设施农业是农业现代化发展的标志,也是农产品提质增效的重要途径。规模农户作为中国现代农业的引领者与创新者,能够极大推动设施农业发展。本文利用第二期“全国新型农业经营主体发展指数调查”数据对专业大户和家庭农场设施农业经营现状进行分析,并采用Probit和Tobit模型对影响其发展的因素予以实证分析。研究发现：这两类农户经营设施农业的比例较低、规模较小,设施农业经营品类丰富、以蔬菜类为主,经营过程面临资金、技术等方面制约,整体效益不高。另外,设施农业发展受户主特征、家庭特征及外部环境等因素的显著影响。总体上,户主人力资本越富裕越有利于设施农业发展,家庭特征对不同类型农户的影响不一致,外部产业环境对设施农业发展有相当显著的促进作用,产业集聚是设施农业做大做强乃至农业现代化的重要方向。因此,为进一步推动家庭农场和专业大户设施农业发展,政府还需从政策、资金、技术及市场建设等方面对其予以支持。

Facility agriculture is a symbol of agricultural modernization and an important way to improve the quality and efficiency of agricultural products and production. As the leader and innovator of modern agriculture, large-scale farmers can greatly promote the development of facility agriculture. Using Probit and Tobit models, this study analyzed the development status of facility agriculture of specialized households and family farms based on the data of the second phase of the “national new agricultural management entities development index survey.” The results show that: The proportion of these two types of farmers operating facility agriculture is low, their planting scale is small, the types of products are diversified, and the main products are vegetables. The operation of facility agriculture is restricted by capital and technology, and the overall benefit is not high. In addition, the development of facility agriculture is significantly affected by the characteristics of household heads, family characteristics, external environment, among other factors. On the whole, the richer the household head’s human capital is, the more beneficial it is to the development of facility agriculture. The influence of family characteristics on different types of farmers is inconsistent. External environment plays a significant role in promoting the development of facility agriculture. Industrial agglomeration is an important direction for facility agriculture to grow and become stronger and for realizing agricultural modernization. Therefore, in order to further promote the development of facility agriculture of family farms and specialized households, the government also needs to support them in terms of policy, capital, technical support, and market development.

针对设施农业产业园区在生产过程中能源得不到高效利用且能耗费用较高的问题,文章提出了一种计及风光就地消纳的设施农业产业园区综合能源系统(integrated energy system, IES)多目标优化调度方法。首先,建立了包含风-光-沼可再生能源的设施农业产业园区综合能源系统出力模型。然后,考虑多种约束条件,并以能耗费用最低与风光消纳率最大作为目标,利用基于反向学习的改进型多目标正余弦优化算法进行求解。最后,以某设施农业产业园区综合能源系统作为实际算例对所提方法进行了验证。结果表明,所提优化调度方法可有效降低园区日运行费用、提高风光就地消纳率。

以新能源为主的新型电力系统的功率平衡面临着重要的技术挑战，以灵活负荷参与电力系统调节是提升新型电力系统有功平衡能力的重要途径。针对电热负荷季节性、时段性特征明显，新能源“极寒极热无风”“晚峰无光”，热电负荷在新型电力系统中呈现反调峰的趋势。针对这一问题，全面分析了电热负荷时空特性和用能特性，深入挖掘其调节潜力，着重分析了电热可控负荷的控制场景，并系统地给出了电热负荷的柔性调度策略，完成电热负荷的柔性控制调节，实现全时间尺度的网荷协同优化和灵活调度，从而验证了该电网电热负荷实时参与调度的可行性。

The objective of this study was to identify the major electricity and water-consuming components of a pasture-based automatic milking (AM) system and to establish the daily and seasonal consumption trends. Electricity and water meters were installed on 7 seasonal calving pasture-based AM farms across Ireland. Electricity-consuming processes and equipment that were metered for consumption included milk cooling components, air compressors, AM unit(s), auxiliary water heaters, water pumps, lights, sockets, automatic manure scrapers, and so on. On-farm direct water-consuming processes and equipment were metered and included AM unit(s), auxiliary water heaters, tubular coolers, wash-down water pumps, livestock drinking water supply, and miscellaneous water taps. Data were collected and analyzed for the 12-mo period of 2015. The average AM farm examined had 114 cows, milking with 1.85 robots, performing a total of 105 milkings/AM unit per day. Total electricity consumption and costs were 62.6 Wh/L of milk produced and 0.91 cents/L, respectively. Milking (vacuum and milk pumping, within-AM unit water heating) had the largest electrical consumption at 33%, followed by air compressing (26%), milk cooling (18%), auxiliary water heating (8%), water pumping (4%), and other electricity-consuming processes (11%). Electricity costs followed a similar trend to that of consumption, with the milking process and water pumping accounting for the highest and lowest cost, respectively. The pattern of daily electricity consumption was similar across the lactation periods, with peak consumption occurring at 0100, 0800, and between 1300 and 1600 h. The trends in seasonal electricity consumption followed the seasonal milk production curve. Total water consumption was 3.7 L of water/L of milk produced. Water consumption associated with the dairy herd at the milking shed represented 42% of total water consumed on the farm. Daily water consumption trends indicated consumption to be lowest in the early morning period (0300-0600 h), followed by spikes in consumption between 1100 and 1400 h. Seasonal water trends followed the seasonal milk production curve, except for the month of May, when water consumption was reduced due to above-average rainfall. This study provides a useful insight into the consumption of electricity and water on a pasture-based AM farms, while also facilitating the development of future strategies and technologies likely to increase the sustainability of AM systems.The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).