Battery Storage Capacity selection for maximum availability of Round-the-Clock (RTC) power to energy transition process plants from renewable energy (Solar and Wind).

As the world increasingly shifts towards renewable energy sources, energy storage solutions become crucial for achieving reliable, round-the-clock power supply. This is particularly important in intermittent renewable power generation plants such as solar and wind. Effective battery storage is key to addressing the intermittency of these renewable sources and ensuring a maximum availability of RTC power for process plants.

Understanding the challenge

Solar and wind energy, while abundant and clean, are inherently variable. Solar power is only available during daylight hours and can be affected by weather conditions, while wind energy fluctuates based on wind speed and patterns. To maximise the use of this intermittent power for energy transition process plants like Green Hydrogen, Ammonia production, some energy generated during peak times must be stored effectively for use when generation is low or demand is high to maximise the availability of continuous RTC power.

The role of battery storage

Battery storage systems are designed to absorb and store energy produced by renewable sources. This stored energy can then be used to maintain a steady power supply, ensuring that the production process remains uninterrupted. The challenge lies in determining the optimal battery storage capacity to handle the energy storage from solar and wind sources efficiently and minimise the curtailment energy (i.e., excess energy more than required demand and battery storage).

Key considerations for battery storage selection

1. Energy Production Profiles: Understanding the production profiles of both solar and wind resources is critical. This involves analysing historical data to determine peak production times, seasonal variations, and patterns of excess energy. By modelling these energy profiles, we can estimate the amount of energy that needs to be stored.

Two important factors which define the performance of power generation plant are

A. Plant load Factor (PLF)

The plant load factor (PLF) of a power plant measures the ratio of the actual output to the maximum possible output over a specific period. It indicates how efficiently the plant is being utilised relative to its full capacity.

Plant Load Factor (PLF) = Actual Output / Maximum Possible Output

A higher PLF indicates that the plant is operating closer to its maximum capacity, suggesting efficient utilisation. A lower PLF reflects lower efficiency and underutilisation of the plant's capacity.

B. Availability Factor (AF)

The Availability factor (AF) of a power plant is a measure of the proportion of time that a plant is capable of generating electricity compared to the total time it is expected to be available for operation. It reflects the reliability and operational efficiency of the plant.

Availability Factor (AF) = Time the Plant is Available to Generate Power / Total time.

A higher availability factor indicates better reliability and fewer unplanned outages, while a lower factor suggests higher levels of downtime and reduced operational efficiency.

2. Battery Storage Capacity Calculation: The battery storage capacity selection takes into account the energy generation from solar and wind sources. It considers factors like peak production periods, energy consumption patterns, and efficiency losses. By taking these parameters into the account, we can determine the storage capacity to ensure round-the-clock power availability for maximum time.

3. Economic and Environmental Impact: Battery storage not only ensures a steady supply of power but also has economic and environmental implications. Properly sized storage systems reduce the need for backup generators and grid support, thereby lowering operational costs and minimising carbon footprint.

Types of coupling for battery storage systems

When integrating battery storage with renewable energy sources, the choice of coupling method is crucial. The main types of coupling are:

1. DC Coupling: In DC coupling, the battery storage system is directly connected to the DC side of the through DC-DC converter. This method allows for efficient direct charging of the batteries with minimal conversion losses. DC coupling is often used in systems where the energy storage and generation are tightly integrated, and it simplifies the system design by reducing the need for multiple inverters. However, it may be less flexible if you want to add additional components or integrate with other energy sources like wind power.

2. AC Coupling: AC coupling involves connecting the battery storage system to the AC side of the power system, typically through transformer and power conversion system (PCS). This method allows the battery storage to be more easily integrated with the grid and other AC-powered loads. AC coupling provides greater flexibility and can simplify the addition of storage to existing systems. However, it may involve additional conversion losses due to the need to convert between AC and DC.

Using XLWINGS (Python library) for energy balancing and battery storage calculation

To select the battery storage requirement for the RTC power assessment for maximum availability and less curtailment, XLWINGS, a powerful Python library that enables seamless integration between Python and Excel is used. XLWINGS facilitates complex calculations and energy balancing by allowing us to use Python’s computational power alongside Excel’s user-friendly interface. Here’s how it plays a crucial role:

1. Energy Production Profiles: XLWINGS helps analyse hourly solar and wind energy production data. By importing and processing this data in Excel, we can create detailed energy production profiles.

2. Storage Capacity Calculation: The developed program, utilising XLWINGS, calculates the optimal battery storage capacity required to store required energy for different availability factors. By inputting parameters like hourly energy production, energy consumption patterns, and efficiency losses into Excel, and running Python calculations through XLWINGS, we can determine the ideal storage capacity for required round-the-clock power availability with maximum energy utilisation.

The following case studies, using various combinations, were conducted with the developed XLWINGS (Python) program to determine RTC power and corresponding battery storage for different % RTC power availability:

Case 1: With 100 MW (AC) Solar Plant

Case 2: With 100 MW (AC) Wind Plant

Case 3: With 50 MW (AC) Solar + 50 MW (AC) Wind Hybrid Plant

Hourly generation data for a year, obtained from renewable generation prediction software (PVSyst), served as input for these calculations. The input parameters for batteries and inverters considered in the calculations are as follows:

Inverter efficiency – 98.40%

PCS inverter efficiency – 98.40%

Battery charging efficiency – 96.00%

Battery discharging efficiency – 94.00%

Transformer efficiency – 99.00%

Initial battery state of charge – 100.00%

Battery depth of discharge – 98.00%

The results of the calculations for Cases 1 to 3, showing RTC power at different availability levels (ranging from 70% to 100%) corresponding to varying battery storage capacities, are tabulated below.

Case 1: Battery Storage Vs RTC power with different % availability for 100 MWac Solar Plant

Case 2: Battery Storage Vs RTC power with different % availability for 100 MWacWind Plant

Case 3: Battery Storage Vs RTC power with different % availability for 50 MWacSolar + 50 MWac WindHybrid Plant

Summary of the above cases:

Case 1: Solar Plant provides lower RTC andlower curtailment compared to the hybrid and wind plant.

Case 2: Wind Plant provides good RTC and highest curtailment compared to the solar and hybrid plant

Case 3: Hybrid Plant provides the highest RTC and relatively higher curtailment compared to solar plant but better than wind plant.

From the above cases, it can be inferred:

1. Increasing Battery storage capacity improves RTC Power:

As the Battery storage capacity increases, the RTC power generally increases across all availability levels. This is expected because more battery storage allows for more energy to be stored and used to meet power demands at non generation hours.

2. Diminishing Returns with Higher Battery storage Capacity:

Beyond a certain point, increasing the Battery storage capacity yields smaller increases in RTC power. For example, In Case-1, at 80% RTC availability, RTC power increases significantly from 300 MWh to 340 MWh, butthe gains become marginal as you move to higher capacities like 480 MWh or 500 MWh.

3. Curtailment Reduces with more Storage: As Battery storage capacity increases, the percentage of curtailment decreases. This indicates that higher storage capacity helps in reducing unplanned energy by storingmore of it.

4. High Availability Levels Show Higher Curtailment: At 95% and 100% RTC availability, the curtailment percentage is significantly higher compared to lower availability levels. This suggests that achieving very high RTC availability requires a lot of battery storage, and even then, a substantial portion of energy might be curtailed.

5. Optimal Storage Levels: For a given RTC availability, there’s an optimal Battery storage capacity where the RTC power is maximised before the benefits start diminishing. For instance, In Case-1, at 80% availability, increasing the Battery storage beyond 460 MWh results in minimal gains in RTC power.

Implementation and benefits

Implementing a battery storage system with renewable energy infrastructure and establishing a control system that manages energy flow between generation, storage, and demand. The benefits of this approach include:

• High Availability Factor: Ensures that the production process is not interrupted by fluctuations in renewable energy generation.
• Increased Efficiency: Maximises the use of generated renewable energy, reducing waste and improving overall efficiency.
• Cost Savings: Reduces dependency on fossil fuels and backup power sources, leading to lower operational costs.
• Environmental Impact: Supports the transition to a more sustainable energy system by enhancing the use of clean energy sources.

Pros of battery storage system

Battery storage systems offer several advantages over other storage systems:

1. Fast Response Time: Batteries can quickly discharge and recharge, providing immediate support to the system. This is an important advantage over other storage systems to overcome the generation disturbances of renewable plants due to sudden change in environmental conditions.

2. Scalability: Batteries can be easily scaled up or down to match specific needs.

3. Modularity: Allows for incremental expansion without major infrastructure changes.

Cons of battery storage system

1. Lifecycle and Degradation: Batteries degrade over time and may requireaugmentation to be done periodically over the life of plant.

2. Thermal Management: Batteries can be sensitive to operating temperature, may require cooling or heating systems for efficient operation.

3. Cost: Batteries can be expensive, in terms of initial investment. However, the costs may reduce as and when different technologies evolve.

Conclusion

Battery storage is a crucial step in harnessing the full potential of renewable power plants employed in energy transition process plants like Green Hydrogen and Ammonia plants. By accurately assessing energy generation and aligning storage solutions with production and demand patterns, it is possible to achieve a reliable, efficient, and environmentally friendly energy system. The XLWINGS using python program developed for arriving at the RTC power and Battery storage capacity for different percentage availability with renewable power plant is a valuable tool, helping to ensure that renewable energy is utilised as per the operation requirements of process plant and remains sustainable.

Balakumaran G has done BE in Electrical and Electronics from BIT Mesra, Ranchi. He has an industry experience of over 15 year and his expertise is in the field of Engineering for Power, Renewable, Oil & Gas and EPC projects. He has been professionally associated with top conglomerates, like Reliance Group and Maire Tecnimont. Currently, he is working as Deputy Chief Engineer – Electrical in Tecnimont.

Acknowledgment

Special thanks to engineering Interns – Kalpit (IIT-BHU), Mrugaja (Pune Engg College) and Shubham (NIT Surat) for their contributionin developing the Python codes for this XLWINGS program. 

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