Development of an open-access generic forecasting methodology for the determination congestion management requirements in power systems
Potential applicants would refer to academic institutions, research institutes, or private companies with a deep understanding and proven expertise on the following fields.
Expertise can be proven by peer-reviewed research papers in scientific journals and international conferences, book chapters, books, technical reports, or portfolios.
In particular, the prospective Third Party should be able to prove its expertise on the following fields:
- Power systems analysis and modeling
- Load flow studies
- Congestion management
- Active management of Distribution Grids towards congestion mitigation
- Optimization studies in power systems
- Demand response
- Integration of volatile renewable energy sources into the grid
- Extensive knowledge in South-East Europe`s power systems
Furthermore, the prospective Third Party should be able to provide proof of its participation in at least 3 organized international projects related to electrical power systems.
In transmission and distribution networks, congestion occurs in cases where the networks cannot process all the transactions due to violations of operating limits. Congestion management is a mechanism to prioritize the transactions to keep the network operations within their nominal limits. The concept refers to the scheme where an aggregator is an intermediate agent between the distribution system operator and a number of distributed energy resources. The interaction between the aggregator and operator includes flexibility offers and requests. The flexibility of the generation units will contribute to congestion management.
For congestion management analysis, potential applicants will be required to work with MATPOWER™ (https://matpower.org/), PowerFactory-DigsilentTM (https://www.digsilent.de/en/powerfactory.html) or/and Power System Analysis Toolbox™ (http://faraday1.ucd.ie/psat.html).
Potential applicants are expected to expand the above software packages in order to develop new packages for congestion management modeling in various types of test systems. Potential applicants are also expected to examine scenarios-based analysis for different cases of congestion instances and, finally, provide insights and recommendations regarding the connection and synergy of transmission and distribution networks in congestion management.
The workflow will include different scenarios of installed capacities of generation units and renewable penetration shares in order to solve an extended power flow analysis problem. The outputs will refer to the determination of indices for congestion management resources.
For the congestion management analysis, the following data will be required:
- Transmission and distribution systems benchmark topologies. For instance, the characteristics of IEEE 24-bus, IEEE 39-bus, IEEE 118-bus, etc., test systems.
- Technical, economic, and operational data of distributed energy resources such as fossil-fired generators, photovoltaics units, and wind generators.
- Hourly active and reactive demand over a 24-hour period in the various buses of the transmission and distribution buses.
- Technical and operational data of transmission lines and buses such as thermal, voltage and stability limits and others.
- Meteorological data for the assessment of renewable energy sources capacity.
The experiment refers to the formulation and solution of a non-cost free congestion management problem. Generally, the outputs refer to the generation units rescheduling and curtailment of load transactions. Next, these outputs will be employed in various models of Task 7.1.
At the DSO level, an approximation and generalization of the findings at several DSO topologies will be conducted so as to determine the overall congestion management requirements at a DSO level.
The objective refers to the determination of the requirements for congestion management resources. The outputs of the workflow will include:
- methodology development for the implementation of a power flow analysis based on the initial DAM energy schedule,
- extensive scenario and test cases assessment for the identification of congestion management requirements, and
- provision of final report including the methodology part, representative results, and concluding remarks.
The methodology’s objective is to quantify the operational congestion management requirements at both TSO and DSO levels. The output of that methodology will be integrated and utilized as input data in the models under development for the day-ahead and balancing markets (INTERRFACE Demo 7.1).
The applicability of the developed framework will be tested in the examined South-Eastern European region, including the power systems of Romania, Bulgaria, and Greece. The business case aims to thoroughly investigate various transmission and distribution systems benchmark topologies to identify generic indicators that can be utilized for the quantification of sub-hourly operational congestion management requirements at both TSO and DSO levels.
Important information for applicants
Recommended software packages:
Power System Analysis Toolbox™ (http://faraday1.ucd.ie/psat.html)
Electric Grid Test Case Repository (https://electricgrids.engr.tamu.edu/)
NASA’s Open Data Portal (https://power.larc.nasa.gov/data-access-viewer/)
Meteoblue database (https://www.meteoblue.com/)
Added value on INTERRFACE project
The experiment will allow the interested parties to examine the flexibility concept in both the transmission and distribution levels. The aggregator’s role in contemporary electricity markets will be highlighted and assessed.
Incorporation of Third Parties in particular for end-users flexibility
Assessment of the distributed energy resources’ impacts on the operation of day-ahead and balancing markets, enabling the provision of clear price signals and the design of appropriate incentives.
Third Parties benefit from getting involved in the business case
Integration with an advanced optimization model for the operation of day-ahead and balancing markets.