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 VersionAbstractHydrogen 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 VersionAbstractWe 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 VersionAbstractIntra-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 VersionAbstractAs 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 VersionAbstractDeployment 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 VersionAbstractWith 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 VersionAbstractThis 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.