30 March 2026
OptOmni: towards a holistic grid optimizer
The project OptOmni aims to join two grid control problems which are currently treated separately: Voltage Control and Congestion Management.
Context
With the latest update of the National Energy and Climate Plan (NECP 2021-2030), Belgium has committed to an overall 47% reduction in greenhouse gas emissions compared to 2005 and an energy mix including 82209 GWh renewable energy. This increase in renewable injection and the growing electrification of our society results in large challenges for the transmission grid.
Moreover, industry’s transition to net zero is accelerating, as demonstrated by Elia Group’s 2022 study ‘Powering Industry Towards Net Zero’. This highlights how industry’s electricity consumption is due to increase by 50% by 2030 in Belgium. Belgium’s total demand (industrial, households and tertiary sectors) for electricity is therefore due to reach 113 TWh in 2030 (up from 82.1 TWh in 2020; a 38% increase).
Therefore, the grid infrastructure is expected to be operating to its limits, decreasing its operational margins while increasing the demands for protection, automation, and control systems.
The project OptOmni aims to join two grid control problems which are currently treated separately: Congestion Management and Voltage Control.
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Congestion ManagementCongestion Management analyzes the transmitted power of the grid elements and attempts to minimize the overload. Overloads can be reduced by changing the topology or adjusting the active power before and after the bottleneck (redispatch). AC or DC load flow solvers can be used to determine the power, with the former being more accurate. The problem is separated into a convex portion, the redispatch optimization using an optimal power flow, and a non-convex portion, the topology optimization trying to find a topology that minimizes redispatch costs through non-costly grid measures such as switching. Preferably, cheap topological actions are used over costly redispatch actions, and in our prior projects we could demonstrate the viability of a topology optimizer on a full-scale grid.
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Voltage ControlIn Voltage Control, the occurring voltage of the grid elements is considered, which must lie within a certain range to prevent disconnections. Like congestion optimization, this problem includes convex and non-convex measures. The non-convex portion consists of topology measures, the convex portion includes switching of capacitor banks, shunts and other reactive power controls. Topology measures for Voltage Control are currently under-explored, and OptOmni aims to transfer the results achieved on Congestion Management to the topic of Voltage Control.
The overload energy of an individual grid element is defined as the amount of the transmitted power on the element that exceeds the rated power. Congestion Management is usually interested in the overload in the event of an outage. We therefore define the overload energy of the whole grid as a function of all possible individual outages (N-1 cases). For each individual grid element, we consider the overload in the worst N-1 case and add these up to the total overload energy.
The connection of individual network elements is described in the grid topology. Busbars are the nodes of the network. Lines and transformers form the branches, connecting nodes across different locations or voltage levels. Several busbars in a substation can be connected via busbar couplers. For this project we consider the following topology measures:
a) Switching lines or transformers On or Off
b) Changing the assignments of branches and injections to busbars
c) Separating busbars by opening the busbar coupler
Approach
Summary of Results
OptOmni investigated whether congestion management, voltage control, and topology optimisation—today typically addressed in separate operational processes—can be combined into a more holistic optimisation approach. The project confirmed that the main barrier to such integration is computational performance, in particular the runtime of AC load flow calculations when evaluating large numbers of contingencies and topology variants.
The key outcome of OptOmni is the development and validation of DC+, a novel, voltage sensitive linearisation of the AC load flow equations. DC+ bridges the gap between the conventional DC approximation, which is fast but ignores voltage and reactive power effects, and fully converged AC simulations, which are accurate but computationally expensive. Unlike DC, DC+ retains voltage magnitudes, voltage angles, active power, and reactive power, while remaining orders of magnitude faster than full AC load flow solvers.
Extensive validation on IEEE benchmark systems and real Belgian transmission grid data shows that DC+ significantly improves accuracy compared to classical DC approaches, particularly for voltage dependent effects and current loading under N 1 contingencies. At the same time, DC+ scales extremely well and enables the evaluation of millions of contingencies and topology options per second, especially when GPU accelerated.
In parallel, OptOmni delivered important groundwork by aligning operational grid data with open source modelling tools and resolving key modelling inconsistencies. This resulted in a validated, production close modelling baseline that can be reused beyond the project.
While DC+ does not replace fully converged AC simulations, it reliably captures the direction, relative severity, and spatial distribution of violations. This makes it well suited for fast screening, contingency ranking, topology optimisation, and as an inner model for optimisation workflows. DC+ therefore represents a key enabling technology for future holistic grid optimisation and is released as an open source component to support further research and industrial uptake.
Results per work package
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WP1 – Review of Existing Research and Operational PracticeWP1 established the conceptual and operational baseline for the project. It reviewed how congestion management, voltage control, redispatch, and topology optimisation are currently handled within Elia Group and identified key limitations of today’s sequential, tool specific approaches. The analysis confirmed that while each optimisation step is mature on its own, important interactions between congestion, voltage, and topology are not fully captured. This work package clarified where joint optimisation could deliver value and where computational constraints currently prevent deeper integration, providing a clear motivation and scope for the subsequent technical work.
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WP2 – Data Preprocessing and Model AlignmentWP2 focused on enabling the use of production quality operational data within open source grid modelling tools. Significant inconsistencies were identified between exported operational models and their open source representations, particularly in transformer and phase shifting transformer modelling. These issues were systematically analysed and resolved, resulting in close alignment between operational load flow results and open source simulations. This work created a validated, production close modelling baseline that was essential for reliable benchmarking and enabled downstream research. The improvements also benefit other grid optimisation and analysis projects beyond OptOmni.
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WP3 – Accelerated Load Flow Methods and Development of DC+
WP3 addressed the core technical bottleneck of holistic grid optimisation: load flow computation speed under large scale N 1 analysis. Multiple acceleration strategies were investigated, including full precision GPU based AC solvers and machine learning based approaches. While technically feasible, these methods did not deliver sufficient practical performance gains or general robustness for operational use.
As a result, the focus shifted to the development of DC+, a voltage sensitive linearisation of the AC load flow equations. DC+ retains voltage magnitudes, voltage angles, and reactive power—capabilities absent in traditional DC approximations—while remaining orders of magnitude faster than fully converged AC solvers. Extensive validation on IEEE benchmark systems and real Belgian grid data demonstrated that DC+ significantly improves accuracy over DC and reliably captures the direction and relative severity of violations. With efficient parallelisation and GPU acceleration, DC+ enables the evaluation of millions of contingencies per second, making it the central technical outcome of OptOmni.
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WP4 – Combining Topology Optimisation with Voltage and Congestion ConsiderationsWP4 investigated how topology optimisation could be extended beyond congestion management to include voltage related effects. While full AC based optimal transmission switching at operational scale remains computationally infeasible, DC+ enables a practical alternative by providing fast, voltage aware estimates of topology impacts. The work showed that DC+ can support more accurate topology assessment, avoid solutions that appear feasible under DC but lead to voltage problems in AC, and introduce new voltage related criteria for evaluating switching actions. Although full implementation was beyond the project scope, WP4 demonstrated the technical feasibility and expected benefits of voltage informed topology optimisation.
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WP5 – Connecting Convex Optimisation FrameworksWP5 explored how convex optimisation approaches for congestion management and voltage control could be connected within a unified framework. While mathematically straightforward, the inclusion of voltage sensitive N 1 constraints poses major performance and robustness challenges. The project did not fully implement a combined optimiser, but demonstrated that DC+ provides a promising building block to efficiently generate voltage aware distribution factors and linearised contingency constraints. WP5 therefore clarified both the remaining challenges and a credible technical path toward future integrated optimisation workflows.
Partners
Thanks to the Energy Transition Fund of the Federal Public Service Economy for supporting the OptOmni project.
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