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Reassessing Cyprus’ Competitive Electricity Market: Structural Distortions and Pathways to Reform

Two months ago, Cyprus embarked on its journey with a competitive electricity market model, promising enhanced competition, increased consumer choices, and lower prices. However, the real-world implementation under the so‐called “target model” has revealed significant distortions that are driving up costs for the end user.

Market Distortions in a Small, Isolated System

The fundamental issue lies in the wholesale market’s pricing mechanism. Specifically, the clearing price is determined by the most expensive conventional generation unit of the Electricity Authority of Cyprus (EAC), which must meet the entire demand. This single pricing benchmark is then applied across all market participants, including renewable energy sources (RES). In a market characterized by just two main players—the EAC and limited RES providers—the distortions become inevitable. Moreover, Cyprus’ lack of interconnection with neighboring countries further exacerbates the situation, reinforcing a de facto monopoly where the EAC controls over 90% of production.

The Timing of Price Setting and Its Implications

An analysis of the hourly operations in the wholesale market reveals the inherent biases. During night and early morning hours (00:00-06:30 and 16:00-24:00), the EAC operates exclusively, setting prices solely in its favor. In contrast, during peak morning and afternoon periods, both the EAC and RES are active, benefiting both groups. It is only during brief midday windows, usually spanning 2-4 hours, that RES might operate alone, potentially lowering costs for consumers. However, given the modest share of RES operations (only 3.4% of daily demand), the overall pricing mechanism remains steeply skewed towards EAC’s most expensive units, leading to higher bills for consumers.

Data Insights From November 24, 2025

The Cyprus Grid platform data for November 24, 2025, offers a clear illustration of these distortions. For 22 hours of the day, the wholesale price is dictated by the highest-priced conventional unit, while RES participation remains marginal. Even when a small portion (1.2%) is negotiated at a zero wholesale price during low-demand periods, the remainder (2.2%) is still subject to the expensive pricing mechanism. Consequently, both conventional and RES operators are remunerated based on the EAC’s highest cost, further inflating consumer expenses.

Toward a Sustainable Solution

Immediate and long-term reforms are essential to realign the market with the interests of consumers. Two critical measures have been proposed:

1. Immediate Relief: Implementing a Wholesale Price Cap

Setting a ceiling based on thorough analyses of actual production costs could protect consumers. Any excess pricing over this cap would be automatically rebated as reduced bills. This approach, similar to the successful Iberian Exception mechanism implemented in Spain and Portugal from June 2022 to December 2023 for gas-powered generation, would provide immediate consumer relief without disincentivizing investment in storage and flexible generation units.

2. A Permanent Solution: Contracts for Difference (CfDs)

CfDs have gained prominence across Europe and in markets such as the United Kingdom, France, Poland, and Greece. Under this model, renewable energy producers secure fixed prices via competitive tenders for extended periods (typically 15-20 years). When the wholesale price falls below the fixed price, a dedicated CfD fund compensates the producer, and vice versa—if the wholesale price exceeds the fixed rate, the surplus is returned to the fund, ultimately reducing consumer bills. This approach not only stabilizes long-term electricity prices but also enhances investor confidence and ensures an equitable distribution of any premium charged.

Implementation Roadmap and Final Thoughts

Pragmatic steps must be taken immediately:

  • 2026: Launch a pilot CfD program targeting 100 MW of new projects in solar and storage.
  • 2027-2028: Transition to mandatory CfDs for all new renewable, storage, and hybrid projects.
  • 2026 Summer: Amend the relevant legislation to incorporate these reforms.

The experience of markets like Greece and the UK shows that a well-organized, closely monitored tender system for hybrid projects (combining RES and battery storage) can ensure a fairer, more efficient market. The misfit of the current target model in Cyprus does not necessitate its abandonment but rather its rapid recalibration to suit local conditions.

Conclusion

By implementing a temporary price cap for immediate relief and transitioning to CfDs as a long-term solution, Cyprus stands to lower consumer bills, foster investments in renewable energy and storage, and build a fairer, sustainable electricity market. The time to act is now—not after another expensive five-year cycle of high electricity costs, but today, to build a more resilient and cost-effective energy future for every household and business in Cyprus.

AI Spending Is Complicating The Fed’s Fight Against Inflation

Silicon Valley leaders have long argued that artificial intelligence will make technology and services dramatically cheaper. OpenAI CEO Sam Altman has described a future where intelligence becomes extremely inexpensive, while Tesla and SpaceX CEO Elon Musk has predicted that AI and robotics will create greater abundance and drive down costs.

So far, those benefits have yet to materialise at scale. AI adoption remains relatively slow, while the enormous investment needed for data centres and AI infrastructure is putting pressure on electricity prices, supply chains and other costs. For the Federal Reserve, this creates a difficult balancing act: AI could eventually boost productivity and reduce inflation, but its current buildout is contributing to higher prices.

OpenAI chief economist Ronnie Chatterji said AI needs to be adopted by organisations and generate measurable value before its broader economic impact becomes visible in productivity statistics.

AI Adoption Remains Uneven

Capital spending on AI infrastructure in the U.S. is expected to reach $581 billion this year, according to Goldman Sachs Research, with global investment potentially reaching $1 trillion.

Despite the scale of spending, adoption remains far from universal. A May survey by the U.S. Census Bureau found that 17% to 20% of U.S. businesses reported using AI, with adoption significantly higher among large companies.

Companies that have implemented AI at scale also highlight the challenges. Julie Averill, former CIO of Lululemon, said successful deployment requires changes in employee behaviour and trust in the technology. OpenAI has observed a similar divide: its most advanced business users deploy AI at around eight times the rate of average companies.

Why Productivity Gains May Take Time

Economists point to the limits of automation. AI can perform individual tasks effectively, but many jobs combine tasks that are difficult to automate.

Stanford professor Charles Jones refers to these as “weak links”. Radiology, for example, involves interpreting scans but also communicating with patients and working with colleagues. AI can automate part of the job without eliminating the profession itself.

As a result, the full economic impact of AI may not become clear until businesses adopt the technology more broadly and reorganise their operations around it.

AI Adds To The Fed’s Policy Challenge

AI’s economic impact has become part of the Federal Reserve’s policy debate. Fed Chairman Kevin Warsh has argued that AI could eventually become a significant disinflationary force by increasing productivity and strengthening U.S. competitiveness.

Other officials are more cautious. In July, the Fed kept interest rates at 3.5% to 3.75%, while some officials expressed concern that AI infrastructure spending could add to inflationary pressures.

Minneapolis Fed President Neel Kashkari pointed to massive data-centre investment as a new source of demand. Household electricity prices rose 10% in the two years through July, compared with a 6.2% increase in overall consumer prices. Meanwhile, shortages of chips and other AI components are pushing up costs. JPMorgan Chase estimates that DRAM prices could rise 400% by the end of 2026 compared with 2024.

Warsh has consequently adopted a more cautious tone, saying that while AI investment is laying the groundwork for future growth, the timing and scale of its economic effects remain difficult to predict.

For the Fed, the challenge is clear: AI could eventually deliver major productivity gains, but the cost of building that future is already showing up in the economy.

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