Title :
Impacts of High Penetration Wind Generation and Demand Response on LMPs in Day-Ahead Market
Author :
Zhechong Zhao ; Lei Wu
Author_Institution :
Electr. & Comput. Eng. Dept., Clarkson Univ., Potsdam, NY, USA
Abstract :
Environmental issues in power systems operation lead to a rapid deployment of renewable wind generations. Wind generation is usually given the highest priority by assigning zero or negative energy bidding prices in the day-ahead power market, in order to effectively utilize available wind energy. However, when congestions occur, negative wind bidding prices would aggravate negative locational marginal prices (LMPs) in certain locations. The paper determines the proper amount of demand response (DR) load to be shifted from peak hours to off peaks under the Independent System Operator´s (ISO) direct load control, for alleviating transmission congestions and enhancing the utilization of wind generation. The proposed mixed-integer linear programming (MILP) model is to minimize the total operation cost while incorporating explicit LMP formulations and non-negative LMP requirements into the network-constrained unit commitment (NCUC) problem, which are derived from the Karush-Kuhn-Tucker (KKT) optimality conditions of the economic dispatch (ED) problem. Numerical case studies illustrate the effectiveness of the proposed model.
Keywords :
integer programming; linear programming; load regulation; power generation dispatch; power generation scheduling; power markets; wind power; ISO; KKT optimality conditions; Karush-Kuhn-Tucker optimality conditions; LMP; MILP; NCUC problem; day-ahead power market; demand response; direct load control; economic dispatch problem; energy bidding prices; environmental issue; high penetration wind generation; independent system operator; locational marginal prices; mixed integer linear programming; network-constrained unit commitment problem; power systems operation; renewable wind generations; transmission congestions; wind energy; Generators; Load management; Load modeling; Power systems; Wind energy generation; Wind forecasting; Wind power generation; Demand response; KKT; LMP; NCUC; load shifting; wind generation;
Journal_Title :
Smart Grid, IEEE Transactions on
DOI :
10.1109/TSG.2013.2274159