Abstract

Western China has good conditions for constructing large-scale photovoltaic (PV) power stations; however, such power plants with large fluctuations and strong randomness suffer from the long-distance power transmission problem, which needs to be solved. For large-scale PV power stations that do not have the conditions for simultaneous hydropower and PV power, this study examined long-distance delivery mode and energy storage optimization. The objective was to realize the long-distance transmission of electrical energy and maximize the economic value of the energy storage and PV power storage. For a large-scale PV power station, the energy storage optimization was modelled under a given long-distance delivery mode, and the economic evaluation system quantified using the net present value (NPV) of the battery was based on the energy dispatch optimization model. By contrast, a lithium battery performance model was developed. Therefore, further analysis of the economics of the energy storage and obtaining the best capacity of the energy storage battery and corresponding replacement cycle considered battery degradation. The case study of Qinghai Gonghe 100 MWp demonstration base PV power station showed that the optimal energy storage capacity was 5 MWh, and the optimal replacement period was 2 years. Therefore, the annual abandoned electricity was reduced by 3.051 × 10 4 MWh compared with no energy storage. The utilization rate of both the PV power station and quality of the delivered electricity were modelled to realize a long-distance transmission to the grid net. This will have an important guiding significance to develop and construct large-scale single PV power stations.

Highlights

  • With the shortage of chemical resources and the increasingly serious environmental pollution, the development and efficient utilization of renewable energy sources, represented by solar energy, have gained attention worldwide [1,2,3,4,5,6]

  • I=1 In Equation (9), ND indicates the maximum number of cycles allowed for the actual capacity of the energy storage battery corresponding to its discharge depth remaining between 60% and 100% of the nominal capacity within a certain charge and discharge interval

  • For a large-scale PV power station under given long-distance delivery mode, the storage batteries of different capacities are different in both cycles and depths of charge and discharge during operations, which results in different life cycles of energy storage batteries with different storage capacities

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Summary

Introduction

With the shortage of chemical resources and the increasingly serious environmental pollution, the development and efficient utilization of renewable energy sources, represented by solar energy, have gained attention worldwide [1,2,3,4,5,6]. With the rapid development of meteorology conditions, the PV power output inevitably exhibits intermittent, volatile, and strong some large-scale centralized PV power stations have been constructed to fully utilize the solar energy technology, the cost of batteries has shown a trend of rapid decline. Ensuring and the characteristics of the the power solar energy in China, a mode development cost of batteries, energy storage will become an effective measure to realize grid connection of power satisfies the quality demand of UHV transmission undertransmission”. Study.ToTo realize long-distance grid connection of large-scale power stations while the benefits, the benefits, aim of the to develop capacity optimization that maximizing theresearch aim of was the research wasa storage to develop a storage capacity method optimization considers three factors, including technology, economy, and economy, energy storage battery storage characteristics. Reference applications for the development of large-scale PV power stations

Long-Distance Delivery Mode
Energy Storage Optimization Model
Energy
1) Objective function
Energy Dispatch Optimization Model
(1) Objective function
Lithium Battery Performance Model
Economic Evaluation System
Energy Dispatch Optimization Model Output
Optimal Energy Storage Capacity
Battery Attenuation Variation Law and Replacement Cycle
Conclusions
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