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Editorial

Wind Integration and Power System Planning: Challenges, Policies, and Governance in Italy

Department of Information Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy
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Author to whom correspondence should be addressed.
Energies 2025, 18(19), 5297; https://doi.org/10.3390/en18195297
Submission received: 22 September 2025 / Accepted: 3 October 2025 / Published: 7 October 2025
(This article belongs to the Special Issue Grid Integration of Renewable Energy: Latest Advances and Prospects)

1. Expanding Wind Power: The European Transition and the Italian Case

The trajectory of wind power worldwide is showing a structural acceleration. The Global Wind Energy Council (GWEC) Global Wind Report 2025 [1] certifies that 117 GW of new power was installed in 2024, bringing the cumulative capacity beyond 1100 GW and outlining a scenario in which the sector could triple by 2030. In Europe, WindEurope’s annual report [2] documents 16.4 GW of new installations raising the total to 285 GW, but it strongly signals the presence of infrastructure bottlenecks, slow authorization processes, and insufficient network planning. Growth is accompanied by strong technological dynamism: the study in [3] remarks on the “three Ds” of transition (decarbonization, decentralization and digitalization) and shows how innovative solutions such as floating wind farms and hybrid and agrivoltaic plants are emerging, while [4], through a global comparison between onshore and offshore resources, highlights that the competitive advantage of the open sea is no longer just theoretical. The reduction in levelized costs and the stability of the resource make offshore increasingly appealing compared to onshore, especially in countries with a low availability of suitable land sites. The Italian framework fits this international dynamic with its own peculiarities. In [5], the authors use GIS methods and multi-criteria techniques to identify the most promising areas for offshore development in Sicily, with emphasis on the need to integrate technical, economic, and environmental criteria. On the sustainability side, the work in [6] analyzes the potential impacts of the Med Wind project (2.8 GW for approximately 9 TWh/year, with HVDC connection towards Campania), showing that offshore expansion must necessarily be accompanied by accurate and transparent environmental assessments. Global data and European experiences show that wind is set to become a backbone of the electricity system. However, the speed of development risks exceeding the actual capabilities of the network, and Italy itself is faced with the challenge of transforming its potential (especially in the South and on the islands) into concrete and sustainable projects.

2. Power Flows and Metaheuristics: Advanced Approaches for Planning and Operation Under High Wind Penetration

The analysis of power flows (PFs) and, in particular, of their optimized extensions (optimal power flow, OPF) constitutes a kind of magnifying glass, indispensable for viewing the transformations taking place in electrical systems. These tools, born as modeling methods to evaluate the distribution of voltages, currents, and losses in idealized networks, have become virtual laboratories to anticipate infrastructure stress points and define more resilient management strategies. The methodological evolution has been rapid: deterministic formulations have gradually given way to stochastic schemes, capable of capturing the uncertainty inherent in renewable sources, primarily wind, and integrating it into the operational constraints of the network. A recent example is the study in [7] using stochastic wind distributions and metaheuristics inspired by animal behavior to address OPF and Security Constraints OPF (SCOPF). In [8], the perspective is extended to the integration with electric vehicles, showing how the problem takes on an increasingly multidimensional nature, while in [9], the developments of genetic algorithms are systematized, highlighting their applicability to complex scenarios such as offshore wind farms. In a more experimental key, the authors of [10] propose the Pathfinder Algorithm for a multi-objective OPF with random sources, while in [11], Horse Herd Optimization is developed to directly integrate the variability of wind farms. These contributions, different in approach but converging in purpose, show how PFs have been transformed into an indispensable numerical laboratory to accompany wind growth and enable its sustainable integration into the grid.

3. Beyond Growth Toward Grid Congestion, Oscillations, and Power Quality Issues

Alongside the enthusiasm for new installed volumes, electrical systems clearly show their weaknesses when wind penetration becomes significant. Several studies [12,13] confirm that the multi-objective OPF problem is never trivial: the presence of random sources and compensating devices such as FACTS produces surfaces of highly nonlinear solutions, which require sophisticated algorithmic tools to explore. The work in [14] also takes this perspective, integrating analytical methods, metaheuristics, and deep neural networks to improve the behavior of distribution networks loaded by wind and photovoltaic power, reducing losses and voltage instability. The challenges do not stop at the optimization plan: it also concerns the quality of the electricity service. The authors in [15] highlight how the growing share of offshore wind introduces new forms of disturbance in power quality (flicker, harmonics, voltage dips), whose timely detection requires monitoring techniques based on synchronized waveform measurements. In addition, the authors of [16] state that the adaptation of European grid codes and the widespread adoption of grid-forming inverters will be essential to guarantee a system capable of providing ancillary services and dynamic stability under increasingly stressful operating conditions.
The frequency problem becomes particularly delicate in scenarios with high renewable penetration. The study in [17] demonstrates how advanced forecasting techniques, combined with storage systems and rapid control strategies, can smooth oscillations, but these require a level of coordination that current infrastructures still struggle to ensure. In Italy, southern regions represent a concrete laboratory for these critical issues. In [18], the authors show that, in Sicily, already in the 2030 scenarios simulated with load flow instruments, significant congestion emerges, especially on the 150 kV backbones. The analysis carried out in [19] delves into the short-term perspective (2025–2027) starting from the connection requests presented to the local Transmission System Operator, Terna, highlighting how the concentration of photovoltaic systems to the east and wind power to the west generates risks of overload and uncontrolled redistribution of flows. Finally, the study in [19] instead offers a dynamic reading: in 2030 scenarios, the frequency of the Sicilian system may deviate significantly from the safety values without the support of HVDC connections in grid-forming mode, such as the Tyrrhenian Link, destined to become structural elements of stability. These results not only describe isolated technical problems but also draw a picture in which congestion, power quality degradation, and frequency instabilities interact and reinforce each other. The risk is that excess installed capacity, if not accompanied by appropriate planning and control tools, will eventually reduce the overall reliability of the electricity system.

4. Grid Bottlenecks and Policy Choices: Driving Wind Growth in Italy

The rapidity of wind development must be matched by equal rapidity in governance choices. The picture that emerges from Terna’s transparency tools, primarily the Econnextion [20] platform, is that of a pipeline of enormous, uneven, and concentrated connection requests, precisely where the network is most fragile. Connection projects for a total of 22.89 GW of wind power are currently accepted in Sicily, of which 6.52 GW is onshore and 16.27 GW is offshore, with a marked concentration along the east coast of the island. In Sardinia, the projects amount to 7.19 GW onshore and 6.81 GW offshore; while in Puglia, there is 8.77 GW onshore and 15.52 GW offshore. Figure 1 shows the comparison between the rated power of the project and the maximum load recorded in 2024 in the same regions. Although these are not directly comparable quantities, due to the natural variability in the wind source, the disproportion between the two values is still astonishing: the capacity planned largely exceeds the peaks of local demand. This fact is even more relevant if the parallel expected growth of other renewable sources is considered, primarily photovoltaics, which are also planned to be concentrated in the same areas.
Continuing with a logic of “first-come, first-served” means stopping gigawatts on already congested lines, generating multi-year queues, and fueling expectations that the system cannot honor in the time needed for the transition. Here, the uncomfortable but decisive theme of ineffective policies emerges. The literature on public policies recalls that well-intentioned tools can produce suboptimal outcomes if decoupled from the institutional and infrastructural context: disproportionate authorization processes, uninterrupted local opposition, auction and market rules that ignore network bottlenecks [21,22]. The result is double damage: projects run faster than the network, and the network grows where it is not really needed. A paradigm shift is needed: selective prioritization of connections, conditional on real hosting capacity and added system value (loss reduction, congestion alleviation, ancillary services), and sequencing of connections consistent with the reinforcement times of critical routes. Modeling needs to be placed at the heart of governance and the decision-making system. OPF scenario-based approaches such as SOPF-WOCG [23], combined with robust prediction techniques, allow estimating accommodable wind capacities without exploding curtailment and with adequate reserves. In terms of governance, this translates into the need for the prior assessment of network capacity, the selective allocation of connection quotas based on system benefits, the mandatory integration of flexible resources, and the adoption of more stringent technological standards for plants located in structurally weak areas. Downstream, market mechanisms for remunerated curtailment and fast frequency services will reduce the asymmetry between the value of the energy produced and the value of the system that must host it.
Planning must not be understood as an accessory but as the common thread that guides development. Wind growth can translate from uncertain promise to sustainable reality, the protagonist of a transition, in which connection demands finding space in a progressively adequate grid, with certain connection methods and times. Therefore, the expansion that lies ahead is not only a challenge but also an opportunity to demonstrate that it is possible to combine technological innovation, effective governance, and harmonious development of the territory.

Author Contributions

Conceptualization, D.A. and M.P.; investigation, D.A. and M.P.; writing—original draft preparation, D.A. and M.P.; writing—review and editing, D.A. and M.P.; supervision, M.P. All authors have read and agreed to the published version of the manuscript.

Funding

This work was produced without any external funding or financial support from third parties.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Global Wind Energy Council (GWEC). Global Wind Report 2025; Technical Report; GWEC: Brussels, Belgium, 2025. [Google Scholar]
  2. WindEurope. Wind Energy in Europe: 2024 Statistics and Outlook 2025–2030; Technical Report; WindEurope: Brussels, Belgium, 2025. [Google Scholar]
  3. Tiismus, H.; Maask, V.; Astapov, V.; Korotko, T.; Rosin, A. State-of-the-art review of emerging trends in renewable energy generation technologies. IEEE Access 2025, 13, 10820–10843. [Google Scholar] [CrossRef]
  4. Tumse, S.; Bilgili, M.; Yildirim, A.; Sahin, B. Comparative analysis of global onshore and offshore wind energy characteristics and potentials. Sustainability 2024, 16, 6614. [Google Scholar] [CrossRef]
  5. Khan, F.; Rapposelli, A. Offshore Wind Farm Development in Italy. In Proceedings of the Scientific Meeting of the Italian Statistical Society, Bari, Italy, 17–20 June 2024; Springer: Cham, Switzerland, 2024; pp. 183–187. [Google Scholar]
  6. Guercio, A.; Rincione, R.; Curto, D.; Longo, S.; Martorana, P.; Guarino, F.; Cellura, M. Evaluation of the potential environmental impacts from an offshore wind energy farm in the Mediterranean Sea. In Proceedings of the OCEANS 2024—Singapore, Singapore, 15–18 April 2024; IEEE: Piscataway, NJ, USA, 2024; pp. 1–6. [Google Scholar]
  7. Khamees, A.K.; Abdelaziz, A.Y.; Eskaros, M.R.; Alhelou, H.H.; Attia, M.A. Stochastic modeling for wind energy and multi-objective optimal power flow by novel meta-heuristic method. IEEE Access 2021, 9, 158353–158366. [Google Scholar] [CrossRef]
  8. Nagarajan, K.; Rajagopalan, A.; Bajaj, M.; Raju, V.; Blazek, V. Enhanced wombat optimization algorithm for multi-objective optimal power flow in renewable energy and electric vehicle integrated systems. Results Eng. 2025, 25, 103671. [Google Scholar] [CrossRef]
  9. Khosravy, M.; Gupta, N.; Witkowski, O. Frontiers in Genetics Algorithm Theory and Applications; Springer: Singapore, 2024. [Google Scholar]
  10. Li, N.; Zhou, G.; Zhou, Y.; Deng, W.; Luo, Q. Multi-objective pathfinder algorithm for multi-objective optimal power flow problem with random renewable energy sources: Wind, photovoltaic and tidal. Sci. Rep. 2023, 13, 10647. [Google Scholar] [CrossRef] [PubMed]
  11. Evangeline, S.I.; Rathika, P. Wind farm incorporated optimal power flow solutions through multi-objective horse herd optimization with a novel constraint handling technique. Expert Syst. Appl. 2022, 194, 116544. [Google Scholar] [CrossRef]
  12. Pandya, S.B.; Kalita, K.; Čep, R.; Jangir, P.; Chohan, J.S.; Abualigah, L. Multi-objective snow ablation optimization algorithm: An elementary vision for security-constrained optimal power flow problem incorporating wind energy source with FACTS devices. Int. J. Comput. Intell. Syst. 2024, 17, 33. [Google Scholar] [CrossRef]
  13. Pandya, S.B.; Ravichandran, S.; Manoharan, P.; Jangir, P.; Alhelou, H.H. Multi-objective optimization framework for optimal power flow problem of hybrid power systems considering security constraints. IEEE Access 2022, 10, 103509–103528. [Google Scholar] [CrossRef]
  14. Avar, A.; Ghanbari, E. Optimal integration and planning of PV and wind renewable energy sources into distribution networks using the hybrid model of analytical techniques and metaheuristic algorithms: A deep learning-based approach. Comput. Electr. Eng. 2024, 117, 109280. [Google Scholar] [CrossRef]
  15. Shao, H.; Henriques, R.; Morais, H.; Tedeschi, E. Power quality monitoring in electric grid integrating offshore wind energy: A review. Renew. Sustain. Energy Rev. 2024, 191, 114094. [Google Scholar] [CrossRef]
  16. Wu, D.; Seo, G.S.; Xu, L.; Su, C.; Kocewiak, L.; Sun, Y.; Qin, Z. Grid integration of offshore wind power: Standards, control, power quality and transmission. IEEE Open J. Power Electron. 2024, 5, 583–604. [Google Scholar] [CrossRef]
  17. Loza, B.; Minchala, L.I.; Ochoa-Correa, D.; Martinez, S. Grid-friendly integration of wind energy: A review of power forecasting and frequency control techniques. Sustainability 2024, 16, 9535. [Google Scholar] [CrossRef]
  18. Musca, R.; Sanseverino, E.R.; Vasile, A.; Zizzo, G.; Iaria, A.; L’Abbate, A.; Vitulano, L. Power-Flow studies on the Future Electricity Grid of Sicily: Analysis of 2030 Scenario Cases. In Proceedings of the 2023 AEIT International Annual Conference (AEIT), Rome, Italy, 5–7 October 2023; IEEE: Piscataway, NJ, USA, 2023; pp. 1–6. [Google Scholar]
  19. Di Gloria, P.; Paradiso, S.; Pede, M.; Sorrentino, V.M.E.; Vergine, C.; Massaro, F.; Vasile, A.; Zizzo, G. On the Impact of Renewable Generation on the Sicilian Power System in Near-Future Scenarios: A Case Study. Energies 2024, 17, 3352. [Google Scholar] [CrossRef]
  20. Terna S.p.A. Econnextion: The Map of Storage and Renewable Connections. 2023. Available online: https://www.terna.it/en/electric-system/efficient-territorial-planning/econnextion (accessed on 19 September 2025).
  21. Roberge, I.; McKeen-Edwards, H.; Campbell-Verduyn, M. Ineffective policies: Causes and consequences of bad policy decisions. In Ineffective Policies; Policy Press: Bristol, UK, 2025; pp. 1–14. [Google Scholar]
  22. Gazzani, F. Acceptance of offshore wind farm in Southwest Sardinia in Italy. Do regional energy policies matter? Int. J. Energy Sect. Manag. 2024, 18, 2169–2190. [Google Scholar] [CrossRef]
  23. Shah, A.A.; Wang, S.C.; Liu, G.; Hassan, R.U.; Nawaz, A. Scenario Based Optimal Power Flow Evaluation for Wind Power Allocation Capacity in Modern Power Systems. IEEE Access 2025, 13, 38443–38453. [Google Scholar] [CrossRef]
Figure 1. Accepted connection requests for wind farms in Italy’s southern region and maximum registered load in 2024.
Figure 1. Accepted connection requests for wind farms in Italy’s southern region and maximum registered load in 2024.
Energies 18 05297 g001
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Astolfi, D.; Pasetti, M. Wind Integration and Power System Planning: Challenges, Policies, and Governance in Italy. Energies 2025, 18, 5297. https://doi.org/10.3390/en18195297

AMA Style

Astolfi D, Pasetti M. Wind Integration and Power System Planning: Challenges, Policies, and Governance in Italy. Energies. 2025; 18(19):5297. https://doi.org/10.3390/en18195297

Chicago/Turabian Style

Astolfi, Davide, and Marco Pasetti. 2025. "Wind Integration and Power System Planning: Challenges, Policies, and Governance in Italy" Energies 18, no. 19: 5297. https://doi.org/10.3390/en18195297

APA Style

Astolfi, D., & Pasetti, M. (2025). Wind Integration and Power System Planning: Challenges, Policies, and Governance in Italy. Energies, 18(19), 5297. https://doi.org/10.3390/en18195297

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