๐⚡ Cross-Country Insights into Wind & Solar PV Interactions Using the Stochastic Lotka-Volterra Model
The global energy transition is powered by clean technologies, but understanding how different renewable sources interact is a complex challenge. ๐ฑ๐ In our latest study, we apply the stochastic Lotka-Volterra model to explore the dynamic interactions between wind power ๐ฌ️ and solar photovoltaic (PV) energy ☀️ across multiple countries.
๐ Key Findings
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Scale Effects
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Wind markets show both positive and negative scale effects depending on the country.
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PV solar markets, however, are consistently scale-restrictive ⚖️, limiting their own growth potential.
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Types of Technology Interactions
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Current interactions are largely mutualistic ๐ค or prey-predator ๐ฆ ๐ in nature.
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Prey-predator dynamics are observed in the US, China, and Italy, with PV solar acting as the predator against wind.
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Stochastic vs. Deterministic Orbits
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Random orbits of installed capacity oscillate around the deterministic equilibrium orbit ๐ฏ.
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These orbits are normally distributed ๐, and the mean orbit converges to the equilibrium defined by the deterministic model.
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๐ Why This Matters
This relationship between stochastic diffusion paths and deterministic equilibrium helps us:
✅ Identify countries with stable technology diffusion patterns.
✅ Use predictive features of the stochastic Lotka-Volterra model for energy forecasting.
๐ Country-Specific Insights
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Stable distributions (normally distributed random orbits): ๐ฎ๐ณ India, ๐ฏ๐ต Japan, ๐ฎ๐น Italy
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Forecasts: Three-year projections (to 2020) for both wind and PV solar technologies indicate clear trends in adoption and growth. ๐
๐ Conclusion
Our findings show that renewable energy technologies don’t just grow independently—they compete, cooperate, and sometimes restrict each other’s growth. Understanding these dynamics is crucial for policy-making, investment decisions, and future energy planning ๐ฎ⚡.
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