Water is essential for bioenergy production. Characterized as low carbon technology, crop-based bioenergy technology witnesses rapid development, inevitably putting pressure on global water resources. Therefore, it is crucial to carefully assess bioenergy technology’s overall impact on scarce water source for a sustainable bioenergy future. In this regard, this study aims to evaluate the life cycle water use of bioenergy from agricultural residues via the first pilot moving-bed pyrolysis polygeneration system in China. By using a tiered hybrid life cycle assessment, both direct and indirect water use are calculated. Results show life cycle water use is 3.89 L H2O/MJ and agricultural process dominates the total water use. Scenarios analysis shows different feedstock allocation ratios during agricultural production have striking influence on water use intensity. In addition, the choice of feedstock is another important influential factor. Under the 2020 Scenario in China’s 13th Five Year Plan, if all the bioenergy target could be met by polygeneration the estimated annual water use will be 6.6 billion m3, in magnitude up to around ten times the total water consumption in Denmark in 2013. In global scenario of potential feedstock available in 2060, the estimated water use for bioenergy produced by polygeneration will be 179-369 billion m3. Although the water use intensity of bioenergy production from agricultural residues by polygeneration is lower than that for other biomass conversion pathways, it is still higher than water intensity of conventional fossil energy products. Large-scale bioenergy production will have macroscopic effects on water demand. Finally, suggestions such as selecting high water-efficient biomass feedstock and reinforcing water-saving irrigation management to minimize water use in agriculture stage are proposed.
This paper focuses on economic dispatch (ED) in power systems with intermittent wind power, which is a very critical issue in future power systems. A stochastic ED problem is formed based on the recently proposed versatile probability dis-tribution (VPD) of wind power. The problem is then analyzed and proved to be strictly convex. Although such convex optimiza-tion is tractable in many cases, it may take a long time to solve due to its large scale. This paper proposes a dual decomposition method to decompose the large problem. Then two methods are employed to solve the decomposed problem, namely, the subgra-dient method and a faster method, limited-memory BFGS with box constraints (L-BFGS-B, a quasi-Newton method). Case stud-ies were conducted to verify the efficiency of the dual decomposi-tion and L-BFGS-B method for solving the stochastic ED problem.
This paper makes an in-depth analysis on demand-driven natural resource requirements in China via the methods of thermodynamic input-output analysis and structural path analysis, in order to reveal the connections between the country's rapid economic development and its intensive use of natural resources. The main natural resources investigated include crops, forestry, rangeland, aquatic products, coal, crude oil & natural gas, ferrous metal ores, nonferrous metal ores, nonmetallic minerals and other primary energy, and exergy is adopted as a common metric for the resource accounting. In 2012, the total domestic resource exergy input into Chinese economic system amounted to 130.1 EJ, of which 44.6% was induced by investment demands. The embodied resource use (ERU) in China's exports was equivalent to over one fifth of its domestic resource supply. The two integrative sectors of Manufacturing and Construction accounted for 44.1% and 28.7% of the national total ERU, respectively. We identified critical supply chain paths starting from resource extraction to final demand, as well as key industrial sectors in driving the extraction, transmission and final use of embodied resources. The top 50 paths were responsible for 30.4 EJ of the ERU. The identification of resource supply chains from a systemic perspective is of great importance when resource and environmental policies are to be applied to concrete industrial sectors and other economic agents. Integrated approaches that take account of consumption-based resource indicators should be developed for resource conservation and cleaner production, particularly for the economic system with a complex supply network.
In this paper, a two-stage optimal charging scheme based on transactive control is proposed for the aggregator to manage day-ahead electricity procurement and real-time EV charging management in order to minimize its total operating cost. The day-ahead electricity procurement considers both the day-ahead energy cost and expected real-time operation cost. In the real-time charging management, the cost of employing the charging flexibility from the EV owners is explicitly modelled. The aggregator uses a transactive market to manage the real-time charging demand to provide the regulating power. A model predictive control (MPC) based method is proposed for the aggregator to clear the transactive market. The real-time charging decisions of the EVs are determined by the clearing of the proposed transactive market according to the real-time requests and preferences of the EV owners. As such, the aggregatorb's decisions in the real-time EV charging management and regulating power markets can be optimized. At the same time, the charging requirements and response preferences of the EV owners are respected. Case studies using real world driving data from the Danish National Travel Surveys were conducted to verify the proposed framework.
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.
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.
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.
The assessment of the economic potential of wind electricity is of critical importance for wind power development in China. Based on the wind resource data between 1995 and 2014 and geological assumptions, this paper calculates economic potential of China’s onshore wind electricity. Furthermore, it builds an econometric model to update the net-present-value model, based on a survey sample of various wind farms. Results show that the economic potential of China’s onshore wind electricity is 8.13 PWh per year with a feed-in-tariff price at 0.60 yuan (about 9.6 U.S. cents) per kilowatt-hour.
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.
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.
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.
In the 21st Conference of the Parties to the UNFCCC held in Paris in December 2015, China pledged to peak its carbon emissions and increase non-fossil energy to 20% by 2030 or earlier. Expanding renewable capacity, especially wind power, is a central strategy to achieve these climate goals. Despite greater capacity for wind installation in China compared to the US (145.1 versus 75.0 GW), less wind electricity is generated in China (186.3 versus 190.9 TWh). Here, we quantify the relative importance of the key factors accounting for the unsatisfactory performance of Chinese wind farms. Different from the results in earlier qualitative studies, we find that the difference in wind resources explains only a small fraction of the present China-US difference in wind power output (17.9% in 2012); the curtailment of wind power, differences in turbine quality, and delayed connection to the grid are identified as the three primary factors (respectively 49.3%, 50.2%, and 50.3% in 2012). Improvements in both technology choices and the policy environment are critical in addressing these challenges.
The climate of our planet is changing at a rate unprecedented in recent human history. The energy absorbed from the sun exceeds what is returned to space. The planet as a whole is gaining energy. The heat content of the ocean is increasing; the surface and atmosphere are warming; mid-latitude glaciers are melting; sea level is rising. The Arctic Ocean is losing its ice cover. None of these assertions are based on theory but on hard scientific fact. Given the science-heavy nature of climate change, debates and discussions have not played as big a role in the public sphere as they should, and instead are relegated to often misinformed political discussions and inaccessible scientific conferences. Michael B. McElroy, an eminent Harvard scholar of environmental studies, combines both his research chops and pedagogical expertise to present a book that will appeal to the lay reader but still be grounded in scientific fact.
In Energy and Climate: Vision for the Future, McElroy provides a broad and comprehensive introduction to the issue of energy and climate change intended to be accessible for the general reader. The book includes chapters on energy basics, a discussion of the contemporary energy systems of the US and China, and two chapters that engage the debate regarding climate change. The perspective is global but with a specific focus on the US and China recognizing the critical role these countries must play in addressing the challenge of global climate change. The book concludes with a discussion of initiatives now underway to at least reduce the rate of increase of greenhouse gas emissions, together with a vision for a low carbon energy future that could in principle minimize the long-term impact of energy systems on global climate.