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Asia’s journey toward a sustainable energy future is a complex, multi-layered narrative of policy, market dynamics, and technological innovation. While many nations have set ambitious renewable energy targets, the path to achieving them is not linear. It is a story of strategic pivots, unforeseen challenges, and the co-evolution of top-down mandates with market-driven mechanisms. This report examines the progress of Renewable Portfolio Standards (RPS) and similar policies in key Asian economies, arguing that the success of these initiatives hinges on a holistic strategy that links policy, infrastructure, and advanced data-driven operational tools.

1: The Architects of Transition: Policy Mechanisms and Their Evolution

The foundation of Asia’s energy transition is a toolkit of policy mechanisms designed to accelerate the adoption of clean energy. These tools have evolved from simple, state-led mandates to sophisticated, market-based frameworks, each with its own set of advantages and challenges.

The Foundation: Mandates and Markets

Early-stage renewable energy markets often rely on direct financial incentives to attract investment. The Feed-in Tariff (FIT) is a prime example of this approach.¹ FITs are a policy mechanism that offers long-term, above-market-price contracts to producers of renewable energy. This provides a crucial level of price certainty for investors, helping to jump-start nascent industries.¹ South Korea’s experience with FITs, however, highlights a significant limitation of this model. The policy was implemented in 2001 but eventually led to a “financial burden” on the government, distributors, and taxpayers.² This fiscal strain ultimately prompted a complete policy shift in 2012, demonstrating that while FITs are effective for initial market growth, they may not be sustainable in the long term.² China similarly implemented FITs in 2006, which successfully expanded renewable capacity but also resulted in challenges like power curtailment and fiscal burdens.³

As markets mature, the policy focus often shifts from price certainty to market competition. This is where the Renewable Portfolio Standard (RPS) becomes a dominant mechanism.⁴ An RPS is a regulation that mandates a specific percentage of the electricity that utilities sell must come from renewable sources. This obligation shifts the responsibility of achieving the renewable target from the government’s budget to the energy suppliers.⁵ RPS policies are often praised for promoting competition between different renewable technologies, as generators must compete on price and efficiency to secure contracts.²

The operational backbone of an RPS policy is a system of market instruments known as Renewable Energy Certificates (RECs) or Tradable Green Certificates (TGCs).⁵ These certificates are the “currency” of renewable energy compliance. One certificate represents the environmental attributes of one megawatt-hour of renewable electricity generated.⁷ Utilities subject to the RPS mandate must acquire these certificates to demonstrate compliance with their obligations, creating a secondary market where these certificates can be bought and sold.⁵

The New Frontier: Auctions and Premiums

The evolution of renewable energy policy has not stopped at RPS. Governments have continued to refine their approach to drive down costs and improve market efficiency. Competitive auctions have emerged as a powerful tool for price discovery.⁹ In an auction, the government issues a call for tenders to install a certain capacity of renewable energy. Project developers submit bids with a price per unit of electricity, and the government signs a power purchase agreement (PPA) with the successful bidders.⁹ This mechanism increases cost efficiency and helps avoid potential windfall profits for developers by fostering intense price competition.⁹

A more recent development is the Feed-in Premium (FIP), a hybrid model that combines elements of both FITs and market-based pricing.¹⁰ Under an FIP, generators sell their electricity at the prevailing market price but also receive a premium on top of that price. Japan’s latest Strategic Energy Plan, which targets 40–50% renewable energy by 2040, is a key example of this approach.¹⁰ The FIP scheme is intended to reduce the financial burden on citizens, which can be a consequence of FITs, by exposing generators to market volatility while still providing a financial incentive for investment.¹⁰

The policy transition across Asia from FITs to RPS and auctions represents a significant shift in how risk and cost are allocated. With FITs, the financial burden is often borne by the government or consumers. In contrast, RPS and auctions transfer the risk and uncertainty of market competition to the private sector, compelling them to be more efficient and innovative to remain profitable. This re-engineering of financial responsibility is a core tenet of the policy evolution observed in the region.

2: Country-Specific Narratives: Case Studies of Progress and Volatility

The effectiveness of these policies is best understood through the unique experiences of individual countries. The following case studies illustrate how national circumstances, market maturity, and regulatory design can shape the narrative of a country’s energy transition.

India’s Green Obligation: The Volatility of REC Markets

India’s renewable energy policy is driven by the state-level Renewable Purchase Obligation (RPO), which mandates that a certain percentage of electricity be procured from renewable sources.¹² This obligation is primarily met through the purchase of

Renewable Energy Certificates (RECs), which are traded on the Indian Energy Exchange (IEX).⁷

The IEX reported an all-time high in monthly electricity trade volume in July 2025.¹³ However, this broader market success was juxtaposed with a significant 48% year-on-year decline in REC trading volumes during the same month, despite a general increase in national energy consumption.¹³ This is not an isolated incident; in August 2024, REC volumes surged by over 737% at an all-time low price of 115 rupees per certificate.⁷

This data reveals a critical disconnect between the existence of a policy mandate and the efficacy of the market designed to support it. A policy’s success is not guaranteed by its existence but by the smooth functioning of its market mechanisms. The declining REC volumes, even as the broader electricity market thrives, suggest a failure in policy execution. It indicates that the price signal intended to incentivize renewable energy investment may be undermined by non-compliance, regulatory uncertainty, or a fundamental imbalance in the supply and demand for certificates. The Central Electricity Regulatory Commission’s (CERC) approval of new market coupling norms further adds to the uncertainty ¹⁶, which could discourage market participants and destabilize the very mechanism meant to drive the transition.

China’s Mandate and Market: The Quest for a Functional TGC System

China’s policy evolution mirrors South Korea’s, as it is transitioning from an FIT to a mandatory RPS with a Tradable Green Certificate (TGC) system.³ This strategic pivot was motivated by a need to address the fiscal burdens and power curtailment issues that plagued the earlier FIT model.³ The goal is to achieve the country’s ambitious “3,060” dual carbon target.⁶

However, China’s TGC market is still in its infancy and faces significant challenges. Trading volumes remain extremely low, accounting for only 1% to 11% of the total issued volume of TGCs.⁶ Compounding this issue, TGC prices are “much higher than the international average”.⁶ This situation is a direct consequence of an immature market that lacks liquidity and clear rules. The policy still has to establish a “feasible TGC trading mechanism and an appropriate quota determination technique”.⁶ The immense challenge of building a market from scratch is evident in these low trading volumes and high prices, which impede the policy’s intended goal of driving efficient renewable deployment.

South Korea’s Policy Pivot: The FIT-to-RPS Experiment

South Korea’s policy shift from a FIT to an RPS in 2012 provides a valuable case study.² The move was a deliberate effort to relieve the government’s financial burden by fostering competition among renewable energy producers.² The policy required power producers with capacities over 500 MW to incrementally increase their renewable energy share, with a target of 25% by 2026.¹⁷

While the RPS promoted competition and technological development, a study on its effects revealed an interesting unintended consequence. The new policy did not have a significant positive impact on cost reduction for land-intensive technologies like onshore wind power and small hydropower.¹⁸ This was attributed to the “gradual depletion of sites favourable to RE power plants”.¹⁸ In contrast, the policy successfully drove down costs for technologies not constrained by land availability, such as fuel cell power.¹⁸ South Korea’s journey illustrates that policy design must account for a country’s physical and technological realities. A one-size-fits-all policy can have vastly different outcomes for different technologies, especially in a geographically constrained nation. This highlights the need for policies to be integrated with spatial planning and to foster a diversity of technologies to meet targets.

Japan’s Strategic Evolution: Beyond RPS with FIP

Japan’s energy policy is guided by its Strategic Energy Plan, which balances energy security, economic efficiency, environmental sustainability, and safety.¹⁰ The most recent draft plan positions renewable energy as a mainstream power source and sets an ambitious target of 40–50% of the electricity supply coming from renewables by 2040.¹⁰ To achieve this, Japan is transitioning to a

Feed-in Premium (FIP) scheme to reduce the financial burden on citizens by exposing generators to market prices.¹⁰ The plan also directly addresses the physical and technical challenges of integrating intermittent renewables by emphasizing the development of interregional grid capacity, storage batteries, and innovation in next-generation technologies like floating offshore wind power.¹⁰

Japan’s integrated approach demonstrates a sophisticated understanding that policy incentives alone are insufficient. The combination of FIP, grid modernization, and technological innovation is a holistic strategy that tackles the economic, physical, and technical aspects of the energy transition simultaneously. This level of comprehensive planning is a testament to a mature approach to the energy transition.

The following table provides a comparative overview of the policy mechanisms, targets, and challenges in these key Asian economies.

Country	Primary Policy Mechanism	Key Targets	Associated Market	Noteworthy Challenges
India	Renewable Purchase Obligation (RPO)	Trajectories to 2030 are prescribed by the Ministry of Power.12	Renewable Energy Certificates (RECs) traded on the IEX.13	Volatile trading volumes and regulatory uncertainty undermine the price signal.13
China	Renewable Portfolio Standard (RPS)	Carbon peaking by 2030, neutrality by 2060.6	Tradable Green Certificates (TGCs).6	Market immaturity, low trading volumes, and high prices due to a lack of a clear trading mechanism.6
South Korea	Renewable Portfolio Standard (RPS)	25% by 2026.17	Renewable Energy Certificates (RECs).20	Successful for some technologies but failed to drive cost reductions for land-intensive technologies due to site depletion.18
Japan	Feed-in Premium (FIP)	40-50% renewable energy by 2040.10	Wholesale electricity market + premium payments.10	Requires significant investment in grid upgrades, storage, and new technologies to support the FIP model.10

3: The Unseen Bedrock: Enabling Technologies and Unaddressed Challenges

While policies set the direction, the successful implementation of Asia’s energy transition depends on the technical and operational realities on the ground. A fragile grid infrastructure, the challenges of data-driven decision-making, and the need for a new maintenance paradigm form the unseen bedrock upon which renewable energy mandates must be built.

A Fragile Foundation: Grid Infrastructure as a Bottleneck

A major obstacle to the rapid deployment of renewables is the inadequacy of existing grid infrastructure. Many of Asia’s power grids are “outdated,” having been designed for centralized, predictable fossil-fuel generation.²¹ These grids are ill-equipped to handle the

variability and unpredictability of distributed renewable sources like solar and wind, which can lead to energy curtailment—the wasteful shutdown of clean energy generation.²² The International Energy Agency (IEA) has highlighted a “significant financing gap” for the grid modernization needed to overcome this challenge.²²

The solution lies in the widespread adoption of smart grids and energy storage systems (ESS). A smart grid, such as the “living lab” being developed in Singapore’s Punggol Digital District, can integrate renewables with BESS to store excess energy and regulate supply.²³ This approach addresses the intermittency of solar power, which is a major constraint in a country like Singapore that lacks alternative renewable resources.²⁴ The Jurong Island ESS, at 285 megawatt-hours, is a world-class example of this technology in action, commissioned in a record-breaking six months and acting as a crucial tool for grid resilience.²⁴

The Data Dilemma: AI, Forecasting, and the “Black Box” Problem

The proliferation of renewable energy and the increasing complexity of energy markets have made Artificial Intelligence (AI) an indispensable tool. AI is a top priority for executives, with a strong focus on generating tangible results.²⁵ Its applications range from real-time market analysis and predictive forecasting of prices and load to the automation of trading decisions.²⁶ Platforms like Tyba and Ascend Analytics use AI to craft optimal bidding strategies and maximize revenue for renewable assets by predicting price movements and managing risk.²⁹

However, the application of AI in the energy sector is not without its challenges. The primary obstacle is the unreliability of historical data for training models. Unlike static data used for large language models, the electricity grid is constantly changing, with experts noting that it “is fundamentally looking different every six months”. This requires AI models to be “resilient” and capable of adapting to a dynamic environment shaped by policy shifts and market changes.³²

A related and growing concern is the “black box” problem, where the internal workings of an AI model are opaque.³³ As AI increasingly takes on high-stakes decisions in a highly regulated sector, its lack of transparency poses a significant risk for regulators and compliance.³³ The emerging field of

mechanistic interpretability seeks to address this by reverse-engineering neural networks to provide a clear view of how they make decisions. This could become a necessary strategy for businesses to ensure compliance and build trust in a world where governments are exploring the idea of AI regulation.³³ This suggests that the solution is not just to build more AI, but to build a new class of resilient and interpretable AI that can operate effectively and compliantly in a world of constantly changing rules.

The New Maintenance Paradigm: CBM for a High-Tech Grid

As the energy sector becomes more complex and capital-intensive, the maintenance of critical assets has shifted from older, inefficient strategies to modern, data-driven approaches. Condition-Based Maintenance (CBM) is a strategy that uses real-time data from IoT sensors to monitor the health and performance of equipment, triggering maintenance only when it is actually needed.³⁴

This approach offers significant advantages over older methods like reactive maintenance, which waits for equipment to fail, or time-based maintenance, which follows a fixed schedule regardless of condition.³⁶ CBM reduces unplanned downtime, lowers maintenance costs, and extends the lifespan of assets like turbines, motors, and transformers by catching small issues before they become catastrophic problems.³⁸

The financial benefits of CBM are substantial. A case study of a chemical manufacturing plant showed a first-year ROI of 200% with annual benefits of $390,000 against a total cost of $130,000.⁴⁰ Another example from a major energy corporation saw an annual ROI of $6.7 million by using AI to optimize maintenance support and reduce outage turnaround times.⁴¹ The U.S. Department of Energy reports that predictive maintenance strategies can save 8–12% over preventive maintenance and up to 40% over reactive maintenance.⁴⁰

Despite the clear benefits, the successful implementation of these technologies is a significant challenge. The “10-20-70 principle” from the Boston Consulting Group highlights this, suggesting that top-performing organizations dedicate 70% of their efforts not to algorithms or data, but to “people, processes, and cultural transformation”.²⁵ This is supported by the finding that many companies do not track the financial KPIs of their AI initiatives ²⁵ and that maintenance departments often lack the systems or knowledge to quantify the savings from CBM.⁴² This suggests that the primary barrier to progress is not a lack of technology but a failure of leadership and organizational culture to implement it effectively.

The co-evolution of policy and technology is a two-way street. Ambitious policies like RPS necessitate technological solutions like AI and smart grids. However, these technologies are in turn challenged by the dynamic, policy-driven nature of the grid. The solution, therefore, is not just to build more technology but to develop resilient and transparent AI that can adapt to a world where the rules are constantly changing.

The following table provides a summary of the enabling technologies and their associated challenges.

Technology	Primary Function	Key Benefits	Associated Challenges
AI-driven Trading Platforms	Real-time market analysis and automated trading.26	Maximizes revenue, optimizes bidding strategies, and manages risk.29	Historical data is unreliable, data quality is poor, and models lack interpretability for regulators.
Condition-Based Maintenance	Uses real-time sensor data to monitor equipment health.34	Reduces unplanned downtime, lowers maintenance costs, and extends asset lifespan.38	High initial investment and a lack of a system to quantify savings.44
Smart Grids & ESS	Integrates renewables and stores excess energy.23	Enhances grid resilience, addresses solar intermittency, and improves stability.24	Significant financing gap, outdated infrastructure, and the complexity of managing variable sources.21

4: Forging a Sustainable Path Forward: A Vision for the Future

Based on the evidence presented, a successful and sustainable energy transition in Asia requires a strategic shift from siloed policies to a collaborative, multi-faceted, and technologically integrated approach.

A Call for Collaboration: The Promise of an ASEAN Grid

One of the most promising solutions to a country’s individual constraints is regional collaboration. Singapore, for example, is geographically limited in its ability to generate large-scale renewable energy.⁴⁷ In response, it has developed a long-term vision to import up to 6 gigawatts of low-carbon electricity by 2035, which would meet roughly a third of its projected electricity supply.²⁴ This strategy directly addresses its domestic limitations by leveraging the renewable potential of its neighbors. A tangible example of this is the approved supply of clean power from Cambodia to Singapore, which strengthens Cambodia’s role as an energy exporter while helping Singapore meet its decarbonization goals.⁴⁹ The development of an interconnected ASEAN power grid would facilitate this kind of regional energy trade, creating a more resilient and efficient system for all participating nations.

The Pragmatic Policy Toolkit

The experiences of India, China, and South Korea demonstrate that there is no perfect policy. A pragmatic and dynamic policy toolkit is essential. This includes designing policies that are flexible enough to adapt to local contexts, such as South Korea’s land constraints. It also means fostering liquid and transparent markets that provide clear price signals, a lesson that is particularly relevant for India and China’s nascent REC and TGC markets.⁶ Finally, the regulatory framework must be agile enough to adapt to the constant changes of the grid, as noted by experts who state that the grid “is fundamentally looking different every six months”.³²

A Holistic Investment Strategy

The energy transition is not just about building new power plants; it is a profound transformation of the entire energy ecosystem. A forward-looking investment strategy must, therefore, be holistic. It must move beyond a focus on just power generation to include investments in the “unseen bedrock” of the transition. This includes building modern, interconnected smart grids, deploying advanced energy storage systems, and investing in AI platforms for forecasting and trading. It also means adopting data-driven maintenance strategies like CBM to ensure asset reliability and maximize the value of these expensive new systems. This integrated approach, which links policy, infrastructure, technology, and operations, is the only way to achieve a resilient and profitable energy transition.

Conclusion: The Narrative of Progress and Persistence

Asia’s progress in renewable energy policy is a story of dynamic evolution. It began with straightforward price guarantees to kickstart investment and has matured into complex, market-based systems designed to drive efficiency and reduce costs. The journey from mandates to markets is messy, marked by volatile trading, unforeseen physical constraints, and the immense challenge of building new markets from scratch. The data suggests that while policies like RPS and auctions are powerful tools, their success is not a foregone conclusion. It is deeply dependent on addressing systemic challenges in grid infrastructure, financing, and data-driven operational strategies. The ultimate success of the region’s decarbonization efforts will be a testament to its ability to persistently address these systemic issues, forging a deep and pragmatic link between ambitious policy and the operational realities of a rapidly changing world.

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