Research on Dynamic Adjustment of Enterprise Resource Integration and Strategic Management Based on Cloud Computing Optimization DOI Open Access
Geng Wang

Applied Mathematics and Nonlinear Sciences, Год журнала: 2024, Номер 9(1)

Опубликована: Янв. 1, 2024

Abstract The extent to which modern enterprises utilize their resources significantly influences strategy formulation and even raises questions about ability remain competitive in the market. This paper finds best way use traditional enterprise by using cloud computing. It does this creating a multi-objective scheduling model combine stochastic-aware real-time task make most of combined raise utilization rate. Based on dynamically changing resource information, strategic integration is constructed based dynamic view adjust development real-time. Company A, an automobile production enterprise, has been selected conduct example study examine its management effect after experiencing computing optimization. deployment time increased optimization, enhancing efficiency deployment. In small-scale workflow, rate achieves 50% improvement, while large-scale exceeds 40%. Compared financial status A before solvency, operating capacity, profitability have improved adjustment. satisfaction scores A’s team five dimensions quality integration, deployment, speed response market feedback, familiarity with market, reasonableness are all above 4, indicating promising results management.

Язык: Английский

A Novel Method to Integrate Hydropower Plants into Resource Adequacy Assessment Studies DOI Creative Commons

Christiana I. Kostaki,

Pantelis A. Dratsas, Georgios N. Psarros

и другие.

Energies, Год журнала: 2024, Номер 17(17), С. 4237 - 4237

Опубликована: Авг. 24, 2024

This paper presents a novel methodology for modeling hydropower plants (HPPs) with and without pumping capability in resource adequacy assessment studies. The proposed method is based on the premise that HPPs should maximize their contribution to system within technical constraints by using energy reserves upper reservoirs significantly deviating from market schedule. approach of this differs conventional operating policies incorporating into studies, which either adhere fixed schedule or perform peak shaving, are inelastic real-time events do not resort realistic temporal correlations between natural water inflows discharge needs cover demand peaks, respectively. focuses large-reservoir generic enough deal both stations capabilities those without. It utilizes state-of-the-art Monte Carlo simulation technique form availability assets determine loss load incidents. level reservoir fulfillment retrieved cost-optimal power algorithm executed offline before application assessment. effectiveness demonstrated through its implementation case study experiencing different levels adequacy, comparing obtained results various traditional HPP methods literature.

Язык: Английский

Процитировано

1

Hydropneumatic Storage Methodology Towards a New Era of Hybrid Energy System's Efficiency and Flexibility DOI Creative Commons

João Coelho,

Modesto Pérez‐Sánchez, Óscar E. Coronado-Hernández

и другие.

Results in Engineering, Год журнала: 2024, Номер 24, С. 103117 - 103117

Опубликована: Окт. 12, 2024

Язык: Английский

Процитировано

0

Research on Dynamic Adjustment of Enterprise Resource Integration and Strategic Management Based on Cloud Computing Optimization DOI Open Access
Geng Wang

Applied Mathematics and Nonlinear Sciences, Год журнала: 2024, Номер 9(1)

Опубликована: Янв. 1, 2024

Abstract The extent to which modern enterprises utilize their resources significantly influences strategy formulation and even raises questions about ability remain competitive in the market. This paper finds best way use traditional enterprise by using cloud computing. It does this creating a multi-objective scheduling model combine stochastic-aware real-time task make most of combined raise utilization rate. Based on dynamically changing resource information, strategic integration is constructed based dynamic view adjust development real-time. Company A, an automobile production enterprise, has been selected conduct example study examine its management effect after experiencing computing optimization. deployment time increased optimization, enhancing efficiency deployment. In small-scale workflow, rate achieves 50% improvement, while large-scale exceeds 40%. Compared financial status A before solvency, operating capacity, profitability have improved adjustment. satisfaction scores A’s team five dimensions quality integration, deployment, speed response market feedback, familiarity with market, reasonableness are all above 4, indicating promising results management.

Язык: Английский

Процитировано

0