journal of Cleaner Production, 321, 25 October 2021, Pp. 128930. Publisher's VersionAbstract
Governments foster voluntary actions within households to mitigate climate change. However, the literature suggests that they may not be as effective as expected due to rebound effects. We use a dynamic economy–energy–environment computable general equilibrium (CGE) model of the Catalan economy to simulate the effect of 75 different actions on GDP and net CO2 emissions, over a 20-year period. We also examine how a carbon tax could counteract the carbon rebound effects. We find energy rebound effects ranging from 61.77% to 117.49% for voluntary energy conservation actions, depending on where the spending is redirected, with similar carbon rebound values. In our main scenarios, where energy savings are redirected to savings and all non-energy goods proportionally, the rebound is between 64.47% and 66.90%. We also find, for these scenarios, that a carbon tax of between 2.4 and 3.6 €/ton per percentage point of voluntary energy reduction would totally offset carbon rebound effects. These results suggest that voluntary actions in households need additional measures to provide the expected results in terms of energy use reduction and climate change mitigation.
Haiyang Lin, Qiuwei Wu, Xinyu Chen, Xi Yang, Xinyang Guo, Jiajun Lv, Tianguang Lu, Shaojie Song, and Michael B. McElroy. 2021. “Economic and Technological Feasibility of Using Power-to-Hydrogen Technology under Higher Wind Penetration in China.” Renewable Energy, 173, Pp. 569-580. Publisher's VersionAbstract
Hydrogen can play a key role in facilitating the transition to a future deeply decarbonized energy system and can help accommodate higher penetrations of renewables in the power system. Arguments to justify this conclusion are supported by an analysis based on real-world data from China’s Western Inner Mongolia (WIM). The economic feasibility and decarbonization potential of renewable-based hydrogen production are discussed through an integrated power-hydrogen-emission analytical framework. The framework combines a high-resolution wind resource analysis with hourly simulation for the operation of power systems and hydrogen production considering technical and economic specifications on selection of three different types of electrolyzers and two operating modes. The results indicate that using wind power to produce hydrogen could provide a cost-competitive alternative (<2 $kg-1) to WIM’s current coal-dominated hydrogen manufacturing system, contributing at the same time to important reductions in wind curtailment and CO2 emissions. The levelized cost for hydrogen production is projected to decrease in the coming decade consistent with increases in wind power capacity and decreases in capital costs for electrolyzers. Lessons learned from the study can be applied to other regions and countries to explore possibilities for larger scale economically justified and carbon saving hydrogen production with renewables.
Cao Jing, Hancheng Dai, Shantong Li, Chaoyi Guo, Mun Ho, Wenjia Cai, Jianwu He, Hai Huang, Jifeng Li, Yu Liu, Haoqi Qian, Can Wang, Libo Wu, and Xiliang Zhang. 2021. “The general equilibrium impacts of carbon tax policy in China: a multi-model assessment.” Energy Economics, 99, July 2021, Pp. 105284. Publisher's VersionAbstract
We conduct a multi-model comparison of a carbon tax policy in China to examine how different models simulate the impacts in both near-term 2020, medium-term 2030, and distant future 2050. Though Top-down computable general equilibrium(CGE) models have been applied frequently on climate or other environmental/energy policies to assess emission reduction, energy use and economy-wide general equilibrium outcomes in China, the results often vary greatly across models, making it challenging to derive policies. We compare 8 China CGE models with different characteristics to examine how they estimate the effects of a plausible range of carbon tax scenarios – low, medium and high carbon taxes.. To make them comparable we impose the same population growth, the same GDP growth path and world energy price shocks. We find that the 2030 NDC target for China are easily met in all models, but the 2060 carbon neutrality goal cannot be achieved even with our highest carbon tax rates. Through this carbon tax comparison, we find all 8 CGE models differ substantially in terms of impacts on the macroeconomy, aggregate prices, energy use and carbon reductions, as well as industry level output and price effects. We discuss the reasons for the divergent simulation results including differences in model structure, substitution parameters, baseline renewable penetration and methods of revenue recycling.
Haiyang Lin, Caiyun Bian, Yu Wang, Hailong Li, Qie Sun, and Fredrik Wallen. 2021. “Optimal planning of intra-city public charging stations.” Energy, Volume 238, Part C, 1 January 2022, Pp. 121948. Publisher's VersionAbstract
Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.
energy.pdf
Peter Sherman, Shaojie Song, Xinyu Chen, and Michael B. McElroy. 2021. “Projected changes in wind power potential over China and India in high resolution climate models.” Environmental Research Letters, 16, 3. Publisher's VersionAbstract
As more countries commit to emissions reductions by midcentury to curb anthropogenic climate change, decarbonization of the electricity sector becomes a first-order task in reaching this goal. Renewables, particularly wind and solar power, will be predominant components of this transition. How availability of the wind and solar resource will change in the future in response to regional climate changes is an important and underdiscussed topic of the decarbonization process. Here, we study changes in potential for wind power in China and India, evaluating prospectively until the year 2060. To do this, we study a downscaled, high-resolution multimodel ensemble of CMIP5 models under high and low emissions scenarios. While there is some intermodel variability, we find that spatial changes are generally consistent across models, with decreases of up to 965 (a 1% change) and 186 TWh (a 2% change) in annual electricity generation potential for China and India, respectively. Compensating for the declining resource are weakened seasonal and diurnal variabilities, allowing for easier large-scale wind power integration. We conclude that while the ensemble indicates available wind resource over China and India will decline slightly in the future, there remains enormous potential for significant wind power expansion, which must play a major role in carbon neutral aspirations.
Qing Yang, Hewen Zhou, Pietro Bartocci, Francesco Fantozzi, Ondřej Mašek, Foster Agblevor, Zhiyu Wei, Haiping Yang, Hanping Chen, Xi Lu, Guoqing Chen, Chuguang Zheng, Chris P. Nielsen, and Michael B. McElroy. 2021. “Prospective contributions of biomass pyrolysis to China’s 2050 carbon reduction and renewable energy goals.” Nature Communications. Publisher's VersionAbstract
Deployment of negative emission technologies needs to start immediately if we are to avoid overshooting international carbon targets, reduce negative climate impacts, and minimize costs of emission mitigation. Actions in China, given its importance for the global anthropogenic carbon budget, can be decisive. While bioenergy with carbon capture and storage (BECCS) may need years to mature, this study focuses on developing a ready-to-implement biomass intermediate pyrolysis poly-generation (BIPP) technology to produce a potentially stable form of biochar, a medium for carbon storage, and to provide a significant source of valuable biofuels, especially pyrolysis gas. Combining the experimental data with hybrid models, the results show that a BIPP system can be profitable without subsidies: its national deployment could contribute to a 68% reduction of carbon emissions per unit of GDP in 2030 compared to 2005 and could result additionally in a reduction in air pollutant emissions. With 73% of national crop residues converted to biochar and other biofuels in the near term (2020 to 2030), the cumulative greenhouse gas (GHG) reduction could reach up to 5653 Mt CO2-eq by 2050, which could contribute 9-20% of the global GHG emission reduction goal for BECCS (28-65 Gt CO2-eq in IPCC’s 1.5 °C pathway), and nearly 2633 Mt more than that projected for BECCS alone. The national BIPP development strategy is developed on a provincial scale based on a regional economic and life-cycle analysis. 
Tianguang Lu, Xinyu Chen, Michael B. McElroy, Chris Nielsen, Wu Qiuwei, Hongying He, and Qian Ai. 2021. “A reinforcement learning-based decision system for electricity pricing plan selection by smart grid end users.” IEEE Transactions on Smart Grid, 1949-3061 . Publisher's VersionAbstract
With the development of deregulated retail power markets, it is possible for end users equipped with smart meters and controllers to optimize their consumption cost portfolios by choosing various pricing plans from different retail electricity companies. This paper proposes a reinforcement learning-based decision system for assisting the selection of electricity pricing plans, which can minimize the electricity payment and consumption dissatisfaction for individual smart grid end user. The decision problem is modeled as a transition probability-free Markov decision process (MDP) with improved state framework. The proposed problem is solved using a Kernel approximator-integrated batch Q-learning algorithm, where some modifications of sampling and data representation are made to improve the computational and prediction performance. The proposed algorithm can extract the hidden features behind the time-varying pricing plans from a continuous high-dimensional state space. Case studies are based on data from real-world historical pricing plans and the optimal decision policy is learned without a priori information about the market environment. Results of several experiments demonstrate that the proposed decision model can construct a precise predictive policy for individual user, effectively reducing their cost and energy consumption dissatisfaction.
Jing Cao, Mun S. Ho, Rong Ma, and Fei Teng. 2021. “When carbon emission trading meets a regulated industry: Evidence from the electricity sector of China.” Journal for Public Economics, 200, August 2021, Pp. 104470. Publisher's VersionAbstract
This paper provides retrospective firm-level evidence on the effectiveness of China’s carbon market pilots in reducing emissions in the electricity sector. We show that the carbon emission trading system (ETS) has no effect on changing coal efficiency of regulated coal- fired power plants. Although we find a significant reduction in coal consumption associated with ETS participation, this reduction was achieved by reducing electricity production. The output contraction in the treated plants is not due to their optimizing behavior but is likely driven by government decisions, because the impacts of emission permits on marginal costs are small relative to the controlled electricity prices and the reduction is associated with financial losses. In addition, we find no evidence of carbon leakage to other provinces, but a significant increase in the production of non-coal-fired power plants in the ETS regions. 
2020
Jing Cao, Mun S Ho, and Rong Ma. 2020. “Analyzing Carbon Pricing Policies using a General Equilibrium Model with Production Parameters Estimated using Firm Data.” Energy Economics. Publisher's VersionAbstract

Policy simulation results of Computable General Equilibrium (CGE) models largely hinge on the choices of substitution elasticities among key input factors. Currently, most CGE models rely on the common elasticities estimated from aggregated data, such as the GTAP model elasticity parameters. Using firm level data, we apply the control function method to estimate CES production functions with capital, labor and energy inputs and find significant heterogeneity in substitution elasticities across different industries. Our capital-labor substitution elasticities are much lower than the GTAP values while our energy elasticities are higher. We then incorporate these estimated elasticities into a CGE model to simulate China’s carbon pricing policies and compare with the results using GTAP parameters. Our less elastic K-L substitution lead to lower base case GDP growth, but our more elastic energy substitution lead to lower coal use and carbon emissions. In the carbon tax policy exercises, we find that our elasticities lead to easier reductions in coal use and carbon emissions.

Fei Xiao, Tianguang Lu, Qian Ai, Xiaolong Wang, Xinyu Chen, Sidun Fang, and Qiuwei Wu. 2020. “Design and implementation of a data-driven approach to visualizing power quality.” IEEE Transactions on Smart Grid, 114, DOI: 10.1109/TSG.2020.2985767. Publisher's VersionAbstract
Numerous underlying causes of power-quality (PQ) disturbances have enhanced the application of situational awareness to power systems. This application provides an optimal overall response for contingencies. With measurement data acquired by a multi-source PQ monitoring system, we propose an interactive visualization tool for PQ disturbance data based on a geographic information system (GIS). This tool demonstrates the spatio–temporal distribution of the PQ disturbance events and the cross-correlation between PQ records and environmental factors, leveraging Getis statistics and random matrix theory. A methodology based on entity matching is also introduced to analyze the underlying causes of PQ disturbance events. Based on real-world data obtained from an actual power system, offline and online PQ data visualization scenarios are provided to verify the effectiveness and robustness of the proposed framework.
Tianguang Lu, Peter Sherman, Xinyu Chen, Shi Chen, Xi Lu, and Michael B. McElroy. 2020. “India’s potential for integrating solar and on- and offshore wind power into its energy system.” Nature Communications, 11, 4750. Publisher's VersionAbstract
This paper considers options for a future Indian power economy in which renewables, wind and solar, could meet 80% of anticipated 2040 power demand supplanting the country’s current reliance on coal. Using a cost optimization model, here we show that renewables could provide a source of power cheaper or at least competitive with what could be supplied using fossil-based alternatives. The ancillary advantage would be a significant reduction in India’s future power sector related emissions of CO2. Using a model in which prices for wind turbines and solar PV systems are assumed to continue their current decreasing trend, we conclude that an investment in renewables at a level consistent with meeting 80% of projected 2040 power demand could result in a reduction of 85% in emissions of CO2 relative to what might be expected if the power sector were to continue its current coal dominated trajectory.
Peter Sherman, Xinyu Chen, and Michael B. McElroy. 2020. “Offshore wind: an opportunity for cost-competitive decarbonization of China’s energy economy.” Science Advances, 6, 8, Pp. eaax9571.Abstract
China has reduced growth in its emissions of greenhouse gases, success attributable in part due to major investments in onshore wind. By comparison, investments in offshore wind have been minor, limited until recently largely by perceptions of cost. Assimilated meteorological data are used here to assess future offshore wind potential for China. Analysis on a provincial basis indicates that the aggregate potential wind resource is 5.4 times larger than current coastal demand for power. Recent experiences with markets both in Europe and the US suggest that potential offshore resources in China could be exploited to cost-competitively provide 1148.3 TWh of energy in a high-cost scenario, 6383.4 TWh in a low-cost option, equivalent to between 36% and 200% of the total coastal energy demand post 2020. The analysis underscores significant benefits for offshore wind for China, with prospects for major reductions greenhouse emissions with ancillary benefits for air quality.
Science_Advances_Full_Text_pdf
Yu Wang, Dasaraden Mauree, Qie Sun, Haiyang Lin, Jean-Louis Scartezzini, and Ronald Wennersten. 2020. “A review of approaches to low-carbon transition of high-rise residential buildings in China.” Renewable and Sustainable Energy Reviews, 131, October 2020, Pp. 109990. Publisher's VersionAbstract

In developing countries with a large population and fast urbanization, High-rise Residential Buildings (HRBs) have unavoidably become a very common, if not the most, accommodation solution. The paradigm of HRB energy consumption is characterized by high-density energy consumption, severe peak effects and a limited site area for integrating renewable energy, which constitute a hindrance to the low-carbon transition. This review paper investigates low-carbon transition efforts in the HRB sector from the perspective of urban energy systems to get a holistic view of their approaches. The HRB sector plays a significant role in reducing carbon emission and improving the resilience of urban energy systems. Different approaches to an HRB low-carbon transition are investigated and a brief overview of potential solutions is offered from the perspectives of improving energy efficiency, self-sufficiency and system resilience. The trends of decarbonization, decentralization and digitalization in the HRB sector allow a better alignment with transitioning urban energy systems and create cross-sectoral integration opportunities for low-carbon transition. It is also found that policy tools are powerful driving forces in China for incentivizing transition behaviors among utilities, end users and developers. Based on a comprehensive policy review, the policy implications are given. The research is geared for the situation in China but could also be used as an example for other developing countries that have similar urbanization patterns. Future research should focus on quantitative analysis, life-cycle analysis and transdisciplinary planning approaches.

2019
China’s CO2 peak before 2030 implied from diverse characteristics and growth of cities
Haikun Wang, Xi Lu, Yu Deng, Yaoguang Sun, Chris P. Nielsen, Yifan Liu, Ge Zhu, Maoliang Bu, Jun Bi, and Michael B. McElroy. 2019. “China’s CO2 peak before 2030 implied from diverse characteristics and growth of cities.” Nature Sustainability, 2, Pp. 748–754. Publisher's VersionAbstract
China pledges to peak CO2 emissions by 2030 or sooner under the Paris Agreement to limit global warming to 2 °C or less by the end of the century. By examining CO2 emissions from 50 Chinese cities over the period 2000–2016, we found a close relationship between per capita emissions and per capita gross domestic product (GDP) for individual cities, following the environmental Kuznets curve, despite diverse trajectories for CO2 emissions across the cities. Results show that carbon emissions peak for most cities at a per capita GDP (in 2011 purchasing power parity) of around US$21,000 (80% confidence interval: US$19,000 to 22,000). Applying a Monte Carlo approach to simulate the peak of per capita emissions using a Kuznets function based on China’s historical emissions, we project that emissions for China should peak at 13–16 GtCO2 yr−1 between 2021 and 2025, approximately 5–10 yr ahead of the current Paris target of 2030. We show that the challenges faced by individual types of Chinese cities in realizing low-carbon development differ significantly depending on economic structure, urban form and geographical location.
Ran Hao, Tianguang Lu, Qiuwei Wu, Xinyu Chen, and Qian Ai. 2019. “Distributed piecewise approximation economic dispatch for regional power systems under non-ideal communication.” IEEE Access, 7. Publisher's VersionAbstract
Appropriate distributed economic dispatch (DED) strategies are of great importance to manage wide-area controllable generators in wide-area regional power systems. Compared with existing works related to ED, where dispatch algorithms are carried out by a centralized controller, a practical DED scheme is proposed in this paper to achieve the optimal dispatch by appropriately allocating the load to generation units while guaranteeing consensus among incremental costs. The ED problem is decoupled into several parallel sub-problems by the primal-dual principle to address the computational issue of satisfying power balance between the demand and the supply from the distributed regional power system. The feasibility test and an innovative mechanism for unit commitment are then designed to handle extreme operation situations, such as low load level and surplus generation. In the designed mechanism, the on/off status of units is determined in a fully distributed framework, which is solved using the piecewise approximation method and the discrete consensus algorithm. In the algorithm, the push-sum protocol is proposed to increase the system adaptation on the time-varying communication topology. Moreover, consensus gain functions are designed to ensure the performance of the proposed DED under communication noise. Case studies on a standard IEEE 30-bus system demonstrate the effectiveness of our proposed methodology
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