Next-generation energy market design and implementation

1. A method using smart grid technologies that bring in distributed, decentralized grid asset data and information into for the next generation of electricity market systems, said next generation of electricity market system that supporting competitive trading of electric energy and ancillary services within day-ahead and real-time market operation frameworks consisting of the following steps, which are a combination of known process steps, accomplished through any means currently known in the art, and novel steps:

a) Novel Trading platform facilitating market executions, auditing re-runs and study analysis comprising information storages and archival, wherein workspaces support system execution in operation and study environments;

b) Modeling of energy storage resources with notification times and inter-temporal parameters comparable with market timeline;

c) Novel Workflow controller facilitating solution sequences and iteration procedures, wherein said workflow controller to facilitate and manage system solution sequences;

d) Topology Processor determining network topology;

e) Pre-Processor validating market input data;

f) SCUC engine optimizing resource commitments and awarded quantities of market commodities;

g) SCED engine optimizing awarded quantities of market commodities respecting optimal resource commitments;

h) NA engine formulating transmission constraints;

i) Novel Pricing engine determining awarded market commodity settlement prices, and

j) Novel Post-Processing validating and delivering market clearing and pricing outcomes to downstream systems.

2. The method of claim 1 , further comprising a variety of solution steps, wherein said Solution Sequences facilitate and manage system execution.

3. The method of claim 1 , further comprising optimal resource commitments and market commodity quantities, wherein said SCUC engine to maximize economic efficiency of electricity market operation while ensuring electric power system reliability and solution quality.

4. The method of claim 3 , further comprising optimization method, wherein said Mixed Integer Linear Programming and Quadratic programming solvers are utilized to determine optimal resource commitments and market commodity quantities.

5. The method of claim 1 , further comprising optimal market commodity quantities for optimal resource commitments, wherein said SCED engine is utilized to maximize economic efficiency of electricity market operation while ensuring electric power system reliability and solution quality.

6. The method of claim 5 , further comprising optimization method, wherein said Mixed Integer Linear Programming and Quadratic programming solvers to determine optimal market commodity quantities for the optimal resource commitments.

7. The method of claim 3 , further comprising mathematical modeling, wherein said mathematical formulations are utilized to specify market operation objectives, constraints and characteristics in mathematical form.

8. The methods of claim 7 , further comprising optimization objective, wherein said objective function is utilized to specify market economic efficiency in a variety of market arrangements.

9. The methods of claim 7 , further comprising energy supply and demand balance, wherein said system power balance is utilized to specify main constraint in a variety of market arrangements.

10. The methods of claim 7 , further comprising required regional ancillary service procurements, wherein said ancillary service requirements are utilized to specify regional ancillary service constraints in a variety of market arrangements.

11. The methods of claim 10 , further comprising ancillary service cascading, wherein said ancillary service substitution is utilized to specify lower quality ancillary service replacement with higher quality ancillary services.

12. The methods of claim 7 , further comprising system security, wherein said transmission constraints are utilized to formulate transmission line power flow limits for base case and a variety of contingency cases.

13. The methods of claim 7 , further comprising resource operating constraints and limits, wherein said resource constraints to formulate the following resource characteristics:

a) Commitment status, startup and shutdown variables

b) Operating and regulating ranges

c) Static ramping limits

d) Dynamic ramping limits

e) Startup cost function for hot, warm and cold warmth states

f) Minimum up and down times

g) Maximum up time

h) Maximum number of starts

i) Commitment interdependency for joint owned units

j) Storage constraints for energy storage resources

k) Multi-state transition constraints for combined cycle plants.

14. The method of claim 7 , further comprising a market commodity pricing, wherein said pricing engine to determine settlement prices for awarded market commodities.

15. The method of claim 14 , further comprising a price formation mechanism, wherein said pricing schema for a variety of price formation processes as follows:

a) Dispatching pricing schema to determine prices for flexible market commodities

b) Relaxed pricing schema for fixed and flexible market commodities with hypothetical system dispatch

c) Partial commitment pricing schema allowing fractional resource commitments, and

d) Advanced pricing schema for fixed and flexible market commodities with preserved actual system dispatch.

16. The method of claim 5 , further comprising mathematical modeling, wherein said mathematical formulations are utilized to specify market operation objectives, constraints and characteristics in mathematical form.