A system controlling equipment to serve energy loads of a building includes a cost function generator configured to obtain a cost function of decision variables representing an amount of resources consumed or produced by the equipment, an optimizer configured to perform a first optimization of the cost function subject to a first set of constraints defining first values of constraint variables to generate a first result defining first values of decision variables, a constraint modifier configured determine a cost gradient, recommend changes to constraint variables, and modify constraint variables to modified values in response to changes. The optimizer is configured to perform an optimization of the cost function subject to a second set of constraints to generate a second optimization result defining second values of the decision variables. The system includes a controller that operates equipment to consume or produce resources defined by second values of the decision variables.

Systems and methods are disclosed for preparing electrified vehicles to transfer energy to other structures. Weather related data and/or grid related data may be leveraged for predicting the likelihood of power outage conditions of a grid power source. When power outage conditions are predicted as being likely, the electrified vehicle may automatically enter a readiness state for transferring power to the structure without any time delays once an actual power outage condition occurs. Entering the readiness state may include steps such as waking up the electrified vehicle, initiating communications with electric vehicle supply equipment (EVSE), completing vehicle pre-checks, precharging certain power transfer system components, etc.

Systems, devices, and methods are provided for powering blockchain computational operations, capable of achieving Proof-of-Work-Without-Waste (PoW-WoW). Techniques described herein may involve utilizing a feedstock of various fossil fuels to generate an electrical power output at a power generating facility of a microgrid. The microgrid may have the capability to operate independently from a main grid. The electrical power output may be utilized to operate blockchain computational operations of a computing center. Further, byproduct of the feedstock may be captured prepared for carbon capture sequestration (CCS) and/or carbon capture utilization storage (CCUS) to reduce or eliminate emissions.

Certain aspects of the present disclosure relate to a local energy management system (LEMS) at local mixed power generating sites for providing grid services and grid service applications. The LEMS generally serves as a local power control agent for facilitating energy management at the local site level by controlling and leveraging a plurality of local assets deployed at the local site, and combining a plurality of generated power from each site which acts as its own virtual power plant for delivering grid services to the grid. In addition, the LEMS has the ability to effectively handle and fulfill energy and electrical objectives of the grid services, including regulation or demand response objectives from the grid, by conveying operational set points that control the power charge and discharge at each local asset in order to meet those objectives.

Embodiments are disclosed for predicting, by a processor circuit, a load parameter value of an electrical equipment for a future time based on at least one machine learning model and multiple load parameter values including a set of predefined number of load parameter values extracted from a time series data stream of load parameter values obtained for the electrical equipment. Thereafter calculating, by the processor circuit, an overload capability for the future time based on the predicted load parameter value and changing, by the processor circuit, at least one parameter associated with the electrical equipment at the present time based on the calculated overload capability for the future time.

A power system operation plan creation assistance device and method capable of maintaining or improving system stability or economy includes an optimization target snapshot power flow determination unit that uses one or more pieces of foundational information to determine an optimization target snapshot power flow. The foundational information includes a power generation plan, a total demand prediction, a sales plan, a renewable energy prediction, a work stoppage plan, system data, and a setting value. A system manipulation variable candidate extraction unit uses the one or more pieces of foundational information and the optimization target snapshot power flow to extract a candidate for a variable for a variable manipulating the system. An optimal system configuration calculation unit uses the one or more pieces of foundational information and the system manipulation variable candidate to calculate an optimal system configuration.

A computer system provides real-time control of power dispatch for a power system. The power system includes power generators, renewable power generators, load, and storage devices interconnected by a power grid. The computer system obtains input data, and solves an online multi-period power dispatch problem formulated from the input data and incorporates AC power flow in the power grid. The computer system generates control signals according to a solution of the online multi-period power dispatch problem, and sends the control signals to controllers of the power generators and the storage devices. In every time period during operation of the power system, the computer system updates the solution, generates updated control signals according to the updated solution, and sends the updated control signals to the controllers to continuously operate the power system with minimized operational cost while fully utilizing renewable power output.

Systems and methods provide intelligent battery charging and balancing. Energy deficits can be forecasted based on historical data and forecasted energy generation. The deficits can be used to determine charging currents over a period of time, and battery cassettes can be charged according to the charging currents to compensate for the forecasted energy deficit. The states of charge of the battery cassettes can be periodically rebalanced. The battery cassettes can be coupled in series and charged and balanced while providing output to a load.

A non-transitory computer-readable recording medium stores an energy system optimization program causing a computer to execute processes of predetermined steps, the steps including an input step of designating a plurality of types of energy facilities configuring an energy system, a calculation step of acquiring at least one of an optimal system configuration and an optimal operation pattern for which a predetermined index is minimal among at least one of system configurations and operation patterns of the energy system satisfying a predetermined demand, and an output step of outputting the at least one of the optimal system configuration and the optimal operation pattern.

Systems, methods, techniques and apparatuses of state estimation are disclosed. One exemplary embodiment is a method comprising determining, with a state estimator, a state estimate based on power grid data corresponding to characteristics of a power grid received from a plurality of local controllers; calculating, with the state estimator, a first gain matrix based on a Gauss-Newton method; updating, with the state estimator, the state estimate based on the first gain matrix; calculating, with the state estimator, a second gain matrix based on Newton's method; updating, with the state estimator, the state estimate based on the second gain matrix; and iteratively recalculating the second gain matrix and updating the state estimate based on the second gain matrix until the state estimate converges.