{"id":467,"date":"2015-10-04T09:04:10","date_gmt":"2015-10-04T09:04:10","guid":{"rendered":"http:\/\/profs.hsu.ac.ir\/msamadi\/?p=310"},"modified":"2020-02-25T11:37:23","modified_gmt":"2020-02-25T08:07:23","slug":"%d9%84%db%8c%d8%b3%d8%aa-%d9%85%d9%82%d8%a7%d9%84%d8%a7%d8%aa-%d9%85%d8%b1%d8%a8%d9%88%d8%b7-%d8%a8%d9%87-%d9%be%d8%b1%d9%88%da%98%d9%87-%d8%af%d8%b1%d8%b3-%d8%a8%d9%87%d8%b1%d9%87-%d8%a8%d8%b1%d8%af","status":"publish","type":"post","link":"https:\/\/staff.hsu.ac.ir\/msamadi\/2015\/10\/04\/%d9%84%db%8c%d8%b3%d8%aa-%d9%85%d9%82%d8%a7%d9%84%d8%a7%d8%aa-%d9%85%d8%b1%d8%a8%d9%88%d8%b7-%d8%a8%d9%87-%d9%be%d8%b1%d9%88%da%98%d9%87-%d8%af%d8%b1%d8%b3-%d8%a8%d9%87%d8%b1%d9%87-%d8%a8%d8%b1%d8%af\/","title":{"rendered":"\u0645\u0642\u0627\u0644\u0627\u062a \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u067e\u0631\u0648\u0698\u0647 \u062f\u0631\u0633 \u0628\u0647\u0631\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc (\u0645\u0647\u0631 94)"},"content":{"rendered":"

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\u0622\u062f\u0631\u0633 \u0627\u06cc\u0645\u06cc\u0644: mmm.samadi@gmail.com<\/p>\n

1<\/a> 2<\/a> 3<\/a> 4<\/a> 5<\/a> 6<\/a> 7<\/a> 8<\/a> 9<\/a> 10<\/a> 11<\/a> 12<\/a> 13<\/a><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
1<\/td>\n\n

A decomposition method for network-constrained unit commitment with AC power \ufb02ow constraints<\/p>\n<\/td>\n<\/tr>\n

2<\/td>\nIntegrated \u00a0 dispatch of generation and load: A pathway towards smart Grids<\/td>\n<\/tr>\n
3<\/td>\nA probabilistic economic dispatch model and methodology considering renewable energy, demand and generator uncertainties<\/td>\n<\/tr>\n
4<\/td>\nImpact of demand response resources on unit commitment and dispatch in a day-ahead electricity market<\/td>\n<\/tr>\n
5<\/td>\nUnit Commitment Model in Smart Grid Environment Considering Carbon Emissions Trading<\/td>\n<\/tr>\n
6<\/td>\nReal time probabilistic power system state estimation<\/td>\n<\/tr>\n
7<\/td>\nCentralized and decentralized optimal decision support for congestion Management<\/td>\n<\/tr>\n
8<\/td>\nIndirect coordination of electricity demand for balancing wind power<\/td>\n<\/tr>\n
9<\/td>\nEconomic Dispatch of Demand Response Balancing Through Asymmetric Block Offers<\/td>\n<\/tr>\n
10<\/td>\nOptimal Residential Demand Response in Distribution Networks<\/td>\n<\/tr>\n
11<\/td>\nA Trend-Oriented Power System Security Analysis Method Based on Load Pro\ufb01le<\/td>\n<\/tr>\n
12<\/td>\nSecurity-Constrained Optimal Power and Natural-Gas Flow<\/td>\n<\/tr>\n
13<\/td>\nImpacts of High Penetration Wind Generation and Demand Response on LMPs in Day-Ahead Market<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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