Opportunity for offshore wind to reduce future demand for coal-fired power plants in China with consequent savings in emissions of CO2.

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 nondispatchable 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.

Synergies of wind power and electrified space heating: case study for Beijing.

Demands for electricity and energy to supply heat are expected to expand by 71% and 47%, respectively, for Beijing in 2020 relative to 2009. If the additional electricity and heat are supplied solely by coal as is the current situation, annual emissions of CO2 may be expected to increase by 59.6% or 99 million tons over this interval. Assessed against this business as usual (BAU) background, the present study indicates that significant reductions in emissions could be realized using wind-generated electricity to provide a source of heat, employed either with heat pumps or with electric thermal storage (ETS) devices. Relative to BAU, reductions in CO2 with heat pumps assuming 20% wind penetration could be as large as 48.5% and could be obtained at a cost for abatement of as little as $15.6 per ton of avoided CO2. Even greater reductions, 64.5%, could be realized at a wind penetration level of 40% but at a higher cost, $29.4 per ton. Costs for reduction of CO2 using ETS systems are significantly higher, reflecting the relatively low efficiency for conversion of coal to power to heat.

Improving distributed PV integration with dynamic thermal rating of power distribution equipment.

The rapid development of distributed photovoltaic (PV) systems poses great challenges to the integration capability of distribution networks. Traditionally, the transfer capacity of power distribution equipment is calculated as the maximum loading that prevents overheating under the assumption of extreme weather conditions. Dynamic thermal rating (DTR), which evaluates equipment capacity based on real-time weather conditions, could enhance the transfer capacity to improve distributed PV integration. Through case studies in Texas, Switzerland, and China, we show that the application of DTR on power distribution equipment could increase installed PV capacities by 15%-27% and improve net revenues by 4%-27%. We also find that the application of DTR would be positively affected by climate change and is more profitable under the PV policies with higher tariffs for the surplus generation fed into the grid. Compared to energy storage systems, DTR provides a more cost-competitive option to enhance the integration capability of distribution networks.

Cost increase in the electricity supply to achieve carbon neutrality in China.

The Chinese government has set long-term carbon neutrality and renewable energy (RE) development goals for the power sector. Despite a precipitous decline in the costs of RE technologies, the external costs of renewable intermittency and the massive investments in new RE capacities would increase electricity costs. Here, we develop a power system expansion model to comprehensively evaluate changes in the electricity supply costs over a 30-year transition to carbon neutrality. RE supply curves, operating security constraints, and the characteristics of various generation units are modelled in detail to assess the cost variations accurately. According to our results, approximately 5.8 TW of wind and solar photovoltaic capacity would be required to achieve carbon neutrality in the power system by 2050. The electricity supply costs would increase by 9.6 CNY¢/kWh. The major cost shift would result from the substantial investments in RE capacities, flexible generation resources, and network expansion.

Exploring the trade-offs between electric heating policy and carbon mitigation in China.

China has enacted a series of policies since 2015 to substitute electricity for in-home combustion for rural residential heating. The Electric Heating Policy (EHP) has contributed to significant improvements in air quality, benefiting hundreds of millions of people. This shift, however, has resulted in a sharp increase in electric loads and associated carbon emissions. Here, we show that China's EHP will greatly increase carbon emissions. We develop a theoretical model to quantify the carbon emissions from power generation and rural residential heating sectors. We found that in 2015, an additional 101.69-162.89 megatons of CO2 could potentially be emitted if EHP was implemented in 45-55% of rural residents in Northern China. In 2020, the incremental carbon emission is expected to reach 130.03-197.87 megatons. Fortunately, the growth of carbon emission will slow down due to China's urbanization progress. In 2030, the carbon emission increase induced by EHP will drop to 119.19-177.47 megatons. Finally, we conclude two kinds of practical pathways toward low-carbon electric heating, and provide techno-economic analyses.

A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the US Electricity Sector.

The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the US becoming the epicenter of COVID-19 cases since late March. As the US begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector. Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing US wholesale electricity markets with COVID-19 case, weather, mobile device location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we rigorously uncover a significant reduction in electricity consumption that is strongly correlated with the number of COVID-19 cases, degree of social distancing, and level of commercial activity.

Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5.

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (-1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic's effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

Carbon emission flow in networks.

As the human population increases and production expands, energy demand and anthropogenic carbon emission rates have been growing rapidly, and the need to decrease carbon emission levels has drawn increasing attention. The link between energy production and consumption has required the large-scale transport of energy within energy transmission networks. Within this energy flow, there is a virtual circulation of carbon emissions. To understand this circulation and account for the relationship between energy consumption and carbon emissions, this paper introduces the concept of "carbon emission flow in networks" and establishes a method to calculate carbon emission flow in networks. Using an actual analysis of China's energy pattern, the authors discuss the significance of this new concept, not only as a feasible approach but also as an innovative theoretical perspective.