Transmission Expansion Planning of Transnational Offshore Grids: A Techno-Economic and Legal Approach Case Study of the North Sea Offshore Grid

The new energy policy of the European Union (EU) with the core objectives of competitiveness, reliability and sustainability, has driven Europe into a transition towards a low carbon & sustainable electricity supply systems. Under the new policy, the European energy systems are pursing two major objectives. First is to shift the focus from national to regional or (perhaps) a European level with the ultimate goal of introducing regional markets that facilitates cross-border power trades. Second, is to incorporate large renewable energy sources into the power systems to best exploit the energy resources. In this regards, special attention is oriented towards the development of the offshore gird in the North Sea region where offshore wind is abundant and has potential to become major energy source in the area. This thesis looks into transmission expansion planing in the North Sea region. It presents a market based approach to solve a long-term transmission expansion planning for a meshed VSC-HVDC offshore grid that connect regional markets. The main goal here is to determine the grid design that enables harnessing the offshore wind energy most efficiently, at the same time, creating capacity for conducting cross-border power exchange. Development of an offshore grid in the North Sea can encounter various technical, legal and economic barriers. Consequently advanced planning frameworks are required that enables accounting for these issues. The methodology proposed here provides a framework to investigate the impact of each of these factors on the development of offshore infrastructures. More precisely, the contributions of this thesis can be summarized as follows: • Static Transmission Expansion Planning framework (STEP) In Chapter 5, I have proposed a multiple time-period static transmission expansion planning framework that is applicable to VSC-HVDC meshed grids. I have shown that the analytical solution to the problem gives the pricing mechanism that expresses the relationship between the electricity price of different zones and the congestion charges associated with the interconnectors between them. It is an extension of the work of Schweppe et al. that has been proven for and applied to VSC-HVDC grids. The proposed formulation includes investment recovery through congestion revenues as an implicit strict equality constraint. It, therefore, computes the expansion plan, such that the investment capital will be fully paid off through congestion revenues by the end of the chosen lifetime of the infrastructure. The framework determines the topology, transmission capacities and the power flows through the offshore grid, and the resulting distribution of social welfare among the price zones. By combining both flow-constraints and investment recovery-constraints and working with historical market data, the framework can deliver useful results that demonstrate how onshore price zones could benefit from an optimal grid design. • Iterative clustering methods for computation feasibility The optimization framework proposed in Chapter 5 was intended to be driven by historical market-data in the form of hourly regional cost curves. The dimensionality of the search space and the computational intensity of the proposed optimization algorithm make the problem intractable. It was desirable to identify and work with only a subset from the total set of operating states. I developed an iterative algorithm that combines an unsupervised clustering technique with the proposed optimization tool to cope with the computational burden of the large-scale optimization problem. Automatic space transformation and clustering were performed to select a subset of representative hourly operating states. The number of samples in the subset was adjusted in order to match the congestion-induced revenues to that of the full data set. This ensured that essential information was not lost. The framework, thus, balances the need for reasonable computation times against the benefits of a model that allows multiple time-periods (as defined by zonal prices and wind power production combinations) and obtains realistic results. Several clustering algorithms (including K-means) and feature reduction techniques (such as Principal Component Analysis (PCA)) have been used in investment planning analysis. Their combination has also been explored in literature. However, this is the first time that an unsupervised PCA/clustering technique has been combined with an optimization tool to refine the clustering results. • StaticWind and Transmission Expansion Planning framework (SWTEP) Chapter 6 describes a novel co-optimization wind and transmission expansion framework applicable to VSC-HVDC meshed grids. This is an extension of the static framework presented in Chapter 5 that adds wind to the TEP formulation, while implementing support schemes, which inherently induce a deviation from perfect competition. This results in a fundamental contradiction between the structure of the competitive market and the nature of support policies. The novelty of the work presented in Chapter 6 is that it has limited the market distortion by excluding the support payments from the market clearing process. To do so, I have proposed a formulation that divides the initial investment of the offshore wind infrastructure into subsidized and unsubsidized parts. Thus, the objective of the optimization problem was to maximize sum of incremental social welfare of all regions at all times, minus the aggregated investment cost of offshore transmission infrastructure and the investment cost of building the offshore wind farms that has not been covered through the support payments. The proposed framework enables the impact of implementing two types of feed-in premium support schemes (i.e., generation-based and capacity-based) to be accounted for in the final development of the grid. The goal of this chapter was to investigate the performance of the two feed-in support policies to verify if investment recovery would be fulfilled under a certain support scheme design. In addition, an ‘optimal’ support level and offshore wind support tariff rate were determined. The analytical solution to the optimization problems confirms the complete recovery of the investment cost of transmission infrastructure. In addition, under the assumption that no offshore wind was curtailed, the revenues collected from market sales of offshore wind farms can pay off the unsubsidized part of the wind farm investment, regardless of the payment basis (generation-based or capacity-based). • Dynamic Transmission Expansion Planning framework (DTEP) In Chapter 7, I have proposed a market-based, multiple stage, multi-time period dynamic transmission expansion planning framework for a meshed offshore grid to connect upcoming offshore wind farms to multiple onshore markets. The main contribution of this framework is that it enables accounting for delays in the construction and implementation of offshore infrastructures, including wind farms and transmission systems. Delays can occur mainly due to legal barriers associated with differing permitting criteria in an international context, but also due to market maturity and supply chain issues. The timing of delays in grid, market and wind farm developments are set exogenously in the model. This is an extension of the work presented in Chapter 5 in which the whole offshore grid was assumed to be built in one instant. The final results include the optimal grid topology, transmission capacities, construction timing and the resulting remuneration and distribution of the social welfare increase and financial benefit among the various onshore price zones. The analytical solution to the optimization problem gives the pricing mechanism that is consistent with the AC onshore counterpart. The proposed market mechanism facilitates the integration of a multi-terminal VSC-HVDC offshore grid into the existing AC grid. In addition, the analytical solution confirms the investment recovery through congestion revenues, regardless of the number of investors that are involved. In the case of multiple investors, an independent financial entity is required that collects the transmission revenues from the grid operators and distributes them appropriately amongst the investors. Under this regulatory assumption, the investment recovery of every cable of every interconnector will be completely fulfilled within the desired economic lifetime.