Risk-constrained optimization of virtual power plants in pool and future markets

A system for distributing energy along a given scheduling horizon for an energy system including a renewable generating source, an energy storage system, a demand load and a conversion system, the system comprising:

• a centralized control (CC) system configured to:
• determine, an optimal value of a risk tolerance level for an uncertainty horizon of long-term forecasting non-stochastic uncertainties, for the energy system, the risk tolerance level having objectives prioritized relative to one another and constrained by short-term forecasting stochastic uncertainties, wherein the energy storage system stores energy from at least one of the renewable generating source and a grid, and supplies energy to at least one of the demand load and the grid, and wherein the conversion system directs a flow of energy between the energy storage system, the renewable generating source and the grid,
• wherein the long-term forecasting non-stochastic uncertainties and the short-term forecasting stochastic uncertainties are related to forecasted values including one or more of energy market values, electricity rates, and power production, storage and consumption,
• wherein the objectives are optimized to generate solutions that maximize an expected total pool market revenue and an expected total future market revenue while minimizing an expected total energy cost for the energy system, and
• wherein the objectives are optimized subject to feasibility constraints generated from a lower bound and an upper bound of an information gap region defined for long-term uncertainties, and technical constraints and additional constraints, wherein the technical constraints are generated from a lower boundary for a profit distribution using second-order stochastic dominance constraints, and wherein the additional constraints include a constraint that requires a level of balancing of power provided to and from the grid;
• identify long-term and short-term energy distribution schedules for charging or discharging the energy storage system, controlling local load demands and contributing to power balancing, based on the solutions of the optimization;
• and
• control the distribution of energy to manage the charging or discharging of the energy storage system, the controlling of local load demands and the contributing of power balancing according to the identified long-term and short-term energy distribution schedules.

A system for distributing energy along a given scheduling horizon for a virtual power plant (VPP) including a renewable generating source, an energy storage device, and a conversion system, the grid, the system comprising:

• a centralized control (CC) system in communication with the renewable generating source, the energy storage device, a grid and the conversion system, the CC system configured to:
• determine an optimal value of a risk tolerance level for an uncertainty horizon of long-term forecasting non-stochastic uncertainties for the VPP, the risk tolerance level having objectives prioritized relative to one another and constrained by short-term forecasting stochastic uncertainties, wherein the energy storage device is configured to store energy from the renewable generating source and the grid, and supply energy to a local demand load and the grid, and wherein the conversion system is configured to direct a flow of energy between the energy storage device, the renewable generating source and the grid,
• wherein the long-term forecasting non-stochastic uncertainties and the short-term forecasting stochastic uncertainties are related to forecasted values including one or more of energy market values, electricity rates, and power production, storage and consumption,
• wherein the objectives are optimized to generate solutions that maximize an expected total pool market revenue and an expected total future market revenue while minimizing an expected total energy cost for the energy system, and
• wherein the objectives are optimized subject to feasibility constraints generated from a lower bound and an upper bound of an information gap region defined for long-term uncertainties, and technical constraints and additional constraints, wherein the technical constraints are generated from a lower boundary for a profit distribution using second-order stochastic dominance constraints, and wherein the additional constraints include a constraint that requires a level of balancing of power provided to and from the grid;
• identify long-term and short-term energy distribution schedules for charging or discharging the energy storage device, controlling local load demands and contributing to power balancing, based on the solutions of the optimization;
• and
• control the distribution of energy for the VPP to manage the charging or discharging of the energy storage device, the controlling of local load demands and the contributing of power balancing according to the identified long-term and short-term energy distribution schedules.