Part 3: Planning for Hydropower Operations and Energy Production

Welcome back to our series on digitalization of hydropower operations and production planning with bespoke integrated solutions. In Part 1, we explored how advanced algorithms predict real-time water inflow with remarkable accuracy, optimizing energy production and increasing efficiency by anticipating water levels and adjusting operations. In Part 2, we highlighted the importance of clear data visualization tools in enhancing collaboration among teams, leading to better decision-making and operational efficiency.

Having sourced, processed, analyzed, and visualized all relevant data, we're ready for the magic—hydropower operations and production planning. In this final part of the series, we will discuss how digitalization supercharges short-, medium-, and long-term production planning and how power markets become more stable with the help of digital solutions. We will also cover optimization opportunities hidden in maintenance and outage planning, seasonal pattern preparedness, seasonal and year-round restriction management. Let’s get started!

Optimizing Short-, Medium-, and Long-Term Production Planning

Transitioning from predictive insights to actionable strategies is the essence of the planning phase. It involves integrating predictive analytics with the operational expertise in your teams to formulate short-, medium-, and long-term production plans that prioritize flexibility building. Operators can use digital tools to automate flexibility-building tasks, such as preemptive reservoir level lowering. While human intelligence remains crucial, digital platforms aid in making informed decisions during unexpected situations. This synthesis of data-driven insights and human intelligence enhances decision-making processes, supporting sustainable and efficient hydropower operations.

Short-term production planning

Employing machine learning methodologies, the continuous processing of live telemetry data and weather forecasts enables the computation of short-term inflow predictions for the upcoming 1 to 72 hours. Given the dynamic nature of both plant telemetry and weather data, the aggregate inflow forecast calculation is updated in real-time. This data serves as the foundation for formulating a production plan tailored for intra-day and day-ahead markets, subsequently conveyed to the operations team through an API, offering recommendations for optimizing storage flexibility and water resource utilization.

To enhance insights for production planning, energy price forecast data is integrated into the model, augmenting the existing datasets for the computation of a “water value.” This calculated value is strategically utilized to dispatch existing flexibility exclusively when the potential for maximizing value is identified. Lastly, all operational and environmental restrictions and regulations, as well as manual outages and maintenance windows, are fed to the algorithm as well, to be factored in for optimization.

Medium- and long-term production planning

Strategically sound production planning for the medium- and long-term is driven by different metrics than short-term production planning. While day-ahead production planning will be largely driven by inflow forecast and water value calculations, medium- and long-term production planning, spanning from one month to five years into the future, uses historical inflow data to extrapolate an estimated inflow. In our experience, asset managers who prioritize long-term optimization over short-term gains are better equipped to weather weather anomalies without compromising their overarching goals. Singular events, although impactful, should not dictate the success or failure of our hydropower production. Instead, it is the ability to optimize and plan for the long-term that sets you apart.

Long-term planning is crucial for the sustainability and profitability of hydropower operations. HYDROGRID Insight introduces an unparalleled long-term forecasting feature that leverages machine learning to derive knowledge from historical data and daily actuals. This solution provides forecasts for water inflow, reservoir levels, and production planning up to 12 months in advance. It’s not just about data; it’s about long term production planning that allow for more efficient maintenance scheduling, outage planning and preparing, and overall water management. After singular unforeseen events, long-term production planning, and inflow forecasts quickly recalibrate to ensure you’re always working with the most current and relevant data.

Production planning for ancillary markets

Ancillary services, essential for grid stability, require a meticulous balance between production capacity and market conditions. Commitment of energy to ancillary markets should always happen at the intersection of production capacity (reservoir level and future forecasted levels) and energy price. Automated digital tools equipped with real-time calculation capabilities enable operators to commit energy to ancillary markets with confidence. These decisions, guided by advanced algorithms, ensure that commitments are made at the optimal intersection of reservoir levels, future forecasts, and energy prices. This strategic approach not only enhances profitability but also contributes to stabilizing power grids.

Water Value for Production Planning -Timely decisions at the crossroads Between Trading and Operations

Heuristic models like HIRO excel in environments filled with uncertainty. These robust decision-making frameworks are designed to handle predictable events and, more importantly, prepare for the unforeseen challenges known as “black swans.” In the current global climate, it's no longer a matter of if a black swan will strike, but when.

The water value concept integrates inflow predictions, energy price forecasts, and operational constraints to determine the optimal use of water resources and asign a monetary value to each drop of water. This approach ensures that water dispatch decisions can integrate trading rationale to better, align with both operational goals and market conditions. For operations planners, this means having a clear, data-driven strategy for managing water resources effectively, minimizing spill, and optimizing energy production.

For traders, the water value model provides critical insights into market conditions and potential revenue opportunities. By understanding the projected water inflow and its calculated value, traders can make informed decisions about when to commit energy to the market. This strategic approach enhances the ability to capitalize on favorable market conditions while maintaining operational efficiency.

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Uncovering Opportunities in Constraint, Maintenance and Outage Planning

Predictive maintenance using integrated digital solutions allow for timely water management ahead, during and after a planned or unplanned outage. By analyzing historical data and real-time operational metrics, AI models can suggest the best window for a needed maintenance, then adjust production planning to prepare your asset for outage day. This proactive approach enhances overall operational efficiency while protecting your hardware.

Benefits of Proactive Maintenance Schedules

Implementing proactive maintenance schedules ensures that maintenance activities are planned and executed during periods of low operational demand, minimizing the impact on production. This strategic planning leads to more efficient use of resources, reducing costs and improving the reliability of hydropower operations. Automated planning tools don't stop at identifying the best maintenance window - long-term production planning will factor in the outage and adjust 'water value' accordingly.

Unplanned Outage Management

Additionally, these tools can aid in managing unplanned outages by recalculating production schedules and forecasts in real-time, ensuring that operations can adapt swiftly to unexpected events and recover faster from 'black swans'. This is thanks to our suite of heuristic models, which are more adaptable and flexible than stocastic ones, enabling them to adjust quickly when confronted with unusual events. They can modify their decision rules based on the current situation, making them more robust in the face of unforeseen circumstances.

Seasonal Pattern Readiness and Restriction Management

While the climate crisis visibly impacts year-on-year patterns and climate at a large scale, which is something we also notice, these seasonal patterns can still be followed and forecasted with the help of machine learning models. Predicting these patterns used to be done using naïve models that assumed each season to look like the last. In the current climate, this approach is no longer efficient for most asset managers. It is perhaps more important to digitalize and automate this process today, as smart hydro can forecast changes at seasonal level as well, based on yearly trends, given that at least one year of historical data is available.

Preparing for Seasonal Variations

The role of AI in predicting seasonal inflow patterns is critical. When computing seasonal patterns, historical data of at least 12 months, and preferably three years or more, is analyzed. Developments at the climate level make it imperative for hydropower managers to forecast trends as accurately as possible and apply mitigation and resilience tactics. We are talking about more intense floods and/or droughts, extended dry seasons, fluctuating air humidity, and fluctuating patterns, all of which are expected to intensify in the following years.

Strategies for Adjusting Operations Based on Seasonal Data

Effective strategies for adjusting operations based on seasonal data involve using AI-driven insights to optimize water resource management. This includes adjusting reservoir levels, managing inflows, and planning energy production to align with seasonal variations. By leveraging advanced forecasting tools, operators can ensure that the forecasted patterns are as accurate as possible and insuring their strategies are both proactive and adaptive, reducing the impact of seasonal fluctuations on operations.

Tools for Managing Seasonal and Year-round Restrictions

Environmental constraints protect the water systems that plants operate in. While these regulations are not directly linked to energy systems, they can greatly impact daily running of the plant, as well as power production flexibility. Managing restrictions with digital solutions involves using advanced software to monitor and comply with regulatory requirements. These tools ensure that water management and trading are done within operational and environmental constraints. We go into greater detail on automated constraint management solutions in this case study.

Conclusion

Successful water management hinges on building flexibility and maximizing your maneuvering window regarding water dispatching strategies. Operators can use digital tools to automate flexibility-building tasks, such as preemptive reservoir level lowering. Where human intelligence remains crucial, digital platforms aid in making informed decisions during unexpected situations. Here are some functionalities that can deliver real-time insight across teams 24/7:

• Real-time Production Planning: Digital solutions enable precise real-time planning, optimizing water use and energy output.
• Long-term Production Planning: Using seasonal patterns and trends derived from historical data of your plant, look up to 12/14 months ahead and plan accordingly.
• Water Value Calculations: AI tools calculate the optimal value of water, considering future inflow expectations, environmental and operational constraints.
• Predictive Maintenance Planning: Digital platforms predict maintenance needs, ensuring timely interventions and minimizing downtime.
• Constraint Management and Prioritization: AI helps manage and prioritize operational constraints, enhancing overall efficiency.
• Collaboration Platforms: These platforms enhance communication and coordination among team members, leading to more effective decision-making.
• Real-time Data Dashboards: Dashboards provide an at-a-glance view of critical metrics, enabling quick and informed decisions.

Partner with HYDROGRID for digitalization of your hydropower plant

We believe that by effectively combining technological advancements with operational expertise, the hydropower industry is well-positioned to maintain its crucial role in the renewable energy landscape, contributing to environmental sustainability and improved operational efficiency. HYDROGRID Insight can aid a production planning strategy by synthesizing these data to save time. In addition to these computations, predictive insight can enhance human decision-making in two ways:

1. It already computes existing limitations of the water system and factors in best practice in the sustainable use of hardware, such as recommended ramping speeds and maintenance planning, turbine best efficiency points/curves, gate operation recommendations, etc.
2. It perpetually uses the latest data available, combined with an ever-growing database of historical data when computing a forecast, with an accuracy that increases as historical data accumulates.