Renewables at >50% in European grids

The efficient use of flexibilities requires smooth TSO/DSO coordination, but also raises the question of interface to the flexibility markets and their role. Recently published Deliverable D3.2 on “Conceptual market organisations for the provision of innovative system services” gives answers to these questions.

As not only the vast majority of renewable energy, but also increasing levels of flexibility will be connected to distribution grids, TSO/DSO coordination becomes more important. If the sourcing of flexibilities is market-based, the role of flexibility market operators (MO) also needs to be determined, including the interfaces of the different actors and the question, how the optimization of the electricity system is carried out (centralized versus decentralized), and which tasks shall be allocated to which actors. These topics also play a role in recent discussions, such as the TSO-DSO report “An Integrated Approach to Active System Management” (2019, CEDEC et. al). Deliverable 3.2 addresses these topics in a qualitative way, whereas Deliverable 3.4 carried out selected quantitative assessments.

The first very important insight is the fact that the optimization of the electricity system, avoiding the violation of operational security limits (such as frequency, voltage and thermal limits), consists of the selection of flexibilities (from generation, demand and storage) and switching measures (e.g. topology changes and tap shifting). It was acknowledged by the two WP3 deliverables – D3.2 and D3.4 – that the combination of both measures leads to optimal results. it is especially true, since the digitalization of electricity grids is evolving, which increases the switching potential.

In order to analyze the allocation of such optimization task to different actors, the role of the Optimization Operator (OO) was introduced, which could – theoretically – be fulfilled by each individual system operator, marketplaces or third parties. Based on different case studies, it was concluded that such OO role could best be fulfilled, if it received comprehensive grid data (description of power flows and electrical properties of the grid) from the respective system operator roles.

Based on this role, the flexibility selection processes for centralized and decentralized optimization were assessed: in case of centralized optimization, a single algorithm (run by a single OO) optimizes both transmission and distribution levels, considering all grid constraints (see Figure 1).

Figure 1: Centralized optimization with comprehensive grid data based on the developed role model

 
In case of decentralized optimization, there is one algorithm for each system operator, which requires coordination between the different OOs, e.g. at least one for transmission (OO_T) and one for the distribution grid (OO_D; see Figure 2).

Figure 2: Decentralized optimization with comprehensive grid data based on the developed role model (OO_D/OO_T: Optimization Operator for Distribution/Transmission Grid)

 

Several aspects were reflected with regards to centralized and decentralized optimization:

  • Both optimization principles must respect operational security limits at all voltage levels. No optimization principle reduces liquidity by design.
  • The number of marketplaces is irrespective of the choice of optimization.
  • Both optimizations can work for all scarcities. Still, decentralized optimization appears more relevant for grids, where DSOs need locational products to solve voltage and congestion problems, which might be the case for many distribution grids now or in the future. Centralized optimization is more relevant for products, where, during the procurement process, the DSO does not need to be involved.
  • Conceptually, centralized optimization can lead to optimal allocation of resources, but decentralized optimization can also reach this optimum or, at least, get close to it in many cases.
  • Decentralized optimization ensures higher resilience, lower complexity of algorithms, and the possibility to better adapt to specific requirements of voltage levels and regions.
  • Centralized optimization has lower interoperability and coordination challenges, but complexity is higher.
  • Depending on the design, centralized optimization can also include a step-wise calculation along the structure of the grid, similar to decentralized optimization.

Allocation of the OO role to different actors is a crucial decision. Centralized optimization leads to the allocation of such role to a single actor, which could be a TSO, a TSO/DSO joint venture or a commercial party (e.g. market operator). In case of decentralized optimization, each DSO and TSO can perform the optimization of its system on their own, carrying out the OO function, or there are commercial actors, e.g. market operators, which run the optimization for each system operator.

For the question of allocation of the OO role to different actors, it was concluded that every option other than allocating the OO role to each DSO and TSO (i.e. only possible with decentralized optimization) leads to significant governance and regulation challenges. Examples of the challenges are:

  • Difficulty for system operators to fulfill their responsibility of system operation according to Art. 31 and 40 of the Electricity Directive (EU) 2019/944.
  • Discrepancy between the actor paying for flexibility and the one selecting the flexibility: challenge to incentivize cost-efficient selection and improvement of the algorithm and to defend costs towards the regulator.
  • Building up additional IT systems for optimization, which system operators must do to fulfill their task in emergencies

Although no clear choice of the optimization principles and the allocation of the OO role to actors has been made, it has become obvious that decentralized optimization (carried out by each DSO and TSO, including coordination) is well-suited from a governance and regulation perspective for the existing stakeholder setting with separated DSOs and TSOs. Consequently, a change towards a centralized optimization of transmission and distribution grids leads to the challenges addressed, whereas it is not clear whether the benefits outweigh the costs. The qualitative investigation revealed that the implementation of a sound TSO/DSO coordination, based on decentralized optimization, could lead to optimization results, which can be the same or get very close to the theoretical optimum of a centralized optimization. Quantitative studies have shown that a potential gap can be minimized, if the optimization of flexibility selection and switching measures can be carried out near real-time.

For more information on this topic, please see chapter 5 of Deliverable 3.2 and chapter 3 of Deliverable 3.4.

Written by: Jan Budke (innogy SE), having worked on TSO-DSO coordination, role models and flexibility market design in Task 3.2 on “Conceptual market organisations for the provision of innovative system services”

innogy SE is a leading German energy company, with revenue of around €37 billion (2018) and around 43,000 employees. With its three business segments Renewables, Grid & Infrastructure and Retail, innogy addresses the requirements of a modern, decarbonised, decentralised and digital energy world. Its activities focus on its about 22 million customers, and on offering them innovative and sustainable products and services which enable them to use energy more efficiently and improve their quality of life. The key markets are Germany, the United Kingdom, the Netherlands and Belgium, as well as several countries in Central Eastern and South Eastern Europe, especially the Czech Republic, Hungary and Poland. In renewable power generation, the company is also active in other regions, e.g. Spain, Italy and the USA, with a total capacity of 4.0 gigawatts. As a leader of innovation in future-oriented fields like eMobility, we are represented in the international hot-spots of the technology industry such as Silicon Valley, Tel Aviv and Berlin. We combine the extensive expertise of our energy technicians and engineers with digital technology partners, from start-ups to major corporates.

For further information please follow us on www.eusysflex.com, LinkedIn, Twitter and Facebook.

Disclaimer: blog entries reflect individual views of the author(s) that may not reflect official positions or communication of the project / project consortium.

 

 

 

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