Electric Vehicle Battery - Wind Energy Storage System

The proposed concept utilizes the EV battery waste stream as a means to store wind energy in order to increase wind energy capacity factor, improve utilization, and make more efficient use of EV batteries prior to recycling. Michigan is an ideal location for such a facility because many of the battery and automotive manufacturers are located here. A 200 MW wind farm can charge a battery farm which consists of all reject and post-consumer batteries and all EVs located in Michigan by 2015. Michigan is on track to meet a 10% renewable portfolio by 2015 with over 1100 MW of planned new wind projects to be installed by then. Therefore, Michigan has plenty of wind capacity to charge the EV battery wind-storage facility and all of Michigan consumer EVs

Applying wind turbines and battery storage to defer Orcas Power and Light Company distribution circuit upgrades

The purpose of this study is to conduct a detailed assessment of the Orcas Power and Light Company (OPALCO) system to determine the potential for deferring the costly upgrade of the 25-kV Lopez- Eastsound circuit, by the application of a MW-scale wind farm and battery storage facilities as appropriate. Local wind resource data has been collected over the past year and used to determine MW-scale wind farm performance. This hourly wind farm performance data is used with measured hourly Eastsound load data, and recent OPALCO distribution system expansion plans and cost projections in performing this detailed benefit-cost assessment. The OPALCO distribution circuit expansion project and assumptions are described. MW-scale wind farm performance results are given. The economic benefit-cost results for the wind farm and battery storage applications on the OPALCO system using OPALCO system design criteria and cost assumptions are reported. A recalculation is presented of the benefit-cost results for similar potential wind farm and battery storage applications on other utility systems with higher marginal energy and demand costs. Conclusions and recommendations are presented

The Effects of Battery Storage on Risk and Cost of Capital of Wind Park Investments

To reach the defined reduction goals for green house gas emissions, an increasing share of renewables and especially wind power is necessary. However, these generation technologies are intermittent and progressively exposed to market risks as a consequence of declining financial support in the future. To reduce revenue volatility, in this thesis, a wind farm is combined with a battery storage. The study emphasizes the battery’s effect on the investment risk and the accompanying cost of capital. In order to assess this effect, I develop a deterministic optimization model based on historic wind farm and market price data in order to maximize cash flows. Monte Carlo scenarios are generated to evaluate the impact on risk by using the Value-at-Risk as risk criterion. I find that batteries can indeed reduce revenue risk in a case without subsidies. Furthermore, the link to cost of capital is made. The latter, as well as the battery prices, need to be reduced by a certain amount to make the application of a battery economically reasonable. To reach the defined reduction goals for green house gas emissions, an increasing share of renewables and especially wind power is necessary. However, these generation technologies are intermittent and progressively exposed to market risks as a consequence of declining financial support in the future. To reduce revenue volatility, in this thesis, a wind farm is combined with a battery storage. The study emphasizes the battery’s effect on the investment risk and the accompanying cost of capital. In order to assess this effect, I develop a deterministic optimization model based on historic wind farm and market price data in order to maximize cash flows. Monte Carlo scenarios are generated to evaluate the impact on risk by using the Value-at-Risk as risk criterion. I find that batteries can indeed reduce revenue risk in a case without subsidies. Furthermore, the link to cost of capital is made. The latter, as well as the battery prices, need to be reduced by a certain amount to make the application of a battery economically reasonable.  Keywords: Renewable energy, Energy markets, Battery storage, Wind investment, Energy investment ris

Techno-Economic Assessment of Offshore Wind and Hybrid Wind-Wave Farms with Energy Storage Systems

Ocean renewables (such as offshore wind and wave) are abundant and essential energy resources for supporting future emission-free targets. However, their energy intermittency and high cost have hindered commercialization and wide-scale implementations of these ocean energy technologies. This paper focuses on both issues and aims to increase the dispatchability of ocean energy farm, by investigating the potential of a hybrid wind and wave energy platform with various energy storage systems (ESSs). In the paper, a novel method is proposed to assess the ESS for an offshore renewable energy farm to guarantee the energy dispatchability to the local demand. The effect of two farm configurations on the ESS capacity is analysed: one involves wind turbines only and the other one uses a hybrid configuration (with wind and wave generation subsystems). Lifecycle cost models of energy farms are developed and the economic feasibility of different energy storage systems are investigated. The sensitivity of energy farm configurations and the energy storage systems to the resource characteristics at multiple locations are also studied. The results indicate that the combined wind and wave energy farm significantly reduces the energy storage system capacity requirement and provides competitive lifecycle costs compared to the stand-alone wind energy farm, though the amount of these benefits vary on the local resource characteristics. In addition, it was concluded that the Lithium-ion battery option in a combined energy farm offers better overall performance over the other storage options considered

Battery Storage System for Frequency Stabilization of AC Networks with High Penetration of Renewable Power

This paper investigates the uses of battery energy storage system (BESS) in ac networks highly populated with wind power generation. The investigation includes power system load levelling, frequency stabilization, and provision of reactive power support to the wind farm network. The BESS is connected to the wind farm main hub via voltage source converter, while the wind farm is connected to ac network modelled with detailed synchronous generator, including excitation and turbine-governor control. In general the paper attempted to study the role of BESS in modern power system regarding improving system stability. Time-domain simulations conducted in Matlab/Simulink are used to validate the importance of the BESS

Modeling and Utilizing a Vanadium Redox Flow Battery for Easier Grid and Market Integration of Wind Power

Power grid and market integration of wind energy is a challenge due to the fluctuating and intermittent power output resulting from the variable nature of wind resource. Energy storage is a promising alternative for effective grid integration of renewable energy. One storage technology which is under the spotlight in the recent years is the vanadium redox flow battery (VRFB) which could have certain advantages when utilized at large-scale grid connected applications. In this study, a megawatt scale VRFB was modeled based on experimental data with a kilowatt scale real life unit. The dependence of the overall system efficiency on the state of charge and power was determined. By using the model, optimal number of modules for certain power levels during charging and discharging operations were estimated for megawatt scale operations. In order to evaluate the power grid integration of wind power at a single wind farm level, a second simulation model which combines the megawatt scale VRFB model and a medium sized (10 MW) wind farm was developed and the battery was utilized to compensate for the deviations resulting from the forecast errors in an electricity market bidding structure. Using an existing electricity market model based on deviation penalties and penalty multipliers, economics of the system were evaluated by determining the payback periods for a dedicated VRFB installation at this medium sized, single wind farm level

Impact Of Wind Farms With Energy Storage On Transient Stability

Today’s energy infrastructure will need to rapidly expand in terms of reliability and flexibility due to aging infrastructure, changing energy market conditions, projected load increases, and system reliability requirements. Over the few decades, several states in the U.S. are now requiring an increase in wind penetration. These requirements will have impacts on grid reliability given the inherent intermittency of wind generation and much research has been completed on the impact of wind on grid reliability. Energy storage has been proposed as a tool to provide greater levels of reliability; however, little research has occurred in the area of wind with storage and its impact on stability given different possible scenarios. This thesis addresses the impact of wind farm penetration on transient stability when energy storage is added. The results show that battery energy storage located at the wind energy site can improve the stability response of the system

The Modeling and Advanced Controller Design of Wind, PV and Battery Inverters

Renewable energies such as wind power and solar energy have become alternatives to fossil energy due to the improved energy security and sustainability. This trend leads to the rapid growth of wind and Photovoltaic (PV) farm installations worldwide. Power electronic equipments are commonly employed to interface the renewable energy generation with the grid. The intermittent nature of renewable and the large scale utilization of power electronic devices bring forth numerous challenges to system operation and design. Methods for studying and improving the operation of the interconnection of renewable energy such as wind and PV are proposed in this Ph.D. dissertation.;A multi-objective controller including is proposed for PV inverter to perform voltage flicker suppression, harmonic reduction and unbalance compensation. A novel supervisory control scheme is designed to coordinate PV and battery inverters to provide high quality power to the grid. This proposed control scheme provides a comprehensive solution to both active and reactive power issues caused by the intermittency of PV energy. A novel real-time experimental method for connecting physical PV panel and battery storage is proposed, and the proposed coordinated controller is tested in a Hardware in the Loop (HIL) experimental platform based on Real Time Digital Simulator (RTDS).;This work also explores the operation and controller design of a microgrid consisting of a direct drive wind generator and a battery storage system. A Model Predictive Control (MPC) strategy for the AC-DC-AC converter of wind system is derived and implemented to capture the maximum wind energy as well as provide desired reactive power. The MPC increases the accuracy of maximum wind energy capture as well as minimizes the power oscillations caused by varying wind speed. An advanced supervisory controller is presented and employed to ensure the power balance while regulating the PCC bus voltage within acceptable range in both grid-connected and islanded operation.;The high variability and uncertainty of renewable energies introduces unexpected fast power variation and hence the operation conditions continuously change in distribution networks. A three-layers advanced optimization and intelligent control algorithm for a microgrid with multiple renewable resources is proposed. A Dual Heuristic Programming (DHP) based system control layer is used to ensure the dynamic reliability and voltage stability of the entire microgrid as the system operation condition changes. A local layer maximizes the capability of the Photovoltaic (PV), wind power generators and battery systems, and a Model Predictive Control (MPC) based device layer increases the tracking accuracy of the converter control. The detail design of the proposed SWAPSC scheme are presented and tested on an IEEE 13 node feeder with a PV farm, a wind farm and two battery-based energy storage systems

Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach

Wind energy has been rapidly gaining popularity as a means for combating climate change. However, the variable nature of wind generation can undermine system reliability and lead to wind curtailment, causing substantial economic losses to wind power producers. Battery energy storage systems (BESS) that serve as onsite backup sources are among the solutions to mitigate wind curtailment. However, such an auxiliary role of the BESS might severely weaken its economic viability. This paper addresses the issue by proposing joint wind curtailment reduction and energy arbitrage for the BESS. We decouple the market participation of the co-located wind-battery system and develop a joint-bidding framework for the wind farm and BESS. It is challenging to optimize the joint-bidding because of the stochasticity of energy prices and wind generation. Therefore, we leverage deep reinforcement learning to maximize the overall revenue from the spot market while unlocking the BESS's potential in concurrently reducing wind curtailment and conducting energy arbitrage. We validate the proposed strategy using realistic wind farm data and demonstrate that our joint-bidding strategy responds better to wind curtailment and generates higher revenues than the optimization-based benchmark. Our simulations also reveal that the extra wind generation used to be curtailed can be an effective power source to charge the BESS, resulting in additional financial returns.Comment: 2023 IEEE Power & Energy Society General Meeting (PESGM). arXiv admin note: text overlap with arXiv:2212.1336