IoT-Enabled Real-Time Management of Smart Grids with Demand Response Aggregators

Integration of widely distributed small-scale Renewable Energy Sources like rooftop Photovoltaic panels and emerging loads like plug-in Electric Vehicles would cause more volatility in total net demand of distribution networks. Utility-owned storage units and control devices like tap changers and capacitors may not be sufficient to manage the system in real-time. Exploitation of available flexibility in demand side through aggregators is a new measure that distribution system operators are interested in. In this paper, we present a developed real-time management schema based on Internet of Things solutions which facilitate interactions between system operators and aggregators for ancillary services like power balance at primary substation or voltage regulation at secondary substations. Two algorithms for power balance and voltage regulation are developed based on modified Optimal Power Flow and voltage sensitivity matrix, respectively. To demonstrate the applicability of the schema, we set-up a real-time simulation- based test bed and realised the performance of this approach in a real-like environment using real data of a network with residential buildings

Water deficit and nitrogen nutrition of crops. A review

Among the environmental factors that can be modified by farmers, water and nitrogen are the main ones controlling plant growth. Irrigation and fertilizer application overcome this effect, if adequately used. Agriculture thus consumes about 85% of the total fresh water used worldwide. While only 18% of the world’s cultivated areas are devoted to irrigated agriculture, this total surface represents more than 45% of total agricultural production. These data highlight the importance of irrigated agriculture in a framework where the growing population demands greater food production. In addition, tighter water restrictions and competition with other sectors of society is increasing pressure to diminish the share of fresh water for irrigation, thus resulting in the decrease in water diverted for agriculture.The effect of water and nutrient application on yield has led to the overuse of these practices in the last decades. This misuse of irrigation and fertilizers is no longer sustainable, given the economic and environmental costs. Sustainable agriculture requires a correct balance between the agronomic, economic and environmental aspects of nutrient management. The major advances shown in this review are the following: (1) the measurement of the intensity of drought and N deficiency is a prerequisite for quantitative assessment of crop needs and management of both irrigation and fertilizer application. The N concentration of leaves exposed to direct irradiance allows both a reliable and high-resolution measurement of the status and the assessment of N nutrition at the plant level. (2) Two experiments on sunflower and on tall fescue are used to relate the changes in time and irrigation intensity to the crop N status, and to introduce the complex relationships between N demand and supply in crops. (3) Effects of water deficits on N demand are reviewed, pointing out the high sensitivity of N-rich organs versus the relative lesser sensitivity of organs that are poorer in N compounds. (4) The generally equal sensitivities of nitrifying and denitrifying microbes are likely to explain many conflicting results on the impact of water deficits on soil mineral N availability for crops. (5) The transpiration stream largely determines the availability of mineral N in the rhizosphere. This makes our poor estimate of root densities a major obstacle to any precise assessment of N availability in fertilized crops. (6) The mineral N fluxes in the xylem are generally reduced under water deficit and assimilation is generally known to be more sensitive to water scarcity. (7) High osmotic pressures are maintained during grain filling, which enables the plant to recycle large amounts of previously assimilated N. Its part in the total grain N yield is therefore generally higher under water deficits. (8) Most crop models currently used in agronomy use N and water efficiently but exhibit different views on their interaction