Loads scheduling for demand response in energy communities

Article Green & Sustainable Science & Technology

A Bi-level optimization-based community energy management system for optimal energy sharing and trading among peers

Edstan Fernandez et al.

Summary: This paper proposes an energy management system for a smart locality that facilitates local energy trading, and develops two optimization frameworks for optimal resource allocation and revenue maximization. The study finds that energy sharing can maximize overall revenue, and grid pricing scheme is a major factor in determining revenue sharing between entities.

JOURNAL OF CLEANER PRODUCTION (2021)

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Article Energy & Fuels

Benefits of small-size communities for continuous cost-optimization in peer-to-peer energy sharing

Romaric Duvignau et al.

Summary: Investments in renewable electricity generation and storage have become more attractive due to lower costs, while peer-to-peer sharing offers a way to optimize financial benefits from distributed resources. Realistic data analysis showed that P2P energy sharing can achieve high fractions of ideal maximum gain without long forecast horizons, emphasizing the potential for small groups to reap financial benefits.

APPLIED ENERGY (2021)

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Article Computer Science, Interdisciplinary Applications

Energy aware scheduling in flexible flow shops with hybrid particle swarm optimization

Junwen Ding et al.

Summary: This paper investigates the integration of energy awareness in the flexible flow shop scheduling system, utilizing a hybrid particle swarm optimization algorithm to simultaneously minimize total tardiness and electric power costs. Experimental results demonstrate the significance of the HPSO algorithm in terms of the number and quality of non-dominated solutions and computational efficiency.

COMPUTERS & OPERATIONS RESEARCH (2021)

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Article Computer Science, Interdisciplinary Applications

Revenue optimization in energy networks involving self-scheduled demand and a smart grid

Sezin Afsar et al.

Summary: In this paper, a day-ahead pricing and load balancing problem is addressed in an environment involving self-scheduled users optimized via a smart grid. The model is formulated as a mixed integer bilevel program, and two heuristic algorithms are designed to provide high quality solutions in moderate computation time based on the problem structure.

COMPUTERS & OPERATIONS RESEARCH (2021)

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Article Thermodynamics

Coordinating shiftable loads for collective photovoltaic self-consumption: A multi-agent approach

G. Pontes Luz et al.

Summary: This study explores the scheduling of uninterruptible shiftable devices in collective photovoltaic self-consumption from a multiagent perspective, proposing both centralized and partially distributed approaches. Experimental results indicate that while the centralized method can find the optimal solution, it takes two orders of magnitude longer than the decentralized method, which, although has lower time cost, incurs higher monetary cost.

ENERGY (2021)

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Article Construction & Building Technology

A data-driven electric water heater scheduling and control system

Gulai Shen et al.

Summary: Domestic hot water heating accounts for 30% of household energy use, with electric water heaters being a potential renewable heating option. However, commercial electric water heaters lack the intelligence for optimization and predictive control, and research studies fail to incorporate real-time data for robust control in real-world settings.

ENERGY AND BUILDINGS (2021)

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Article Thermodynamics