ﺑﺮﻧﺎﻣﻪرﯾﺰي اﺳﺘﻮار ﺳﯿﺴﺘﻢ ﺗﺮﮐﯿﺒﯽ ﺟﺰﯾﺮهاي ﺷﺎﻣﻞ ﻣﻨﺎﺑﻊ ﺗﺠﺪﯾﺪﭘﺬﯾﺮ و ﺗﺠﺪﯾﺪﻧﺎﭘﺬﯾﺮ و ذﺧﯿﺮهﺳﺎزﻫﺎي ﺳﺎﮐﻦ و ﺳﯿﺎر

Robust Planning of the Islanded Hybrid System Including Renewable and Non-Renewable Sources and Stationary and Mobile Storages

در اﯾﻦ ﻣﻘﺎﻟﻪ ﺑﺮﻧﺎﻣﻪرﯾﺰي اﺳﺘﻮار ﺳﯿﺴﺘﻢ ﺗﺮﮐﯿﺒﯽ ﺟﺰﯾﺮهاي ﺟﻬﺖ اﯾﺠﺎد ﯾﮏ ﺳﯿﺴﺘﻢ ﯾﮏﭘﺎرﭼﻪ ﺷﺎﻣﻞ ﺗﻮرﺑﯿﻦ ﺑﺎدي، ﻓﺘﻮوﻟﺘﺎﺋﯿﮏ، دﯾﺰل ژﻧﺮاﺗﻮر و ذﺧﯿﺮهﺳﺎزي ﺳﺎﮐﻦ )ﺑﺎﺗﺮي( و ﺳﯿﺎر )ﺧﻮدروﻫﺎي اﻟﮑﺘﺮﯾﮑﯽ( اراﺋﻪ ﻣﯽﺷﻮد. ﻃﺮح ﭘﯿﺸﻨﻬﺎدي ﮐﻤﯿﻨﻪﺳﺎزي ﻣﺠﻤﻮع ﻫﺰﯾﻨﻪ ﺑﺮﻧﺎﻣﻪرﯾﺰي )ﺷﺎﻣﻞ اﺣﺪاث، ﺗﻌﻤﯿﺮ، ﻧﮕﻬﺪاري و ﺑﻬﺮهﺑﺮداري( ﻋﻨﺎﺻﺮ ﻣﺬﮐﻮر و ﺳﻄﺢ آﻻﯾﻨﺪﮔﯽ زﯾﺴﺖ ﻣﺤﯿﻄﯽ را ﺑﺮ ﻋﻬﺪه دارد. اﯾﻦ ﻣﺴﺄﻟﻪ ﻧﯿﺰ ﻣﻘﯿﺪ ﺑﻪ ﻣﺪل ﺑﻬﺮهﺑﺮداري و ﺑﺮﻧﺎﻣﻪرﯾﺰي ﻣﻨﺎﺑﻊ و ذﺧﯿﺮهﺳﺎزﻫﺎي ﻣﺨﺘﻠﻒ و ﻗﯿﺪ ﺗﻌﺎدل ﺗﻮان در ﺳﯿﺴﺘﻢ ﺗﺮﮐﯿﺒﯽ ﺟﺰﯾﺮهاي اﺳﺖ. ﻃﺮح ﻣﺬﮐﻮر در ﻗﺎﻟﺐ ﺑﻬﯿﻨﻪﺳﺎزي ﭘﺎرﺗﻮ ﻣﺒﻨﯽ ﺑﺮ روش ﻣﺠﻤﻮع ﺗﻮاﺑﻊ وزندار ﻣﺪلﺳﺎزي ﻣﯽﺷﻮد. ﻫﻤﭽﻨﯿﻦ از ﺑﻬﯿﻨﻪﺳﺎزي اﺳﺘﻮار ﻣﺒﻨﯽ ﺑﺮ ﻋﺪم ﻗﻄﻌﯿﺖ ﮐﺮاندار ﺑﺮاي ﻣﺪلﺳﺎزي ﻋﺪم ﻗﻄﻌﯿﺖﻫﺎي ﺑﺎر، ﺗﻮان ﺗﺠﺪﯾﺪﭘﺬﯾﺮ و اﻧﺮژي ذﺧﯿﺮهﺳﺎزﻫﺎي ﺳﯿﺎر اﺳﺘﻔﺎده ﻣﯽﺷﻮد. ﺳﭙﺲ از اﻟﮕﻮرﯾﺘﻢ ﺗﮑﺎﻣﻠﯽ ﺗﺮﮐﯿﺒﯽ ﻣﺒﻨﯽ ﺑﺮ ﺗﺮﮐﯿﺐ ﺑﻬﯿﻨﻪﺳﺎزي دﺳﺘﻪ ﻣﯿﮕﻮﻫﺎ و ﺑﻬﯿﻨﻪﺳﺎزي ﮔﺮگﻫﺎي ﺧﺎﮐﺴﺘﺮي ﺟﻬﺖ دﺳﺖﯾﺎﺑﯽ ﺑﻪ راهﺣﻞ ﺑﻬﯿﻨﻪ داراي اﻧﺤﺮاف ﻣﻌﯿﺎر ﭘﺎﯾﯿﻦ در ﭘﺎﺳﺦدﻫﯽ ﻧﻬﺎﯾﯽ اﺳﺘﻔﺎده ﻣﯽﮔﺮدد. در ﻧﻬﺎﯾﺖ ﺑﺎ اﺳﺘﺨﺮاج ﻧﺘﺎﯾﺞ ﻋﺪدي ﻣﺸﺎﻫﺪه ﻣﯽﮔﺮدد ﮐﻪ ﻃﺮح ﭘﯿﺸﻨﻬﺎدي ﻗﺎﺑﻠﯿﺖ ﻣﻨﺎﺳﺒﯽ در ﺑﺮﻧﺎﻣﻪرﯾﺰي ﺳﯿﺴﺘﻢ ﯾﺎد ﺷﺪه از ﻧﻈﺮ اﻗﺘﺼﺎدي و زﯾﺴﺖ ﻣﺤﯿﻄﯽ دارد.

In this paper, the robust planning of the islanded hybrid system (IHS) to create an integrated system with wind turbine, photovoltaic, diesel generator, stationary (battery) and mobile (electric vehicles) storages is presented. The proposed scheme minimizes the planning cost (including construction, maintenance, and operation) of the mentioned sources and storages, and environmental pollution level. This problem is constrained to operation and planning model of the different sources and storages, and power balance constraint in IHS. The proposed scheme is formulated in the Pareto optimization framework based on method of the summation of weighted functions. Also, the bounded uncertainty-based robust optimization (BURO) is used to model the uncertainties of load, renewable power, and energy of mobile storage. Then, the hybrid evolutionary algorithm according to composition of Krill Herd Optimization (KHO) and Grey Wolf Optimization (GWO) algorithms obtains an optimal solution including low standard deviation in the final response. Finally, it is seen that the proposed scheme has a suitable capability in the planning of the proposed system according to economic and environmental viewpoints based on obtained numerical results.