Optimal Sizing and Analysis of Solar PV, Wind, and Energy Storage Hybrid System for Campus Microgrid

Considering the increasing penetration of variable and non-dispatchable renewable energy in worldwide electricity mixes, an increasing requirement for energy storage capacity is foreseen in order to decouple production and demand. Electrochemical battery systems and/or hydrogen systems (electrolysers and fuel cells) provide a suitable alternative to be implemented in local small-to-medium scale microgrid environments. The research aims to address the optimal sizing of an Energy Storage System composed of lead acid batteries and a hydrogen loop (electrolyser, compressed storage tank and fuel cell) within an actual hybrid renewable microgrid located in Huelva, Spain. The energy storage systems must couple the variable production of 15 kWp of solar PV systems and a 3 kWnom horizontal axis wind turbine to a real monitored residential load, which present a time-shifted power demand. By making use of previously developed and validated component models, three storage configurations (battery-only, hydrogen-only and hybrid batteryhydrogen) are assessed via parametrical variation in yearly simulations in hourly timestep, analysing the Loss of Load (LL) and Over Production (OP) output values. The results provide quantitative information regarding the optimal storage system capacity in each configuration providing valuable insight in terms of sizing of the energy storage systems in the long-term.

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Implementation of Analytical Method and Improved Particle Swarm Optimization Method for Optimal Sizing of a Standalone PV/Wind and Battery Energy Storage Hybrid System

2019 IEEE 5th International Conference for Convergence in Technology (I2CT) ◽

10.1109/i2ct45611.2019.9033540 ◽

2019 ◽

Author(s):

Gauri M. Karve ◽

Kalyani M. Kurundkar ◽

Geetanjali A. Vaidya

Keyword(s):

Particle Swarm Optimization ◽

Energy Storage ◽

Hybrid System ◽

Analytical Method ◽

Optimization Method ◽

Swarm Optimization ◽

Battery Energy Storage ◽

Optimal Sizing ◽

Improved Particle Swarm Optimization ◽

Battery Energy

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Sensorless Fuzzy MPPT Technique of Solar PV and DFIG Based Wind Hybrid System

International Review on Modelling and Simulations (IREMOS) ◽

10.15866/iremos.v10i3.11361 ◽

2017 ◽

Vol 10 (3) ◽

pp. 152

Author(s):

Marouane El Azzaoui ◽

Hassane Mahmoudi ◽

Karima Boudaraia

Keyword(s):

Hybrid System ◽

Solar Pv

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Price and subsidy under uncertainty: Real-option approach to optimal investment decisions on energy storage with solar PV

Energy & Environment ◽

10.1177/0958305x21992291 ◽

2021 ◽

pp. 0958305X2199229

Author(s):

Jingyu Qu ◽

Wooyoung Jeon

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Real Option ◽

Financial Burden ◽

Investment Decisions ◽

Optimal Investment ◽

Investment Incentives ◽

Solar Pv ◽

Increased Risk ◽

Trigger Price

Renewable generation sources still have not achieved economic validity in many countries including Korea, and require subsidies to support the transition to a low-carbon economy. An initial Feed-In Tariff (FIT) was adopted to support the deployment of renewable energy in Korea until 2011 and then was switched to the Renewable Portfolio Standard (RPS) to implement more market-oriented mechanisms. However, high volatilities in electricity prices and subsidies under the RPS scheme have weakened investment incentives. In this study we estimate how the multiple price volatilities under the RPS scheme affect the optimal investment decisions of energy storage projects, whose importance is increasing rapidly because they can mitigate the variability and uncertainty of solar and wind generation in the power system. We applied mathematical analysis based on real-option methods to estimate the optimal trigger price for investment in energy-storage projects with and without multiple price volatilities. We found that the optimal trigger price of subsidy called the Renewable Energy Certificate (REC) under multiple price volatilities is 10.5% higher than that under no price volatilities. If the volatility of the REC price gets doubled, the project requires a 26.6% higher optimal investment price to justify the investment against the increased risk. In the end, we propose an auction scheme that has the advantage of both RPS and FIT in order to minimize the financial burden of the subsidy program by eliminating subsidy volatility and find the minimum willingness-to-accept price for investors.

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