TY - JOUR
T1 - Optimal investment and operation of a microgrid to provide electricity and heat
AU - Angarita, Jorge L.
AU - Jafari, Hossein
AU - Mohseni, Mojtaba
AU - Al-Sumaiti, Ameena Saad
AU - Heydarian-Forushani, Ehsan
AU - Kumar, Rajesh
N1 - Publisher Copyright:
© 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
PY - 2021/9/7
Y1 - 2021/9/7
N2 - This paper proposes a robust investment and operation model to attend the power and heat needs of a microgrid (MG) connected to the distribution system. The optimization algorithm decides on the best investment and operation of combined heat and power (CHP), boilers, PV power generation and battery energy storage systems (BESS). For the BESS, the algorithm estimates the optimal energy storage capacity (MWh) as well as the maximum hourly delivery capacity (MW). The non-linear and non-concave heat rate chart is recast by a mix-integer linear model to have a tractable and precise model. The model considers the uncertain in some parameters using probability density function (pdf) to portrait its behavior. Thus, the problem has been modeled using stochastic programming approach, and its objective function is the expected value of the annual operational cost. The model is tested using a real case where two adjacent consumers share the power and heat facilities to minimize the overall up to 17% depending on the gas price scenario. The results demonstrate the benefits of employing different technologies and the synergies of all technologies operating together.
AB - This paper proposes a robust investment and operation model to attend the power and heat needs of a microgrid (MG) connected to the distribution system. The optimization algorithm decides on the best investment and operation of combined heat and power (CHP), boilers, PV power generation and battery energy storage systems (BESS). For the BESS, the algorithm estimates the optimal energy storage capacity (MWh) as well as the maximum hourly delivery capacity (MW). The non-linear and non-concave heat rate chart is recast by a mix-integer linear model to have a tractable and precise model. The model considers the uncertain in some parameters using probability density function (pdf) to portrait its behavior. Thus, the problem has been modeled using stochastic programming approach, and its objective function is the expected value of the annual operational cost. The model is tested using a real case where two adjacent consumers share the power and heat facilities to minimize the overall up to 17% depending on the gas price scenario. The results demonstrate the benefits of employing different technologies and the synergies of all technologies operating together.
UR - http://www.scopus.com/inward/record.url?scp=85105229230&partnerID=8YFLogxK
U2 - 10.1049/rpg2.12190
DO - 10.1049/rpg2.12190
M3 - Article
AN - SCOPUS:85105229230
SN - 1752-1416
VL - 15
SP - 2586
EP - 2595
JO - IET Renewable Power Generation
JF - IET Renewable Power Generation
IS - 12
ER -