Differential Dynamic Programming Based Home Energy Management Scheduler

Differential Dynamic Programming Based Home Energy Management Scheduler

This paper proposes a computationally efficient home energy management scheduler (HEMS) to minimize the cost of electricity consumption (CoEC) within a home which consists of rooftop photovoltaics (PV), a battery energy storage systems, and controllable appliances. Differential dynamic programming (...

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Bibliographic Details
Published in:IEEE transactions on sustainable energy Vol. 11; no. 3; pp. 1427 - 1437
Main Authors: Jeddi, Babak, Mishra, Yateendra, Ledwich, Gerard
Format: Journal Article
Language:English
Published: Piscataway IEEE 01-07-2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Batteries
battery degradation
Battery energy storage system
Computational modeling
Computer simulation
controllable appliances
Degradation
differential dynamic programming
Dynamic programming
Electric appliances
Electricity consumption
Energy conservation
Energy management
Energy storage
Home appliances
home energy management
Household appliances
Linear programming
Mixed integer
Nonlinear programming
Photovoltaic cells
Photovoltaics
Residential energy
Roofs
Schedules
Storage systems
Subspaces
Trajectory
Uncertainty
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Summary:This paper proposes a computationally efficient home energy management scheduler (HEMS) to minimize the cost of electricity consumption (CoEC) within a home which consists of rooftop photovoltaics (PV), a battery energy storage systems, and controllable appliances. Differential dynamic programming (DDP) algorithm is used and the uncertainty of PV generation and household demand along with the battery degradation is incorporated. The DDP algorithm divides the original problem space into several smaller subspaces and iteratively searches for a better solution within a subspace. The effectiveness of the developed framework is investigated through numerical simulations. The proposed HEMS minimizes the CoEC by determining an appropriate schedule of all devices ensuring an acceptable level for the customer comfort. The DPP-based HEMS is faster than the exact DP, approximate DP and mixed integer non-linear programming method. It is implemented in an intra-day setting where the BESS power is adjusted based on real-time observations of uncertain variable.
ISSN:1949-3029
1949-3037
DOI:10.1109/TSTE.2019.2927237