Abstract: An approach for adjusting the inclination of a solar panel and the pitch of one or more micro-turbines to maximize power output. The approach predicts wind velocity at a small opening of an inclined solar panel wherein a plurality of micro-turbines is located. The approach predicts solar irradiance striking the inclined solar panel. The approach calculates an optimal solar panel inclination angle and micro-turbine pitch based on maximizing power output. The approach adjusts the solar panel inclination angle and micro-turbine pitch based on the calculation.

Abstract: An approach for adjusting the inclination of a solar panel and the pitch of one or more micro-turbines to maximize power output. The approach predicts wind velocity at a small opening of an inclined solar panel wherein a plurality of micro-turbines is located. The approach predicts solar irradiance striking the inclined solar panel. The approach calculates an optimal solar panel inclination angle and micro-turbine pitch based on maximizing power output. The approach adjusts the solar panel inclination angle and micro-turbine pitch based on the calculation.

Abstract: A method, computer system, and a computer program product for improving environmental impact estimations is provided. The present invention may include obtaining data pertaining to an agricultural area. The present invention may include deriving one or more features from the data pertaining to the agricultural area. The present invention may include identifying one or more stubble burning areas within the agricultural areas based on the one or more derived features. The present invention may include determining an environmental impact for each of the one or more stubble burning areas.

Abstract: A method for photosynthesis optimization including determining ambient levels of at least one gas, water, and sunlight at a location. A catalyst is selected to perform an artificial photosynthesis reaction at the location. At least one limiting factor is determined for the artificial photosynthesis reaction based on the catalyst and the ambient levels, and the at least one limiting factor is compensated for.

Abstract: Methods, systems, and computer program products for generating GHG emissions estimations associated with logistics contexts using machine learning techniques are provided herein.

Abstract: Provided are a computer program product, system, and method for generating constraints based on reported crop arrivals to marketplaces and remote sensed data to estimate farm yields of farm fields. A total arrival quantity constraint for a marketplace is generated comprising a function of a reported arrival of crops at a marketplace and an estimated arrival to the marketplace comprising a sum of farm yields for the farm fields, wherein the farm yields comprise variables to optimize. Sensed data of the farm fields is used to determine relationships of the farm yields for the farm fields. Comparative farm yield constraints are generated comprising relationships of the farm yields for different pairs of farms. A constraint optimization problem is solved based on the total arrival quantity constraint and comparative farm yield constraints to calculate the farm yields of the farm fields.

Abstract: Methods, systems, and computer program products for generating context-aware process-based model determinations for greenhouse gas emissions from agricultural fields are provided herein.

Abstract: Methods, systems, and computer program products for enhancing spatial and temporal resolution of greenhouse gas emission estimates for agricultural fields using cohort analysis techniques are provided herein.

Abstract: One embodiment provides a method, including: training a plurality of machine-learning models, wherein each of the machine-learning models is trained for a specific farm field region utilizing training data for the plurality of machine-learning models; wherein the utilizing training data includes identifying one of the farm field regions having a similarity to another of the farm field regions and transferring training data; identifying a plurality of types of data needed for updating at least one of the plurality of machine-learning models to address at least one uncertainty; recommending collection of and collecting at least one of the plurality of types of data; and re-training the subset of the plurality of machine-learning models utilizing the at least one of the plurality of types of data, thereby decreasing the cost the of data collection, for example, crowdsourced data, by utilizing data collected from one farm field region in other farm field regions.

Abstract: Methods, systems, and computer program products for dynamic determination of irrigation-related data using machine learning techniques are provided herein.

Abstract: Provided are a computer program product, system, and method for generating constraints based on reported crop arrivals to marketplaces and remote sensed data to estimate farm yields of farm fields. A total arrival quantity constraint for a marketplace is generated comprising a function of a reported arrival of crops at a marketplace and an estimated arrival to the marketplace comprising a sum of farm yields for the farm fields, wherein the farm yields comprise variables to optimize. Sensed data of the farm fields is used to determine relationships of the farm yields for the farm fields. Comparative farm yield constraints are generated comprising relationships of the farm yields for different pairs of farms. A constraint optimization problem is solved based on the total arrival quantity constraint and comparative farm yield constraints to calculate the farm yields of the farm fields.

Abstract: Methods, systems, and computer program products for dynamic determination of irrigation-related data using machine learning techniques are provided herein.

Abstract: Methods, systems, and computer program products are provided herein in connection with IoT-enabled solar PV health monitoring and advising related thereto.

Abstract: An agricultural plot evaluation method, computer program product and system are provided. A processor receives a plot for evaluation. A processor determines one or more characteristics associated with the plot for evaluation. A processor identifies a plurality of similar plots based on at least one of the one or more characteristics associated with the plot for evaluation. A processor generates a prediction model for one or more features of the plurality of similar plots. A processor determines a score for the plot for evaluation based, at least in part, on the prediction model for one or more features of the plurality of similar plots.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predictive maintenance of refrigeration cases. A computer collects a temperature time series for a refrigeration case and, based on the temperature time series, learns a refrigeration case signature for both non-frost and defrost cycles. The computer generates features based on the refrigeration case signature and compares the refrigeration case signature to real time, or observed, temperatures and features using a rule-based and/or machine learning framework. Based on determining that the real time data varies beyond a threshold from the refrigeration case signature, the computer identifies a failure symptom of the refrigeration case and diagnoses a root cause of the symptom or failure. In addition, the computer may activate an alarm and open a work order corresponding to the root cause of the symptom or failure.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predictive maintenance of refrigeration cases. A computer collects a temperature time series for a refrigeration case and, based on the temperature time series, learns a refrigeration case signature for both non-frost and defrost cycles. The computer generates features based on the refrigeration case signature and compares the refrigeration case signature to real time, or observed, temperatures and features using a rule-based and/or machine learning framework. Based on determining that the real time data varies beyond a threshold from the refrigeration case signature, the computer identifies a failure symptom of the refrigeration case and diagnoses a root cause of the symptom or failure. In addition, the computer may activate an alarm and open a work order corresponding to the root cause of the symptom or failure.

Abstract: One embodiment provides a method, including: receiving configuration input for a solar structure; the configuration input comprising (i) a geographical location, (ii) module configuration input, and (iii) reflector configuration input; identifying the position of the sun; determining an angle between the solar reflector and the solar module corresponding to a predetermined power gain for the solar module, wherein the determining comprises (i) identifying the corresponding area of the solar module that is illuminated by the solar reflector and (ii) totaling the contributions from each of the solar reflectors to calculate an irradiance for each solar cell; adjusting the angles of at least some of the solar reflectors with respect to the solar module to angles determined to correspond to the predetermined power gain using at least one actuator; and dynamically changing how the solar cells are electrically connected together to form a plurality of strings.

Abstract: One embodiment provides a method, including: receiving information, from at least one energy subsystem, indicating a desired amount of photovoltaic output to be produced by at least one photovoltaic panel, wherein the at least one photovoltaic panel comprises at least one photovoltaic harvester; ascertaining the amount of photovoltaic output being produced by the at least one photovoltaic panel; determining the difference between the desired amount of photovoltaic output and the amount of photovoltaic output being produced; identifying the maximum possible amount of photovoltaic output that could be produced by the at least one photovoltaic panel; and optimizing, using an optimization technique, the amount of photovoltaic output produced by the at least one photovoltaic harvester by adjusting at least one characteristic of the at least one photovoltaic harvester, wherein the adjusting comprises: if the difference is less than the maximum possible amount, adjusting at least one characteristic of the at least o

Abstract: Methods, systems, and computer program products for determining intermittent renewable energy penetration limits in a grid are provided herein.

Abstract: A method of operating a battery pack includes identifying a plurality of batteries in the battery pack, estimating a state of charge of each of the plurality of the batteries, obtaining a plurality of parameters of each of the plurality of the batteries, and determining, selectively, a charge current or a discharge current for each of the plurality of batteries using the state of charge and the plurality of parameters of each of the plurality of the batteries.