Data-driven optimal scheduling for integrated electricity-heat-gas-hydrogen energy system considering demand-side management: A deep reinforcement learning approach

International Journal of Hydrogen Energy, Год журнала: 2025, Номер 103, С. 147 - 165

Опубликована: Янв. 17, 2025

Язык: Английский

---

Data based digital twin for operational performance optimization in CFB Boilers

Energy, Год журнала: 2024, Номер 306, С. 132532 - 132532

Опубликована: Окт. 1, 2024

Язык: Английский

---

Scenario-Based Stochastic Optimization on the Variability of Solar and Wind for Component Sizing of Integrated Energy Systems

Renewable Energy, Год журнала: 2024, Номер 237, С. 121543 - 121543

Опубликована: Окт. 5, 2024

Язык: Английский

---

Multi-stage cooperative planning among shared energy storage operator and multiple prosumers in regional integrated energy system considering long-term uncertainty

Journal of Energy Storage, Год журнала: 2024, Номер 103, С. 114244 - 114244

Опубликована: Окт. 23, 2024

Язык: Английский

---

A novel multi-objective optimization approach for resilience enhancement considering integrated energy systems with renewable energy, energy storage, energy sharing, and demand-side management

Journal of Energy Storage, Год журнала: 2025, Номер 115, С. 115966 - 115966

Опубликована: Март 1, 2025

Язык: Английский

---

Multi-timescale rolling optimization strategy for integrated energy systems considering renewable energy consumption and source–load uncertainty

Journal of Renewable and Sustainable Energy, Год журнала: 2025, Номер 17(3)

Опубликована: Май 1, 2025

Integrated energy systems enhance renewable consumption and supply efficiency through optimized scheduling of production, conversion, storage. This paper introduces a day-ahead stochastic-intraday robust two-phase multi-timescale rolling optimal model that addresses source–load uncertainty, improving utilization reducing operational costs. In the phase, builds on traditional Monte Carlo simulation by updating discrete probability density matrix based temporal characteristics data. It employs adaptive for generating source load scenarios. Additionally, an improved k-means algorithm, utilizing elbow method considering triangular inequality Euclidean distances, enhances scene analysis accuracy. intraday incorporates slack variables constraint sets, integrating them with cardinality uncertain scenario set light optimization model. approach reduces conservatism typically associated (RO) models. The proposed RO facilitates efficient balanced across various timescales. Overall, findings demonstrate leverages multi-energy complementarities to optimize ensure in dynamic environment.

Язык: Английский

---

Multi-objective dispatch of integrated renewable power systems leveraging robust optimization in deep reinforcement learning

Computers & Chemical Engineering, Год журнала: 2025, Номер unknown, С. 109173 - 109173

Опубликована: Май 1, 2025

Язык: Английский

---

RETRACTED:Optimum planning of energy hub with participation in electricity market and heat markets and application of integrated load response program with improved particle swarm algorithm

Energy, Год журнала: 2023, Номер 286, С. 129587 - 129587

Опубликована: Ноя. 4, 2023

Язык: Английский

---

Methodology to compare and optimize district heating and decentralized heat supply for energy transformation on a municipality level

Energy, Год журнала: 2023, Номер 282, С. 128987 - 128987

Опубликована: Сен. 5, 2023

Язык: Английский

---

Configuration Strategy and Performance Analysis of Combined Heat and Power System Integrated with Biomass Gasification, Solid Oxide Fuel Cell, and Steam Power System

Processes, Год журнала: 2024, Номер 12(3), С. 446 - 446

Опубликована: Фев. 22, 2024

Renewable energy integration is a crucial approach for achieving low-carbon supply in industrial utility systems. However, the uncertainty of user demand often leads to mismatch between system’s real operating conditions and optimal points, resulting wastage high emissions. This study presents multi-source heat power system that integrates biomass gasification, solar collecting, solid oxide fuel cell (SOFC), gas turbine, steam A scheduling strategy varies heat-to-power ratio proposed accommodate changes requirements. simulation model this established validated. The influence three key parameters on performance under different configurations explored. Energy economic evaluations are conducted configurations, production adjustable range determined. analysis reveals that, configuration, can achieve an efficiency 64.51%, it economically feasible with levelized cost electricity (LCOE) USD 0.16/kWh. capable producing output ranging from 11.52 355.53 MW by implementing configuration strategies. be adjusted 0.91 28.09.

Язык: Английский

---