Real-Time Pricing Control on Generation-Side: Optimal Demand-Tracking Model and Information Fusion Estimation Solver

This paper develops the information fusion based pricing control (IFPC) scheme for the generation-side in the liberalized wholesale electricity market. The market mechanism is described by a feedback system, in which the independent system operator (ISO) interacts with generation companies (GenCOs) via proposing and responding to real-time nodal prices. The linear constrained quadratic optimal tracking problem is formulated; and the solution (nodal price sequence) is repeatedly computed by fusing the recently available information with backward manner and updated over the receding preview horizon. So that the total supply dynamically tracks the demand, the price is stationarized and each GenCO gains the maximal profit for the given price. Numeric results on a 118-bus network validate IFPC's effectiveness and flexibility on incorporating various line rating constraints as well as wind power fluctuation uncertainties. Comparative study demonstrates that IFPC outperforms the negotiated predictive dispatch but elapsing heavier computations. The irrational behavior analysis verifies the convergence to equilibrium; and speculation behavior of GenCOs in the real market is also discussed. Along with the rapid development of smart grid, IFPC is practically enabled by the information and communication technology (ICT); its significance and potentials for renewable energy sources (RES) integration would be realized and exploited.