This paper addresses two issues that concern the electricity market participants under the European day-ahead market(DAM)framework,namely the feasibility of the attained schedules and the non-confiscation of cleared v...This paper addresses two issues that concern the electricity market participants under the European day-ahead market(DAM)framework,namely the feasibility of the attained schedules and the non-confiscation of cleared volumes.To address the first issue,new resource-specific orders,i.e.,thermal orders for thermal generating units,demand response orders for load responsive resources,and energy limited orders for storage resources,are proposed and incorporated in the existing European DAM clearing problem.To address the second issue,two approaches which lead to a non-confiscatory market are analyzed:①discriminatory pricing with side-payments(U.S.paradigm);and②non-discriminatory pricing excluding out-ofmoney orders(European paradigm).A comparison is performed between the two approaches to investigate the most appropriate pricing rule in terms of social welfare,derived revenues for the sellers,and efficiency of the attained results.The proposed model with new resource-specific products is evaluated in a European test system,achieving robust solutions.The feasibility of the attained schedules is demonstrated when using resource-specific orders compared with block orders.Finally,the results indicate the supremacy of discriminatory pricing with side-payments compared with the current European pricing rule.展开更多
This paper proposes the day-ahead electricity price forecasting using the artificial neural networks （ANN） and weighted least square （WLS） technique in the restructured electricity markets. Price forecasting is ve...This paper proposes the day-ahead electricity price forecasting using the artificial neural networks （ANN） and weighted least square （WLS） technique in the restructured electricity markets. Price forecasting is very important for online trading, e-commerce and power system operation. Forecasting the hourly locational marginal prices （LMP） in the electricity markets is a very important basis for the decision making in order to maximize the profits/benefits. The novel approach pro- posed in this paper for forecasting the electricity prices uses WLS technique and compares the results with the results obtained by using ANNs. To perform this price forecasting, the market knowledge is utilized to optimize the selection of input data for the electricity price forecasting tool. In this paper, price forecasting for Pennsylvania-New Jersey-Maryland （PJM） interconnec- tion is demonstrated using the ANNs and the proposed WLS technique. The data used for this price forecasting is obtained from the PJM website. The forecasting results obtained by both methods are compared, which shows the effectiveness of the proposed forecasting approach. From the simulation results, it can be observed that the accuracy of prediction has increased in both seasons using the proposed WLS technique. Another important advantage of the proposed WLS technique is that it is not an iterative method.展开更多
文摘This paper addresses two issues that concern the electricity market participants under the European day-ahead market(DAM)framework,namely the feasibility of the attained schedules and the non-confiscation of cleared volumes.To address the first issue,new resource-specific orders,i.e.,thermal orders for thermal generating units,demand response orders for load responsive resources,and energy limited orders for storage resources,are proposed and incorporated in the existing European DAM clearing problem.To address the second issue,two approaches which lead to a non-confiscatory market are analyzed:①discriminatory pricing with side-payments(U.S.paradigm);and②non-discriminatory pricing excluding out-ofmoney orders(European paradigm).A comparison is performed between the two approaches to investigate the most appropriate pricing rule in terms of social welfare,derived revenues for the sellers,and efficiency of the attained results.The proposed model with new resource-specific products is evaluated in a European test system,achieving robust solutions.The feasibility of the attained schedules is demonstrated when using resource-specific orders compared with block orders.Finally,the results indicate the supremacy of discriminatory pricing with side-payments compared with the current European pricing rule.
文摘This paper proposes the day-ahead electricity price forecasting using the artificial neural networks （ANN） and weighted least square （WLS） technique in the restructured electricity markets. Price forecasting is very important for online trading, e-commerce and power system operation. Forecasting the hourly locational marginal prices （LMP） in the electricity markets is a very important basis for the decision making in order to maximize the profits/benefits. The novel approach pro- posed in this paper for forecasting the electricity prices uses WLS technique and compares the results with the results obtained by using ANNs. To perform this price forecasting, the market knowledge is utilized to optimize the selection of input data for the electricity price forecasting tool. In this paper, price forecasting for Pennsylvania-New Jersey-Maryland （PJM） interconnec- tion is demonstrated using the ANNs and the proposed WLS technique. The data used for this price forecasting is obtained from the PJM website. The forecasting results obtained by both methods are compared, which shows the effectiveness of the proposed forecasting approach. From the simulation results, it can be observed that the accuracy of prediction has increased in both seasons using the proposed WLS technique. Another important advantage of the proposed WLS technique is that it is not an iterative method.
