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Chen, Xinyu

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Xinyu Chen, Yaxing Liu, Qin Wang, Jiajun Lv, Jinyu Wen, Xia Chen, Chongqing Kang, Shijie Cheng, and Michael McElroy. In Press. “Optimized pathways towards carbon neutrality in China with negative CO2 abatement costs informed by high-resolution system modeling.” Joule.
2021
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.
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, Pp. 034057. 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.
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, 12, 3, Pp. 2176-2187. 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.
2020
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, 5, Pp. 4366-4379. 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. Publisher's VersionAbstract
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
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2019
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, Pp. 45533-45543. 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
IEEE_Full_Text
Xingning Han, Xinyu Chen, Michael B. McElroy, Shiwu Liao, Chris P. Nielsen, and Jinyu Wen. 2019. “Modeling formulation and validation for accelerated simulation and flexibility assessment on large scale power systems under higher renewable penetrations.” Applied Energy, 237, 1 March, Pp. 145-154. Publisher's VersionAbstract
Deploying high penetration of variable renewables represents a critical pathway for decarbonizing the power sector. Hydro power (including pumped-hydro), batteries, and fast responding thermal units are essential in providing system flexibility at elevated renewable penetration. How to quantify the merit of flexibility from these sources in accommodating variable renewables, and to evaluate the operational costs considering system flexibility constraints have been central challenges for future power system planning. This paper presents an improved linear formulation of the unit commitment model adopting unit grouping techniques to expedite evaluation of the curtailment of renewables and operational costs for large-scale power systems. All decision variables in this formulation are continuous, and all chronological constraints are formulated subsequently. Tested based on actual data from a regional power system in China, the computational speed of the model is more than 20,000 times faster than the rigorous unit commitment model, with less than 1% difference in results. Hourly simulation for an entire year takes less than 3 min. The results demonstrate strong potential to apply the proposed model to long term planning related issues, such as flexibility assessment, wind curtailment analysis, and operational cost evaluation, which could set a methodological foundation for evaluating the optimal combination of wind, solar and hydro investments.
Hongjian Wei, Wenzhi Liu, Xinyu Chen, Qing Yang, Jiashuo Li, and Hanping Chen. 2019. “Renewable bio-jet fuel production for aviation: a review.” Fuel, 254, 15 October, Pp. 115599. Publisher's VersionAbstract

Due to excessive greenhouse gas emissions and high dependence on traditional petroleum jet fuel, the sustainable development of the aviation industry has drawn increasing attention worldwide. One of the most promising strategies is to develop and industrialize alternative aviation fuels produced from renewable resources, e.g. biomass. Renewable bio-jet fuel has the potential to reduce CO2 emissions over their life cycle, which make bio-jet fuels an attractive substitution for aviation fuels. This paper provided an overview on the conversion technologies, economic assessment, environmental influence and development status of bio-jet fuels. The results suggested that hydrogenated esters and fatty acids, and Fischer-Tropsch synthesis can be the most promising technologies for bio-jet fuels production in near term. Future works, such as searching for more suitable feedstock, improving competitiveness for alternative jet fuels, meeting emission reduction targets in large-scale production and making measures for the indirect impact are needed for further investigation. The large-scale deployment of bio-jet fuels could achieve significant potentials of both bio-jet fuels production and CO2 emissions reduction based on future available biomass feedstock.

2018
Xinyu Chen, Junling Huang, Qing Yang, Chris P. Nielsen, Dongbo Shi, and Michael B. McElroy. 2018. “Changing carbon content of Chinese coal and implications for emissions of CO2.” Journal of Cleaner Production, 194, Pp. 150-157. Publisher's VersionAbstract

The changing carbon content of coal consumed in China between 2002 and 2012 is quantified using information from the power sector. The carbon content decreased by 7.7% over this interval, the decrease particularly pronounced between 2007 and 2009. Inferences with respect to the changing carbon content of coal and the oxidation rate for its consumption, combined with the recent information on coal use in China, are employed to evaluate the trend in emissions of CO2. Emissions are estimated to have increased by 158% between 2002 and 2012, from 3.9 Gt y-1 to 9.2 Gt y-1. Our estimated emissions for 2005 are notably consistent with data reported by China in its “Second National Communication” to the UN (NDRC, 2012) and significantly higher than the estimation published recently in Nature. The difference is attributed, among other factors, to the assumption of a constant carbon content of coal in the latter study. The results indicate that CO2 emissions of China in 2005 reported by Second National Communication are more reliable to serve as the baseline for China's future carbon commitments (e.g. those in Paris Agreement of the UNFCCC). Discrepancies between national and provincial statistics on coal production and consumption are investigated and attributed primarily to anomalous reporting on interprovincial trade in four heavily industrialized provinces.

Xinyu Chen, Zhiwei Xu, Chris P Nielsen, and Michael B. McElroy. 2018. “Impacts of fleet types and charging modes for electric vehicles on emissions under different penetrations of wind power.” Nature Energy, 3, Pp. 413-421. Publisher's VersionAbstract
Current Chinese policy promotes the development of both electricity-propelled vehicles and carbon-free sources of power. Concern has been expressed that electric vehicles on average may emit more CO2 and conventional pollutants in China. Here, we explore the environmental implications of investments in different types of electric vehicle (public buses, taxis and private light-duty vehicles) and different modes (fast or slow) for charging under a range of different wind penetration levels. To do this, we take Beijing in 2020 as a case study and employ hourly simulation of vehicle charging behaviour and power system operation. Assuming the slow-charging option, we find that investments in electric private light-duty vehicles can result in an effective reduction in the emission of CO2 at several levels of wind penetration. The fast-charging option, however, is counter-productive. Electrifying buses and taxis offers the most effective option to reduce emissions of NOx, a major precursor for air pollution.
Michael B. McElroy, Xinyu Chen, and Yawen Deng. 2018. “The missing money problem: incorporation of increased resources from wind in a representative US power market.” Renewable Energy, 126, Pp. 126-136. Publisher's VersionAbstract
The paper considers opportunities to reduce emissions of CO2 through increases in commitments to wind in a representative US power market. A model is applied to simulate market operations for different wind levels focusing on implications of the reduction in clearing prices arising due to increasing inputs of zero marginal cost power from wind, a dilemma referred to as the missing money problem. The resulting decrease in income poses problems for existing thermal and nuclear generating systems, at the same time making investments in wind uneconomic in the absence offsetting policy interventions. Two options are considered to subsidize cost: an investment credit (IC) or a subsidy on production (PC). The dilemma could be addressed also with a carbon tax targeted to increase income. It is assumed that the cost associated with the IC and PC options should be borne by the consumer, offsetting benefits from lower wholesale prices. It is assumed further that income from the carbon tax should be rebated to the consumer offsetting related increases in clearing prices. IC and PC options offer opportunities to reduce emissions at low or even negative net costs to the consumer. Higher costs are associated with the option of a carbon tax.
Xinyu Chen, Jiajun Lv, Michael B. McElroy, Xingning Han, Chris Nielsen, and Jinyu Wen. 2018. “Power system capacity expansion under higher penetration of renewables considering flexibility constraints and low carbon policies.” IEEE Transactions on Power Systems, 33, 6, Pp. 6240-6253. Publisher's VersionAbstract
Deploying high penetration of variable renewables represents a critical pathway for deep decarbonizing the power sector. The conflict between their temporal variability and limited system flexibility has been largely ignored currently at planning stage. Here we present a novel capacity expansion model optimizing investment decisions and full-year, hourly power balances simultaneously, with considerations of storage technologies and policy constraints, such as carbon tax and renewable portfolio standards (RPS). Based on a computational efficient modeling formulation, all flexibility constrains (ramping, reserve, minimum output, minimal online/offline time) for the 8760-hour duration are incorporated. The proposed model is applied to the northwestern grid of China to examine the optimal composition and distribution of power investments with a wide range of renewable targets. Results indicate that the cost can increase moderately towards 45% of RPS, when properly designing the generation portfolio: prioritizing wind investments, distributing renewable investments more evenly and deploying more flexible mid-size coal and gas units. Reaching higher penetrations of renewables is expensive and the reductions of storage costs are critically important for an affordable low-carbon future. RPS or carbon taxes to reach a same target of emission reduction in China will result in similar overall costs but different generation mixes.
Meng Gao, Yihui Ding, Shaojie Song, Xiao Lu, Xinyu Chen, and Michael B. McElroy. 2018. “Secular decrease of wind power potential in India associated with warming Indian Ocean.” Science Advances, 4, 12. Publisher's VersionAbstract
The Indian government has set an ambitious target for future renewable power generation, including 60 GW of cumulative wind power capacity by 2022. However, the benefits of these substantial investments are vulnerable to the changing climate. On the basis of hourly wind data from an assimilated meteorology reanalysis dataset covering the 1980–2016 period, we show that wind power potential may have declined secularly over this interval, particularly in western India. Surface temperature data confirm that significant warming occurred in the Indian Ocean over the study period, leading to modulation of high pressure over the ocean. A multivariable linear regression model incorporating the pressure gradient between the Indian Ocean and the Indian subcontinent can account for the interannual variability of wind power. A series of numerical sensitivity experiments confirm that warming in the Indian Ocean contributes to subsidence and dampening of upward motion over the Indian continent, resulting potentially in weakening of the monsoonal circulation and wind speeds over India.
Science Advances paper.pdf
2017
Xinyu Chen, Michael B. McElroy, and Chongqing Kang. 2017. “Integrated energy systems for higher wind penetration in China: Formulation, implementation, and impacts.” IEEE Transactions on Power Systems, 33, 2, Pp. 1309-1319. Publisher's VersionAbstract
With the largest installed capacity in the world, wind power in China is experiencing a ∼20% curtailment. The inflexible combined heat and power (CHP) has been recognized as the major barrier for integrating the wind source. The approach to reconcile the conflict between inflexible CHP units and variable wind power in Chinese energy system is yet un-clear. This paper explores the technical and economic feasibility of deploying the heat storage tanks and electric boilers under typical power grids and practical operational regulations. A mixed integer linear optimization model is proposed to simulate an integrated power and heating energy systems, including a CHP model capable of accounting for the commitment decisions and non-convex energy generation constraints. The model is applied to simulate a regional energy system (Jing-Jin-Tang) covering 100-million population, with hourly resolution over a year, incorporating actual data and operational regulations. The results project an accelerating increase in wind curtailment rate at elevated wind penetration. Investment for wind breaks-even at 14% wind penetration. At such penetration, the electric boiler (with heat storage) is effective in reducing wind curtailment. The investment in electric boilers is justified on a social economic basis, but the revenues for different stakeholders are not distributed evenly.
Michael B. McElroy and Xinyu Chen. 2017. “Wind and solar power in the United States: Status and prospects.” CSEE Journal of Power and Energy Systems, 3, 1. Publisher's VersionAbstract

 

The United States has committed to reduce its greenhouse gas emissions by 26%–28% by 2025 and by 83% by 2050 relative to 2005. Meeting these objectives will require major investments in renewable energy options, particularly wind and solar. These investments are promoted at the federal level by a variety of tax credits, and at the state level by requirements for utilities to include specific fractions of renewable energy in their portfolios (Renewable Portfolio Standards) and by opportunities for rooftop PV systems to transfer excess power to utilities through net metering, allowing meters to operate in reverse. The paper discusses the current status of these incentives.

 

Peter Sherman, Xinyu Chen, and Michael B. McElroy. 2017. “Wind-generated electricity in China: Decreasing potential, inter-annual variability, and association with climate change.” Scientific Reports, 7. Publisher's VersionAbstract
China hosts the world’s largest market for wind-generated electricity. The financial return and carbon reduction benefits from wind power are sensitive to changing wind resources. Wind data derived from an assimilated meteorological database are used here to estimate what the wind generated electricity in China would have been on an hourly basis over the period 1979 to 2015 at a geographical resolution of approximately 50 km × 50 km. The analysis indicates a secular decrease in generating potential over this interval, with the largest declines observed for western Inner Mongolia (15 ± 7%) and the northern part of Gansu (17 ± 8%), two leading wind investment areas. The decrease is associated with long-term warming in the vicinity of the Siberian High (SH), correlated also with the observed secular increase in global average surface temperatures. The long-term trend is modulated by variability relating to the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO). A linear regression model incorporating indices for the PDO and AO, as well as the declining trend, can account for the interannual variability of wind power, suggesting that advances in long-term forecasting could be exploited to markedly improve management of future energy systems.
Science_Reports_Full_Text
2016
Ning Zhang, Xi Lu, Chris P Nielsen, Michael B. McElroy, Xinyu Chen, Yu Deng, and Chongqing Kang. 2016. “Reducing curtailment of wind electricity in China by employing electric boilers for heat and pumped hydro for energy storage.” Applied Energy, 184, Pp. 987-994. Publisher's VersionAbstract

Accommodating variable wind power poses a critical challenge for electric power systems that are heavily dependent on combined heat and power (CHP) plants, as is the case for north China. An improved unit-commitment model is applied to evaluate potential benefits from pumped hydro storage (PHS) and electric boilers (EBs) in West Inner Mongolia (WIM), where CHP capacity is projected to increase to 33.8 GW by 2020. A business-as-usual (BAU) reference case assumes deployment of 20 GW of wind capacity. Compared to BAU, expanding wind capacity to 40 GW would allow for a reduction in CO2 emissions of 33.9 million tons, but at a relatively high cost of US$25.3/ton, reflecting primarily high associated curtailment of wind electricity (20.4%). A number of scenarios adding PHS and/or EBs combined with higher levels of wind capacity are evaluated. The best case indicates that a combination of PHS (3.6 GW) and EBs (6.2 GW) together with 40 GW of wind capacity would reduce CO2 emissions by 43.5 million tons compared to BAU, and at a lower cost of US$16.0/ton. Achieving this outcome will require a price-incentive policy designed to ensure the profitability of both PHS and EB facilities.

2014
Xi Lu, Michael B. McElroy, Xinyu Chen, and Chongqing Kang. 2014. “Opportunity for offshore wind to reduce future demand for coal-fired power plants in China with consequent savings in emissions of CO2.” Environmental Science & Technology, 48, 24, Pp. 14764–14771. Publisher's VersionAbstract

Although capacity credits for wind power have been embodied in power systems in the U.S. and Europe, the current planning framework for electricity in China continues to treat wind power as a non-dispatchable source with zero contribution to firm capacity. This study adopts a rigorous reliability model for the electric power system evaluating capacity credits that should be recognized for offshore wind resources supplying power demands for Jiangsu, China. Jiangsu is an economic hub located in the Yangtze River delta accounting for 10% of the total electricity consumed in China. Demand for electricity in Jiangsu is projected to increase from 331 TWh in 2009 to 800 TWh by 2030. Given a wind penetration level of 60% for the future additional Jiangsu power supply, wind resources distributed along the offshore region of five coastal provinces in China (Shandong, Jiangsu, Shanghai, Zhejiang and Fujian) should merit a capacity credit of 12.9%, the fraction of installed wind capacity that should be recognized to displace coal-fired systems without violating the reliability standard. In the high-coal-price scenario, with 60% wind penetration, reductions in CO2 emissions relative to a business as usual reference could be as large as 200.2 million tons of CO2 or 51.8% of the potential addition, with a cost for emissions avoided of $29.0 per ton.

 

Final Manuscript in DASH

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