• Energy Research

n HVDC grid in the North-Sea is considered to have a high potential to aid the energy transition in Europe.n HVDC grid in the North-Sea is considered to have a high potential to aid the energy transition in Europe.A High investment cost and operational challenges are the major roadblocks in its realisation. This paper proposes a demonstration grid in the North-Sea and shows that it is a financially viable project. A sensitivity analysis corresponding to line capacities and base prices is performed. Recommendations for the construction and operation of such a grid are made from the regulatory stand point.

This paper presents a method to optimize equipment investments in multizonal transmission systems, considering spatial properties of the areas of focus. Together with a probabilistic technique for assessing nodal injection capability, the method in the paper completes the methodology of a long term transmission system planning tool. Transmission topology, line route and technology are optimized through iterative application of linear integer programming and Dijkstra's shortest path algorithm. By optimizing the transmission route, the spatial properties of the area of focus are taken into account, which in turn can significantly influence the installation costs of transmission equipment. The optimization method considers both AC and DC technology and takes the N-1 security criterion into account.

HVDC technology has gone through major developments in the past decades, resulting in higher power ratings, increased efficiency, and the availability of effective means for HVDC grid protection. These developments have made overlay HVDC grids a viable option to accommodate the shift towards a carbon-free power system by enabling optimal use of renewable resources. In particular, overlay HVDC grids greatly increase the prospects of building (trans-)continental supergrids to facilitate global economic development. Notwithstanding the significant progress made over the last decades, overlay HVDC grids still encounter challenges due to the distance and amount of power involved. This paper focuses on analyzing the readiness of the current technologies and the challenges associated with overlay HVDC grids. An in-depth analysis is carried out to evaluate the applicability of current technologies for overlay HVDC grids. Based on the review of recent R&D efforts, the gaps and challenges towards the realization of a global HVDC grid are summarized.

For market-based procurement of low-voltage flexibility, DSOs identify the amount of flexibility needed for resolving probable distribution network (DN) voltage and thermal congestion. A framework is required to avoid over or under-procurement of flexibility in the presence of uncertainty. To this end, we propose a scenario-based robust chance-constrained (CC) day-ahead flexibility needs assessment (FNA) framework. The CC level is analogous to the risk DSO is willing to take in flexibility planning. Multi-period optimal power flow is performed to calculate the amount of flexibility needed to avoid network issues. Future uncertainties are considered as multiple scenarios, which are utilized to solve the flexibility needs assessment optimal power flow (FNA-OPF) problem. The FNA tool calculates the temporal and locational ramp-up and ramp-down flexibility needs of the DN. We also propose a Pareto optimal mechanism for selecting CC level to reduce flexibility needs while reducing DN congestion. Zonal clustering of a DN feeder is performed using electrical distance as a measure, with spatial partitioning and silhouette coefficient. Further, a zonal and nodal bid matching algorithm is proposed, where alternate flexibility bids in the same zone are identified in case nodal matching is not exact, compared to the calculated FNA. The proposed bid matching algorithm assists the system operator in bid selection by avoiding rerunning power flow evaluations. The zonal and nodal bid matching leads to more than 43% additional reduction of probable network incidents compared to naive nodal bid matching. Furthermore, we also calculate FNA for a real German DN with 646 nodes and 331 consumers.

This work develops a mathematical formulation to determine the combinatorial search space of the Offshore Wind Transmission Optimization Problem (OWTOP). The model accounts for Capital Expenditures (CAPEX), Corrective Maintenance (CM), losses and Expected Energy Not Transmitted (EENT) and determines the optimal radial transmission system topology to connect a number of Offshore Wind Power Plants (OWPPs) to the shore. The model also considers the stochastic nature of wind. In this context a greedy search algorithm is developed capable of finding the globally optimal solution for the location of offshore substations (OSSs), sizing of the transmission infrastructure and topological layout. Rather than a single optimal solution, the algorithm finds a solution space of feasible topologies, bounded from below by the optimal radial solution. The algorithm is applied to 4 test cases including one based on the Belgian North Sea area. It is shown to outperform a traditional Transmission Network Expansion Problem (TNEP) formulation both in computational speed and solution quality.

This work develops a method of quantifying the effect of adding meshed connections to radial network topologies used for offshore extraction. The method accounts for Capital Expenditures (CAPEX), Corrective maintenance (CM), losses and Expected Energy Not Transmitted (EENT). The stochastic nature of wind is also accounted for. The method is applied to a statistically significant randomly generated population of Offshore Wind Power Plant (OWPP) pairs. Analysis of both Medium Voltage (MV) and High Voltage (HV) bus meshing is performed. It is demonstrated that in the two OWPPs case meshed connections have a narrow but significant region of applicability. Further, the method is applied to a system of 6 wind farms and compared to the lowest cost radial connection, using a number of different planning horizons. It is shown that the optimal radial topology is no longer the clear choice as the development horizon increases.

The FlexPlan Horizon2020 project aims at establishing a new grid-planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the Clean Energy for all Europeans regulatory package of the European Commission. FlexPlan creates a new innovative grid-planning tool whose ambition is to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of the best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030, 2040, 2050), incorporation of a full range of cost–benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly renewable energy sources (RES) and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. FlexPlan will end up formulating guidelines for regulators and planning offices of system operators by indicating to what extent system flexibility can contribute to reducing overall system costs (operational + investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper provides a complete description of the modelling features of the planning tool and pre-processor and provides the first results of their application in small-scale scenarios.