Optimal Capacity Allocation of Large-Scale Wind-PV-Battery Hybrid System

2015 ◽  
Author(s):  
Li Wei ◽  
Zhang Weijia ◽  
Pang Jin ◽  
Niu Qian
Keyword(s):  
Hybrid System ◽  
Large Scale ◽  
Capacity Allocation ◽  
Optimal Capacity

scholarly journals Optimal Capacity Allocation of Large-Scale Wind-PV-Battery Units

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Kehe Wu ◽  
Huan Zhou ◽  
Jizhen Liu
Keyword(s):  
Power Generation ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Hybrid Genetic Algorithm ◽  
Capacity Allocation ◽  
Government Support ◽  
Utilization Rate ◽  
Full Life Cycle ◽  
Optimal Capacity ◽  
Generation Unit

An optimal capacity allocation of large-scale wind-photovoltaic- (PV-) battery units was proposed. First, an output power model was established according to meteorological conditions. Then, a wind-PV-battery unit was connected to the power grid as a power-generation unit with a rated capacity under a fixed coordinated operation strategy. Second, the utilization rate of renewable energy sources and maximum wind-PV complementation was considered and the objective function of full life cycle-net present cost (NPC) was calculated through hybrid iteration/adaptive hybrid genetic algorithm (HIAGA). The optimal capacity ratio among wind generator, PV array, and battery device also was calculated simultaneously. A simulation was conducted based on the wind-PV-battery unit in Zhangbei, China. Results showed that a wind-PV-battery unit could effectively minimize the NPC of power-generation units under a stable grid-connected operation. Finally, the sensitivity analysis of the wind-PV-battery unit demonstrated that the optimization result was closely related to potential wind-solar resources and government support. Regions with rich wind resources and a reasonable government energy policy could improve the economic efficiency of their power-generation units.

scholarly journals Optimal Capacity Allocation of Energy Storage in Distribution Networks Considering Active/Reactive Coordination

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1611
Author(s):  
Tao Xu ◽  
He Meng ◽  
Jie Zhu ◽  
Wei Wei ◽  
He Zhao ◽  
...  
Keyword(s):  
Energy Storage ◽  
Life Cycle Cost ◽  
Large Scale ◽  
Reactive Power ◽  
Supply And Demand ◽  
Distribution Networks ◽  
Capacity Allocation ◽  
Mixed Integer ◽  
Optimal Capacity ◽  
Network Losses

Energy storage system (ESS) has been advocated as one of the key elements for the future energy system by the fast power regulation and energy transfer capabilities. In particular, for distribution networks with high penetration of renewables, ESS plays an important role in bridging the gap between the supply and demand, maximizing the benefits of renewables and providing various types of ancillary services to cope the intermittences and fluctuations, consequently improving the resilience, reliability and flexibility. To solve the voltage fluctuations caused by the high permeability of renewables in distribution networks, an optimal capacity allocation strategy of ESS is proposed in this paper. Taking the life cycle cost, arbitrage income and the benefit of reducing network losses into consideration, a bilevel optimization model of ESS capacity allocation is established, the coordination between active/reactive power of associate power conversion system is considered, and the large scale nonlinear programming problem is solved using genetic algorithm, simulated annealing and mixed integer second-order cone programming method. The feasibility and effectiveness of the proposed algorithm have been verified.

scholarly journals Modeling and Coordinated Control Strategy of Large Scale Grid-Connected Wind/Photovoltaic/Energy Storage Hybrid Energy Conversion System

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Lingguo Kong ◽  
Guowei Cai ◽  
Sidney Xue ◽  
Shaohua Li
Keyword(s):  
Energy Storage ◽  
Energy Conversion ◽  
Hybrid System ◽  
Control Strategy ◽  
Large Scale ◽  
Coordinated Control ◽  
Hybrid Energy ◽  
Conversion System ◽  
Energy Conversion System ◽  
Continuous Power

An AC-linked large scale wind/photovoltaic (PV)/energy storage (ES) hybrid energy conversion system for grid-connected application was proposed in this paper. Wind energy conversion system (WECS) and PV generation system are the primary power sources of the hybrid system. The ES system, including battery and fuel cell (FC), is used as a backup and a power regulation unit to ensure continuous power supply and to take care of the intermittent nature of wind and photovoltaic resources. Static synchronous compensator (STATCOM) is employed to support the AC-linked bus voltage and improve low voltage ride through (LVRT) capability of the proposed system. An overall power coordinated control strategy is designed to manage real-power and reactive-power flows among the different energy sources, the storage unit, and the STATCOM system in the hybrid system. A simulation case study carried out on Western System Coordinating Council (WSCC) 3-machine 9-bus test system for the large scale hybrid energy conversion system has been developed using the DIgSILENT/Power Factory software platform. The hybrid system performance under different scenarios has been verified by simulation studies using practical load demand profiles and real weather data.

scholarly journals A Nonlinear Model For The Optimal Capacity Placement In Self-Healing ATM Networks Based On Link Restoration Strategy

2021 ◽  
Author(s):  
ABM B. Alam
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Performance Metrics ◽  
Asynchronous Transfer Mode ◽  
Critical Issue ◽  
Self Healing ◽  
Network Failure ◽  
Optimal Capacity ◽  
Telecommunications Network ◽  
Important Challenge

Network Survivability is a critical issue in telecommunications network due to increasing dependence of the society on communication systems. Fast restoration from a network failure is an important challenge that deserves attention. This thesis addresses an optimal link capacity design problem for survivable asynchronous transfer mode (ATM) network based on the link restoration strategy. Given a projected traffic demands and the network topology, capacity and flow assignment are jointly optimized to yield the optimal capacity placement. The problem is formulated as large-scale nonlinear programming and is solved using a specific type of Lagrange method (so called Separable Augmented Lagrangian Algorithm or SALA for short). Several networks with diverse topological characteristics are used in the experiments to validate our proposed novel model, using capacity installation cost, routing cost, total network cost, used capacity and required CPU time, as performance metrics. Link restoration strategy is compared against global reconfiguration strategy using these performance metrics.

scholarly journals Optimising the balance of acute and intermediate care capacity for the complex discharge pathway: computer modelling study during COVID-19 recovery in England

2021 ◽  
Author(s):  
Zehra Onen Dumlu ◽  
Alison L Harper ◽  
Paul G Forte ◽  
Anna L Powell ◽  
Martin Pitt ◽  
...  
Keyword(s):  
Computer Modelling ◽  
Care Pathway ◽  
Capacity Allocation ◽  
Community Services ◽  
System Level ◽  
Computer Simulation Model ◽  
Intermediate Care ◽  
Care Services ◽  
Optimal Capacity ◽  
Care Capacity

Objectives: While there has been significant research on the pressures facing acute hospitals during the COVID-19 pandemic, there has been less interest in downstream community services which have also been challenged in meeting demand. This study aimed to estimate the theoretical cost-optimal capacity requirement for 'step down' intermediate care services within a major healthcare system in England, at a time when considerable uncertainty remained regarding vaccination uptake and the easing of societal restrictions. Methods: Demand for intermediate care was projected using an epidemiological model (for COVID-19 demand) and regressing upon public mobility (for non-COVID-19 demand). These were inputted to a computer simulation model of patient flow from acute discharge readiness to bedded and home-based Discharge to Assess (D2A) intermediate care services. Cost-optimal capacity was defined as that which yielded the lowest total cost of intermediate care provision and corresponding acute discharge delays. Results: Increased intermediate care capacity is likely to bring about lower system-level costs, with the additional D2A investment more than offset by substantial reductions in costly acute discharge delays (leading also to improved patient outcome and experience). Results suggest that completely eliminating acute 'bed blocking' is unlikely economical (requiring large amounts of downstream capacity), and that health systems should instead target an appropriate tolerance based upon the specific characteristics of the pathway. Conclusions: Computer modelling can be a valuable asset for determining optimal capacity allocation along the complex care pathway. With results supporting a Business Case for increased downstream capacity, this study demonstrates how modelling can be applied in practice and provides a blueprint for use alongside the freely-available model code.

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