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AuthorKanaan, Laith
AuthorIsmail, Loay S.
AuthorGowid, Samer
AuthorMeskin, Nader
AuthorMassoud, Ahmed M.
Available date2024-03-13T09:01:26Z
Publication Date2023
Publication NameIEEE Access
ResourceScopus
ISSN21693536
URIhttp://dx.doi.org/10.1109/ACCESS.2023.3281562
URIhttp://hdl.handle.net/10576/53010
AbstractUncertainties in load and solar power forecasting, complex energy storage system (ESS) constraints, and feedback correction pose challenges for very short-term and short-term hybrid power plant scheduling. This paper proposes a two-stage mixed-integer linear programming (MILP)-based energy dispatch engine (EDE). The proposed model ensures optimized scheduling through accurate load and power forecasting, a feedback correction loop, and a set of constraints governing the state of charge (SOC) and state of health (SOH) of the ESS. Such an EDE aims to reduce the plant's operating costs and the usage of diesel generators (DGs), and minimize the cost of carbon emissions. To test the performance of the developed model, real-time load and photovoltaic (PV) data were used in conjunction with a PV-DG-ESS hybrid plant. The system was evaluated against a heuristic control model and a multistage stochastic control model, with the daily overall electricity and carbon emission costs as evaluation metrics. The test results revealed a 9.2% and 3.5% decrease in daily costs compared to the heuristic and stochastic methods, respectively, and a 29.4% decrease in carbon emission costs.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectenergy dispatch engine (EDE)
energy management system (EMS)
forecasting
Hybrid power plants
mixed integer linear programming (MILP)
optimization
TitleOptimal Energy Dispatch Engine for PV-DG-ESS Hybrid Power Plants Considering Battery Degradation and Carbon Emissions
TypeArticle
Pagination58506-58515
Volume Number11
dc.accessType Open Access


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