Interconnected gears representing energy cycles, with wind turbines and solar panels in the background.

Renewable Energy's Hidden Trap: Are Green Mandates Messing with Our Storage?

Reese Marlowe in Climate & Environment December 2025 • 4 min read.

"Unintended storage cycling is a sneaky problem in energy models. Learn how renewable energy targets might be backfiring and what can be done."

The push to decarbonize our economies has led many governments to set ambitious targets for renewable energy. These targets, often framed as a percentage of electricity demand or supply, appear straightforward. However, implementing these targets in energy models—the tools we use to plan our energy future—can be surprisingly tricky.

A growing body of research suggests that these renewable energy mandates can inadvertently create a modeling artifact: excessive electricity storage use. This phenomenon, dubbed "unintended storage cycling," occurs when energy models simultaneously charge and discharge storage systems in ways that don't reflect real-world needs.

This article will dissect this issue, explaining how different approaches to implementing renewable share constraints can lead to unintended storage cycling. We'll also explore the potential consequences of this cycling and offer recommendations for avoiding these pitfalls, ensuring our energy models provide a more accurate roadmap for a sustainable future.

What is 'Unintended Storage Cycling' and Why Should You Care?

Interconnected gears representing energy cycles, with wind turbines and solar panels in the background.

Imagine a scenario where wind and solar energy flood the grid, exceeding consumer demand. The intuitive solution is to curtail the excess renewable energy. However, certain renewable share constraints can lead energy models to choose a different path: replacing curtailment with storage conversion losses. This happens through additional, and often simultaneous, charging and discharging of storage systems.

This "unintended storage cycling" increases the apparent need for renewable energy generation. It may seem like a good thing at first glance. It helps meet renewable energy targets. However, it may create distortions in energy dispatch, investment decisions, and even market prices.

Distorted Dispatch: Storage systems might cycle energy unnecessarily, leading to inefficiencies.
Skewed Investment: Investments may be misdirected towards storage rather than other crucial technologies.
Price Volatility: Market prices might become artificially distorted.

Ultimately, unintended storage cycling can undermine the accuracy of energy models, leading to suboptimal outcomes. Recognizing and addressing this issue is crucial for effective energy planning. By ensuring the integrity of our models, we can pave the way for a truly sustainable and economically sound energy future.

Navigating the Future of Renewable Energy Modeling

The journey toward a sustainable energy future requires careful planning and accurate modeling. By understanding the potential pitfalls of unintended storage cycling and implementing appropriate safeguards, we can ensure that our energy models serve as reliable guides. Fully accounting for storage losses in renewable energy constraints, exploring alternative target formulations, or employing emission constraints can pave the way for more robust and realistic energy planning.

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Everything You Need To Know

What is 'unintended storage cycling' in the context of renewable energy, and why is it a concern?

'Unintended storage cycling' refers to a modeling artifact where energy models excessively charge and discharge storage systems in unrealistic ways, not aligned with actual grid needs. This typically happens when renewable share constraints are implemented in energy models. It's concerning because it can distort energy dispatch, skew investment decisions towards storage over other potentially more effective technologies, and even create artificial price volatility in energy markets, ultimately undermining the accuracy and effectiveness of energy planning.

How can renewable energy targets inadvertently lead to 'unintended storage cycling' in energy models?

Renewable energy targets, when implemented as renewable share constraints in energy models, can inadvertently lead to 'unintended storage cycling'. When wind and solar energy exceed demand, instead of curtailing the excess, some models choose to charge and discharge storage systems unnecessarily to meet the imposed renewable share targets. This happens because the models attempt to replace curtailment with storage conversion losses, increasing the apparent need for renewable energy generation and creating a cycle of charging and discharging that doesn't reflect real-world operational needs.

What are the potential consequences of 'unintended storage cycling' on energy dispatch, investment decisions, and market prices?

The consequences of 'unintended storage cycling' are threefold. First, it can lead to distorted energy dispatch, where storage systems cycle energy unnecessarily, resulting in inefficiencies. Second, it can skew investment decisions, misdirecting resources towards storage rather than other critical technologies needed for a balanced energy system. Finally, it can create price volatility in the market, leading to artificial distortions that don't accurately reflect supply and demand dynamics.

What measures can be taken to avoid 'unintended storage cycling' and ensure more accurate energy modeling for a sustainable future?

To avoid 'unintended storage cycling' and improve the accuracy of energy models, several measures can be implemented. One approach is to fully account for storage losses in renewable energy constraints, ensuring the models accurately reflect the energy lost during storage conversion. Another is to explore alternative target formulations that move beyond simple renewable share constraints. Additionally, employing emission constraints can provide a more holistic and realistic framework for energy planning, guiding models toward optimal solutions that prioritize both renewable energy adoption and overall system efficiency.

Beyond the immediate effects, what are the broader implications of distortions caused by 'unintended storage cycling' for achieving long-term sustainability goals?

Beyond immediate effects like distorted energy dispatch and skewed investments, distortions from 'unintended storage cycling' have broader implications for achieving long-term sustainability. If energy models inaccurately represent real-world conditions, they can lead to suboptimal energy infrastructure investments, hindering the transition to a truly sustainable and economically sound energy future. The misallocation of resources could delay the deployment of essential technologies, increase the overall cost of decarbonization, and ultimately slow progress towards climate goals. Accurate modeling, free from artifacts like 'unintended storage cycling', is crucial for making informed decisions that support a sustainable energy transition.