A method for controlling energy supply to different units includes receiving, by an aggregator, the demand request signal, and performing, by the aggregator, an allocation of the requested demand modification to the units based on a negotiating process with the units for minimizing an impact of the allocation on a future operation of another utility or of other utilities. Each unit is connected to multiple utilities for receiving enemy for operating its energy systems. A demand request signal is provided by at least one operational entity and/or by at least one utility for requesting a demand modification of a utility and/or of one form of energy.

A demand-response system includes first and second aggregators and a power aggregator. The first aggregator performs demand-response-related control of a first heating device group including a heat pump device, and the second aggregator performs demand-response related control of a second heating device group. The power aggregator sends a second power adjustment request to the first and second aggregators using a command being common to the first and second aggregators. In accordance with the second power adjustment request, the first aggregator performs demand-response-related control of the first heating device group using a first dedicated command, and the second aggregator performs demand-response-related control of the second heating device group using a second dedicated command that is different from the first dedicated command.

A thermal behavior model of a building may be constructed based on time series data. Based on the constructed thermal behavior model, forecasted zone temperature and energy usage for a next control time period may be predicted. An objective function may be constructed based on at least a dynamically priced grid energy cost, occupant comfort matrix, and one or more of: energy storage system cost and associated operational cost, and energy generation system cost and associated green house emission cost and associated operational cost. Constraints may be constructed based on at least the forecasted zone temperature values and energy usage values for the next control time period. A control profile of the HVAC system and sourcing decision of energy load of the HVAC system may be determined simultaneously based on the objective function and the plurality of constraints.

Resources are required to satisfy various needs and wants of people, businesses, and machines. Resources come in the forms of time, talents, money, materials, energy, services, people, knowledge, communication, and other tangible and intangible assets. When both the capacities and the needs of multiple resources are stored in a way that allows for them to be connected together using computers, they can be efficiently and effectively matched. This matching creates shared value, which has potential academic, economic, societal and philanthropic benefits. Connected computer system(s) can query and match resources together in a way that is mutually beneficial. While a common lexicon is the simplest way to perform the matching, natural language processing, machine translation, or use of similar technologies may be optimal. Any method of collecting these inputs should be able to handle one or multiple capacities, and one or multiple needs.

The power flexibility of energy loads is maximized using a value function for each load and outputting optimal control parameters. Loads are aggregated into a virtual load by maximizing a global value function. The solution yields a dispatch function providing: a percentage of energy for each individual load, a time-varying power level for each load, and control parameters and values. An economic term represents the value of the power flexibility to different players. A user interface includes for each time interval upper and lower bounds representing respectively the maximum power that may be reduced to the virtual load and the maximum power that may be consumed. A trader modifies an energy level in a time interval relative to the reference curve for the virtual load. Automatically, energy compensation for other intervals and recalculation of upper and lower boundaries occurs. The energy schedule for the virtual load is distributed to the actual loads.

The present invention is directed to a system for generating thermal energy from different energy sources, having a combustion-powered thermal energy source, an electric-powered thermal energy source, a steam distribution system, and a controller. The combustion-powered thermal energy source and the electric-powered each having a plurality of sensors. The controller is configured to actuate either or both of the energy sources based at least in part on information received from one or more of the plurality of sensors.

Embodiments of systems and methods for power demand management are described herein. More specifically, embodiments comprise systems and methods for powering, controlling, and/or operating various types of controllable load for integration with power fluctuations from intermittent power generation plants, such as photovoltaic arrays and wind turbine farms.