ﻣﺪل ﺑﻬﯿﻨﻪ ﺳﺎزي ﻣﻘﺎوم ﺑﺮاي ﻣﺪﯾﺮﯾﺖ ﻋﺪم ﻗﻄﻌﯿﺖ در ﺳﯿﺴﺘﻢ ﻫﻮﺷﻤﻨﺪ ﻫﺎب اﻧﺮژي و آب ﺑﺎ در ﻧﻈﺮﮔﯿﺮي ﺑﺮﻧﺎﻣﻪ ﻫﺎي ﭘﺎﺳﺨﮕﻮﯾﯽ ﺑﺎر

A Robust Optimization Approach for Uncertainty Management of Smart Water and Energy Hub along with Demand Response Program

ﭼﮑﯿﺪه: ﻣﺪﯾﺮﯾﺖ ﯾﮑﭙﺎرﭼﻪ آب و دﯾﮕﺮ ﺣﺎﻣﻞ ﻫﺎي اﻧﺮژي ﻣﺎﻧﻨﺪ ﺑﺮق، ﮔﺎز و ﺗﻮان ﺣﺮارﺗﯽ ﺳﺒﺐ ارﺗﻘﺎي ﺑﺎزده اﻗﺘﺼﺎدي در ﻫﺎب اﻧﺮژي ﻣﯽ ﮔﺮدد. ﯾﮑﯽ از ﭼﺎﻟﺶ ﻫﺎي ﻋﻤﺪه اي ﮐﻪ ﻣﺎﻧﻊ اﺛﺮﺑﺨﺸﯽ اﯾﻦ ﻣﺪﯾﺮﯾﺖ ﯾﮑﭙﺎرﭼﻪ ﻣﯽ ﺷﻮد ﻋﺪم ﻗﻄﻌﯿﺖ ﻗﯿﻤﺖ ﺑﺮق در ﺑﺎزار ﺑﺎﻻدﺳﺖ اﺳﺖ. ﺑﺮاي ﺣﻞ اﯾﻦ ﻣﺸﮑﻞ، اﯾﻦ ﻣﻘﺎﻟﻪ ﯾﮏ روش ﺑﻬﯿﻨﻪ ﺳﺎزي ﻣﻘﺎوم ﺑﺮاي ﻣﺪﯾﺮﯾﺖ ﻋﺪم ﻗﻄﻌﯿﺖ در ﻣﺪل ﯾﮑﭙﺎرﭼﻪ ﻫﺎب ﻫﻮﺷﻤﻨﺪ اﻧﺮژي و آب اراﺋﻪ ﻣﯽ دﻫﺪ. در روﯾﮑﺮد ﻣﻘﺎوم ﭘﯿﺸﻨﻬﺎدي، ﺗﺎﺑﻊ ﻫﺪف ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﻣﺠﻤﻮﻋﻪ ﻋﺪم ﻗﻄﻌﯿﺖ ﻣﺴﺌﻠﻪ ﺑﻬﯿﻨﻪ ﻣﯽ ﺷﻮد. ﭘﺎﺳﺦ ﺑﻬﯿﻨﻪ ﺑﻪ دﺳﺖ آﻣﺪه ﺗﻮﺳﻂ روش ﭘﯿﺸﻨﻬﺎدي ﺑﻬﺘﺮﯾﻦ اﺳﺘﺮاﺗﮋي را ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ رﻓﺘﺎر ﺑﻬﺮه ﺑﺮدار ﺳﯿﺴﺘﻢ ﻧﺴﺒﺖ ﺑﻪ رﯾﺴﮏ اراﺋﻪ ﻣﯽ دﻫﺪ. ﻣﺪل ﺑﻬﯿﻨﻪ ﺳﺎزي ﻣﻘﺎوم اﻧﺮژي و آب ﭘﯿﺸﻨﻬﺎدي ﯾﮏ ﻣﺪل ﺑﻬﯿﻨﻪ ﺳﺎزي ﺧﻄﯽ آﻣﯿﺨﺘﻪ ﺑﺎ اﻋﺪاد ﺻﺤﯿﺢ اﺳﺖ ﮐﻪ ﺗﻮﺳﻂ ﺣﻠﮕﺮ ﺳﯿﭙﻠﮑﺲ در ﻣﺤﯿﻂ ﮔﻤﺰ ﺣﻞ ﻣﯽ ﺷﻮد. اﺛﺮﺑﺨﺸﯽ روش ﭘﯿﺸﻨﻬﺎدي در ﯾﮏ ﻣﻄﺎﻟﻌﻪ ﻣﻮردي ﻣﻮرد ﺑﺮرﺳﯽ ﻗﺮار ﮔﺮﻓﺘﻪ اﺳﺖ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن ﻣﯽ دﻫﺪ ﮐﻪ ﻫﺰﯾﻨﻪ ﺑﻬﺮه ﺑﺮداري ﻣﺪل ﭘﯿﺸﻨﻬﺎدي ﺗﻘﺮﯾﺒﺎً در ﺑﺪﺗﺮﯾﻦ ﺣﺎﻟﺖ 1,6 درﺻﺪ اﻓﺰاﯾﺶ ﻣﯽ ﯾﺎﺑﺪ. ﺑﺎ اﯾﻦ ﺣﺎل، ﻣﯿﺰان ﻣﻘﺎوم ﺑﻮدن ﺳﯿﺴﺘﻢ ﺑﻪ ﻃﻮر ﻗﺎﺑﻞ ﺗﻮﺟﻬﯽ اﻓﺰاﯾﺶ ﯾﺎﻓﺘﻪ اﺳﺖ.

Energy and water are two important factors that are crucial for human survival. In an energy hub, integrated management of water and multi-type of energies such as electrical power, gas, and thermal power increases the economic efficiency of using vital resources. One of the major challenges that deter the effectiveness of this integrated management is the electricity price uncertainties of the upstream market. To address this problem, this paper provides a novel mathematical model along with a robust optimization approach for uncertainty management in smart water and energy hubs. In the proposed robust uncertainty approach, the objective function is optimized subject to the uncertainty set of the problem. Therefore, the optimal solution of the proposed optimization problem is an effective point referring to the amount of specified uncertainty budget by the energy hub system operator. Moreover, a new water infrastructure including a water desalination system and water storage is considered in the proposed smart water and energy hubs. The proposed power and water robust optimization (PWRO) is a Mixed Integer Linear Programing (MILP) model and is solved by CPLEX solver in GAMS environment. The effectiveness of the proposed approach is examined in a case study. Results show that the operation cost of the proposed model increases 1.6 % percent approximately in the worst case. However, the robustness of the system is significantly increased.