Abstract: A computer system that includes a plurality of compute clusters that are located at different geographical locations. Each compute cluster is powered by a local energy source at a geographical location of that compute cluster. Each local energy source has a pattern of energy supply that is variable over time based on an environmental factor. The computer system further includes a server system that executes a global scheduler that distributes virtual machines that perform compute tasks for server-executed software programs to the plurality of compute clusters of the distributed compute platform. To distribute virtual machines for a target server-executed software program, the global scheduler is configured to select a subset of compute clusters that have different complementary patterns of energy supply such that the subset of compute clusters aggregately provide a target compute resource availability for virtual machines for the target server-executed software program.

Abstract: The techniques disclosed herein enable systems to optimize generation and dispatch of renewable energies using data-driven models. In many contexts, a renewable energy system is collocated with a local consumer such as a datacenter, a smart building, and so forth. The objective of the renewable energy system is to meet local power needs while participating in various energy markets of differing trading frequencies. To optimally manage the renewable energy system, a data-driven model is configured to analyze current conditions and generate policies to control renewable energy system operations. For instance, the model can retrieve current market prices, generation capacity, costs associated with generating energy, and so forth. Based on the collected information, the model can generate a policy that maximizes revenue obtained by the renewable energy system while meeting local demand. Through many iterations, the model can determine a realistically optimal policy for managing the renewable energy system.

Abstract: A computer system is provided, including a processor and associated memory storing instructions that when executed cause the processor to implement a plurality of artificial intelligence (AI) models. Each AI model is configured to receive, as input, time series data and to output a model-specific time series forecast including a respective predicted value for each of a plurality of future time steps. The processor is further configured to implement a model selection neural network configured to select a predicted most accurate AI model from among the plurality of AI models for each of the plurality of future time steps. The processor is further configured to implement a blended output generator configured to output a model-blended time series forecast including the respective predicted value computed by the predicted most accurate AI model selected for each of the plurality of future time steps.

Abstract: A computing system is provided comprising a processor and a memory storing instructions executable by the processor. The instructions are executable to, during a run-time phase, receive run-time input data that includes time series data indicating a state of a graph network at each of a series of time steps. The graph network includes a plurality of nodes, and at least one edge connecting pairs of the nodes. The run-time input data is input into a trained graph neural network to thereby cause the graph neural network to output a predicted state of the graph network at one or more future time steps.

Abstract: The techniques disclosed herein enable systems to enable multi-market optimization of renewable energies using data-driven models. To achieve this, a model retrieves a current state from a resource generation system and associated resource markets. The model can then compute a policy based on the state as well physical and technical constraints. The policy defines various actions that direct operation of the resource generation system such as resource production and dispatch to markets. Applying the policy to the resource generation results in a modified state which the model extracts along with a measure of optimality which quantifies the success of the policy. Based on these metrics, the model can generate an updated iteration of the policy defining a different set of actions. In this way, the model can gradually develop an optimal policy for controlling the resource generation system.

Abstract: A computer system that includes a plurality of compute clusters that are located at different geographical locations. Each compute cluster is powered by a local energy source at a geographical location of that compute cluster. Each local energy source has a pattern of energy supply that is variable over time based on an environmental factor. The computer system further includes a server system that executes a global scheduler that distributes virtual machines that perform compute tasks for server-executed software programs to the plurality of compute clusters of the distributed compute platform. To distribute virtual machines for a target server-executed software program, the global scheduler is configured to select a subset of compute clusters that have different complementary patterns of energy supply such that the subset of compute clusters aggregately provide a target compute resource availability for virtual machines for the target server-executed software program.

Abstract: Methods, systems, and computer program products for user-preference driven control of electrical and thermal output from a photonic energy device are provided herein. A system includes a solar photovoltaic module, and a fluid positioned on the solar photovoltaic module. The system also includes configurable reflective surfaces that collect and distribute direct solar and diffuse solar radiation across multiple portions of the fluid and/or portions of the solar photovoltaic module. Additionally, the reflective surfaces is physically connected to the solar photovoltaic module at an angle that is variable in relation to the surface of the solar photovoltaic module. Further, the system includes a controller that modulates an amount of thermal output and/or electrical power output generated by the solar photovoltaic module by transmitting a signal to adjust at least one variable pertaining to the fluid, and transmitting a signal to adjust at least one variable pertaining to the reflective surfaces.

Abstract: Methods, apparatus and systems for tunable photonic harvesting for solar energy conversion and dynamic shading tolerance are provided herein. An apparatus includes a solar photovoltaic module; a sensor device operative to determine portions of the solar photovoltaic module that are underperforming in relation to separate portions; reflective surfaces of a first type, each physically connected to the solar photovoltaic module at a given angle in relation to the surface of the solar photovoltaic module; and reflective surfaces of a second type, each physically connected to a respective one of the reflective surfaces of the first type; wherein the reflective surfaces of the first type and second type are configurable based on a determination of the underperforming portions of the solar photovoltaic module to collect and distributed direct solar radiation and diffuse solar radiation across the solar photovoltaic module to offset the underperforming portions by a given amount.

Abstract: Methods, apparatus and systems for tunable photonic harvesting for solar energy conversion and dynamic shading tolerance are provided herein.

Abstract: A computer-implemented method includes: receiving, using a processor, multiple data session records (DSRs); storing the multiple DSRs in a memory communicatively coupled to the processor; analyzing, using the processor, the stored multiple DSRs for temporal and spatial data; and determining, using the processor, quality degradation by using the temporal and spatial data for the stored multiple DSRs.

Abstract: Methods, systems, and computer program products for operating re-configurable solar energy generators for increasing yield during non-ideal weather conditions are provided herein. A computer-implemented method includes determining, for each of multiple portions of the sky, by using one or more machine learning algorithms, a respective level of diffuse irradiance corresponding to image data from that portion; identifying one or more portions of the image data corresponding to the multiple portions of sky image data that include a higher level of diffuse irradiance, as compared to other portions of the image data; and configuring one or more solar photovoltaic modules based at least in part on the one or more identified portions of image data that include a higher level of diffuse irradiance.

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

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 providing energy elasticity services via distributed virtual batteries are provided herein.

Abstract: Methods and arrangements for processing face-to-face mobile phone transactions. An agreed-upon price for a product is accepted from a buyer mobile phone and a seller mobile phone. Distinct random numbers are assigned to each of the buyer and seller mobile phones. The random number assigned to the seller mobile phone is received from the buyer mobile phone, and the random number assigned to the buyer mobile phone is received from the seller mobile phone. A match is ascertained between the buyer and seller mobile phones based on receipt from the buyer mobile phone the random number assigned to the seller mobile phone and receipt from the seller mobile phone the random number assigned to the buyer mobile phone.

Abstract: A computer-implemented method includes: receiving, using a processor, multiple data session records (DSRs); storing the multiple DSRs in a memory communicatively coupled to the processor; analyzing, using the processor, the stored multiple DSRs for temporal and spatial data; and determining, using the processor, quality degradation by using the temporal and spatial data for the stored multiple DSRs.

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.

Abstract: One embodiment provides a method, including: determining a light profile of light falling onto a solar module, wherein the light profile identifies (i) a position of the light with respect to the solar module and (ii) the intensity of the light with respect to solar panels within the solar module; identifying at least one solar panel within the solar module having partial light coverage; and changing the light profile by shaping the reflection of the light onto the solar module created by a flexible curved reflector in proximity to the solar module, thereby increasing the amount of light falling onto said at least one solar panel within the solar module; the changing the light profile comprising modifying the geometry of the flexible curved reflector by activating at least one actuator to move at least a portion of the flexible curved reflector.

Abstract: One embodiment provides a method, including: capturing at least one image of an object that is of interest to a user; identifying and capturing an environmental context of the object, wherein the environmental context (i) identifies a plurality of features of the environment surrounding the object, and (ii) comprises context captured from different modalities; storing the at least one image and the environmental context of the object, wherein the storing comprises indexing the object within the remote storage location using the identified features of the environment; receiving a request for the at least one image of the object; accessing the remote storage location and retrieving the at least one image of the object, wherein the retrieving comprises (i) searching for the at least one of the plurality of features and (ii) retrieving the at least one image of an object; and displaying the at least one image.