Optimal planning of CHP-based microgrids considering DERs and demand response programs
Qaeini, Saeid; Nazar, Mehrdad S.; Shafie-khah, Miadreza; Osório, Gerardo J.; Catalão, João P. S. (2020-07-15)
Qaeini, Saeid
Nazar, Mehrdad S.
Shafie-khah, Miadreza
Osório, Gerardo J.
Catalão, João P. S.
IEEE
15.07.2020
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2020073047755
https://urn.fi/URN:NBN:fi-fe2020073047755
Kuvaus
vertaisarvioitu
©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Tiivistelmä
This work addresses a stochastic framework for optimal operation and long-term expansion planning of combined heat and power based microgrid as a part of an active distributing system. The microgrid utilizes renewable energy sources, electricity and heat generation units, energy storage systems, and demand response programs. The proposed model determines the optimal location and capacity of the electrical and thermal facilities, and it considers the impact of renewable energy sources and demand response on the expansion-planning problem. A stochastic mixed-integer linear programming formulation is utilized to minimize the investment and operation costs of system for five years. To evaluate the effectiveness of the proposed model, the algorithm is assessed for the 9-bus system and the 33-bus IEEE test systems. The results demonstrate that the utilization of the proposed algorithm reduces the operational cost and increases system revenues.
Kokoelmat
- Artikkelit [2788]