Data-driven two-stage robust optimization dispatching model and benefit allocation strategy for a novel virtual power plant considering carbon-green certificate equivalence conversion mechanism

Applied Energy, Journal Year: 2024, Volume and Issue: 362, P. 122974 - 122974

Published: March 16, 2024

Language: Английский

---

Multi-objective battery energy storage optimization for virtual power plant applications

Applied Energy, Journal Year: 2023, Volume and Issue: 352, P. 121860 - 121860

Published: Sept. 16, 2023

The increasing share of renewable energy sources (RESs) in electricity generation leads to increased uncertainty generation, frequency and voltage regulation as well difficulties management. A virtual power plant (VPP), a combination dispersed generator units, controllable load storage system (ESS), provides an efficient solution for management scheduling, so reduce the cost network impact caused by spikes. This paper proposes multi-objective optimization (MOO) battery (BESS) VPP applications. low-voltage (LV) Alice Springs (Northern Territory, Australia) is considered test this study. BESS each customer used store release when required maintain performance LV cost. To optimize charge/discharge schedule battery, tool (MOOT) developed, where MOO can directly communicate with DIgSILENT PowerFactory platform perform multi-time scale simulation. mainly focuses on generating set trade-off solutions over 24 h considering customer's impact. Then according stakeholder's prior preference, one selected verified realistic network. We also design several scenarios different penetrations photovoltaics (PVs) batteries verify how they influence With PVs batteries, experimental results preference show that customers' be largely reduced maintaining performance.

Language: Английский

---

Comparative assessment of multi-objective optimization of hybrid energy storage system considering grid balancing

Renewable Energy, Journal Year: 2023, Volume and Issue: 216, P. 119107 - 119107

Published: Aug. 2, 2023

Language: Английский

---

A low-carbon economic dispatch method for regional integrated energy system based on multi-objective chaotic artificial hummingbird algorithm

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 19, 2024

Abstract This paper investigates Regional Integrated Energy Systems (RIES), emphasizing the connection of diverse energy supply subsystems to address varied user needs and enhance operational efficiency. A novel low-carbon economic dispatch method, utilizing multi-objective chaotic artificial hummingbird algorithm, is introduced. The method not only optimizes environmental benefits but also aligns with "carbon peak carbon neutrality" objectives. study begins by presenting a comprehensive model, followed proposal crucial for deriving Pareto frontier model. Additionally, we introduce TOPSIS approach based on combined subjective objective weights, this harnesses data from solution set deftly, curbs biases dispatchers effectively facilitates selection an optimal system operation plan frontier. Finally, simulation results highlight outstanding performance our in terms optimization outcomes, convergence efficiency, diversity. Noteworthy among these 8.8% decrease costs 14.2% reduction emissions.

Language: Английский

---

Bi-level programming optimization method of rural integrated energy system based on coupling coordination degree of energy equipment

Energy, Journal Year: 2024, Volume and Issue: 298, P. 131289 - 131289

Published: April 17, 2024

Language: Английский

---

Assessing carbon emission reduction benefits of the electrification transition of agricultural machinery for sustainable development: A case study in China

Sustainable Energy Technologies and Assessments, Journal Year: 2024, Volume and Issue: 63, P. 103634 - 103634

Published: Jan. 19, 2024

Language: Английский

---

NSGA-II based short-term building energy management using optimal LSTM-MLP forecasts

International Journal of Electrical Power & Energy Systems, Journal Year: 2024, Volume and Issue: 159, P. 110070 - 110070

Published: June 3, 2024

To conduct analysis on the field of electricity management in buildings is crucial to contribute clean energy promotion, efficiency, and resilience against climate change. This manuscript proposes a methodology for modeling predictive calibrated system (EMS) using hybrid that combines long short-term memory multilayer perceptron models (LSTM-MLP) optimized by non-dominated sorting genetic algorithm II (NSGA-II). The proposed approach utilizes global forecast (GFS) data anticipate consumption fluctuations optimize use distributed sources, such as photovoltaic (PV) production, based knowledge prices free market one day ahead. trade-off building conducted with NSGA-II, guaranteeing exploration exploitation while minimizing costs wastes. research carried out demonstrates effectiveness LSTM-MLP model advantages NSGA-II hyperparameter tuning balance sustainable practices. tested an existing building, Industrial Engineering School located Campus Lagoas-Marcosende Universidade de Vigo, Spain.

Language: Английский

---

Mismatch analysis of rooftop photovoltaics supply and farmhouse load: Data dimensionality reduction and explicable load pattern mining via hybrid deep learning

Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124520 - 124520

Published: Sept. 21, 2024

Language: Английский

---

Balancing stakeholder benefits: A many-objective optimal dispatch framework for home energy systems inspired by Maslow's Hierarchy of needs

Advances in Applied Energy, Journal Year: 2023, Volume and Issue: 13, P. 100160 - 100160

Published: Dec. 21, 2023

The optimal scheduling of home energy systems is influenced by the benefits different stakeholders, with hierarchical nature user's needs being particularly significant. However, previous studies have largely neglected these factors. To bridge research gaps, a many-objective dispatch framework for systems, which was inspired Maslow's hierarchy needs, proposed. In framework, were categorized into various hierarchies referring to theory, fulfilled in specific sequence during optimization. addition grid operators and policymakers considered developed nonlinear model, includes six objective functions that capture interests end-users, operators, policymakers. Simulation results obtained across configurations verified effectiveness proposed framework. Results indicate can be fully satisfied tradeoff among achieved. For demonstrated reductions 22.33%-81.05% daily operation costs, 14.39%-25.68% CO2 emissions, 15.58%-17.49% peak-valley differences, associated increment 5.37%-15.51% self-consumption rate 8.91%-27.29% self-sufficiency rate, compared benchmark. provides valuable guidance practical applications.

Language: Английский

---

A Novel Statistical Framework for Optimal Sizing of Grid-Connected Photovoltaic–Battery Systems for Peak Demand Reduction to Flatten Daily Load Profiles

Solar, Journal Year: 2024, Volume and Issue: 4(1), P. 179 - 208

Published: March 14, 2024

Integrating photovoltaic (PV) systems plays a pivotal role in the global shift toward renewable energy, offering significant environmental benefits. However, PV installation should provide financial benefits for utilities. Considering that utility companies often incur costs both energy and peak demand, installations aim to reduce demand charges. Although can needs during day, their effectiveness reducing particularly early morning late evening, is limited, as generation zero or negligible at those times. To address this limitation, battery storage are utilized storing off-peak hours releasing it finding optimal size of accompanying remains challenge. While valuable optimization models have been developed determine PV–battery systems, certain gap where reduction has not sufficiently addressed process. Recognizing gap, study proposes novel statistical model optimize system reduction. The aims flatten 95% daily demands up threshold, ensuring consistent supply benefit companies. A straightforward effective search methodology employed sizes. Additionally, model’s rigorously tested through modified Monte Carlo simulation coupled with time series clustering generate various scenarios assess performance under different conditions. results indicate successfully flattens selected threshold 2000 kW, yielding USD 812,648 over 20 years.

Language: Английский

---