Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response

Existing energy systems face problems such as depleting fossil fuels, rising energy prices and greenhouse gas (GHG) emissions which seriously affect the comfort and affordability of energy for large-sized commercial customers. These problems may be mitigated by the optimal scheduling of distributed...

Full description

Bibliographic Details
Main Authors: Hafiz Abd Ul Muqeet, Aftab Ahmad
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9066843/
id doaj-6b531184dbdc427d9c6f7fc9862465b9
record_format Article
spelling doaj-6b531184dbdc427d9c6f7fc9862465b92021-03-30T02:58:48ZengIEEEIEEE Access2169-35362020-01-018713787139410.1109/ACCESS.2020.29879159066843Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand ResponseHafiz Abd Ul Muqeet0https://orcid.org/0000-0002-0866-4165Aftab Ahmad1Department of Electrical Engineering, University of Engineering and Technology at Taxila, Taxila, PakistanDepartment of Electrical Engineering, University of Engineering and Technology at Taxila, Taxila, PakistanExisting energy systems face problems such as depleting fossil fuels, rising energy prices and greenhouse gas (GHG) emissions which seriously affect the comfort and affordability of energy for large-sized commercial customers. These problems may be mitigated by the optimal scheduling of distributed generators (DGs) and demand response (DR) policies in the distribution system. The focus of this paper is to propose an energy management system (EMS) strategy for an institutional microgrid (μG) to reduce its operational cost and increase its self-consumption from green DGs. For this purpose, a real-time university campus has been considered that is currently feeding its load from the national grid only. However, under the proposed scenario, it contains building owned solar photovoltaic (PV) panels as non-dispatchable DG and diesel generator as dispatchable DG along with the energy storage system (ESS) to cope up with the intermittency of solar irradiance and high operational cost of grid energy. The resulting linear mathematical problem has been mapped in mixed-integer linear programming (MILP) and simulated in MATLAB. Simulations show that the proposed EMS model reduces the cost of grid electricity by 35% and 29% for summer and winter seasons respectively, while per day reductions in GHG emissions are 750.46 kg and 730.68 kg for the respective seasons. The effect of a half-sized PV installation on energy consumption cost and carbon emissions is also observed. Significant economic and environmental benefits as compared to the existing case are enticing to the campus owners to invest in DG and large-scale energy storage installation.https://ieeexplore.ieee.org/document/9066843/Batteriescampus microgriddistributed generationenergy storage systemenergy management systemprosumer market
collection DOAJ
language English
format Article
sources DOAJ
author Hafiz Abd Ul Muqeet
Aftab Ahmad
spellingShingle Hafiz Abd Ul Muqeet
Aftab Ahmad
Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response
IEEE Access
Batteries
campus microgrid
distributed generation
energy storage system
energy management system
prosumer market
author_facet Hafiz Abd Ul Muqeet
Aftab Ahmad
author_sort Hafiz Abd Ul Muqeet
title Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response
title_short Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response
title_full Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response
title_fullStr Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response
title_full_unstemmed Optimal Scheduling for Campus Prosumer Microgrid Considering Price Based Demand Response
title_sort optimal scheduling for campus prosumer microgrid considering price based demand response
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Existing energy systems face problems such as depleting fossil fuels, rising energy prices and greenhouse gas (GHG) emissions which seriously affect the comfort and affordability of energy for large-sized commercial customers. These problems may be mitigated by the optimal scheduling of distributed generators (DGs) and demand response (DR) policies in the distribution system. The focus of this paper is to propose an energy management system (EMS) strategy for an institutional microgrid (μG) to reduce its operational cost and increase its self-consumption from green DGs. For this purpose, a real-time university campus has been considered that is currently feeding its load from the national grid only. However, under the proposed scenario, it contains building owned solar photovoltaic (PV) panels as non-dispatchable DG and diesel generator as dispatchable DG along with the energy storage system (ESS) to cope up with the intermittency of solar irradiance and high operational cost of grid energy. The resulting linear mathematical problem has been mapped in mixed-integer linear programming (MILP) and simulated in MATLAB. Simulations show that the proposed EMS model reduces the cost of grid electricity by 35% and 29% for summer and winter seasons respectively, while per day reductions in GHG emissions are 750.46 kg and 730.68 kg for the respective seasons. The effect of a half-sized PV installation on energy consumption cost and carbon emissions is also observed. Significant economic and environmental benefits as compared to the existing case are enticing to the campus owners to invest in DG and large-scale energy storage installation.
topic Batteries
campus microgrid
distributed generation
energy storage system
energy management system
prosumer market
url https://ieeexplore.ieee.org/document/9066843/
work_keys_str_mv AT hafizabdulmuqeet optimalschedulingforcampusprosumermicrogridconsideringpricebaseddemandresponse
AT aftabahmad optimalschedulingforcampusprosumermicrogridconsideringpricebaseddemandresponse
_version_ 1724184199507738624