Electricity–gas multi-agent planning method considering users’ comprehensive energy consumption behavior

Frontiers in Energy Research, Journal Year: 2024, Volume and Issue: 11

Published: Jan. 10, 2024

With the advent of energy Internet and swift growth unified systems, comprehensive demand users has gradually become a problem that cannot be ignored for planning integrated systems. Aiming at this problem, paper suggests multi-agent approach electricity gas, considering users’ holistic consumption behavior. First, utilizing combined subjective objective weighting method, study establishes utility model characteristics. The analysis behavior is conducted through an evolutionary game. On basis, revenue grid gas network investors formulated, game mechanism different analyzed. A dynamic electricity–gas proposed. Ultimately, resolved using iterative exploration approach. validity efficacy proposed method are confirmed simulation example.

Language: Английский

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Ultra-short-term wind power forecasting techniques: comparative analysis and future trends

Frontiers in Energy Research, Journal Year: 2024, Volume and Issue: 11

Published: Jan. 12, 2024

In recent years, the integration of wind power into grid has steadily increased, but volatility and uncertainty pose significant challenges to planning, scheduling operation. Ultra-short term forecasting technology as basis daily decision can accurately predict future hourly output, important research significance for ensuring safe stable operation grid. Although on ultra-short-term reached maturity, practical engineering applications still face several challenges. These include limited potential improving accuracy numerical weather forecasts, issue missing historical data from new farms, need achieve accurate prediction under extreme scenarios. Therefore, this paper aims critically review current proposed methods. On basis, analyze combined method scenarios, illustrate its effectiveness through farm case studies. Finally, according development trend demand systems, directions are proposed.

Language: Английский

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Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty

Sustainability, Journal Year: 2022, Volume and Issue: 14(17), P. 11002 - 11002

Published: Sept. 2, 2022

A large-scale renewable-based sustainable power system requires multifaced techno-economic optimization and energy penetration. Due to the volatile non-periodic nature of renewable energy, uncertainty renewables combined with load uncertainties significantly impacts operational efficiency integration. The complexities in balancing demand, generation, maintaining reliability have introduced new challenges current distribution system. Most associated can be effectively reduced by using a battery storage (BESS) right techniques for handling uncertainties. In this paper, distributionally robust (DRO) technique linear decision rule is formulated unit commitment (UC) framework optimal scheduling network that consists wind farm, solar PV, distributed generator (DG), BESS. To cut cost per unit, BESS plays an important role storing at off-peak time on-peak-time use relatively lower prices. For all-time minimum overall systems cost, size connected provide DGs. Three case studies are IEEE 14 bus (converted from MW kW match available market) solved proposed achieve maximum operating point capacity BESS, i.e., wind, hybrid. Each study has its own 30-min interval schedule DGs along comparison without impact on start-up shut down reported all dynamic economic dispatch results, including battery’s state-of-charge profile. handle allows economical sizing comparatively computational processing complexities.

Language: Английский

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Research on Power System Day-Ahead Generation Scheduling Method Considering Combined Operation of Wind Power and Pumped Storage Power Station

Sustainability, Journal Year: 2023, Volume and Issue: 15(7), P. 6208 - 6208

Published: April 4, 2023

In the proposed wind-storage combined operation technology, storage side is foreseen to play a significant role in power system day-ahead generation scheduling. Based on operational characteristics of pumped stations, dispatching method with wind farms and stations studied. The mode that aims at lowest operating cost proposed, taking into consideration coordination relationship between scheduling benefit total peak-shaving economy fluctuation new energy output. First, constraint reservoir capacity, output power, daily pumping station account, model constructed, objective minimizing costs. Then, imperial competition algorithm applied model. Finally, compared standard particle swarm optimization algorithm. simulation results based 4-unit 10-unit systems indicate effective robust for stations.

Language: Английский

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Multistep Wind Power Prediction Using Time-Varying Filtered Empirical Modal Decomposition and Improved Adaptive Sparrow Search Algorithm-Optimized Phase Space Reconstruction–Echo State Network

Sustainability, Journal Year: 2023, Volume and Issue: 15(11), P. 9107 - 9107

Published: June 5, 2023

Accurate wind power prediction is vital for improving grid stability. In order to improve the accuracy of prediction, in this study, a hybrid model combining time-varying filtered empirical modal decomposition (TVFEMD), improved adaptive sparrow search algorithm (IASSA)-optimized phase space reconstruction (PSR) and echo state network (ESN) methods was proposed. First, data were decomposed into set subsequences by using TVFEMD. Next, PSR used construct corresponding matrix sequences, which then divided training sets, validation testing sets. Then, ESN subsequence prediction. Finally, predicted values all subseries determine final power. To enhance performance, terms discoverer position update strategy, follower population structure. IASSA employed synchronously optimize multiple parameters PSR-ESN. The results revealed that proposed has higher applicability than existing models.

Language: Английский

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