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Moving towards regional Supergrids, an increasing number of interconnections are formed by High Voltage Direct Current (HVDC) lines. Currently, in most regions, HVDC losses are not considered in market operations, resulting in additional costs for Transmission System Operators (TSOs). Nordic TSOs have proposed the introduction of HVDC loss factors in the market clearing algorithm, to account for the cost of losses and avoid HVDC flows between zones with zero price difference. In this paper, we introduce a rigorous framework to assess the introduction of loss factors, in particular HVDC loss factors, in nodal and zonal pricing markets. First, we focus on the identification of an appropriate loss factor. We propose and compare three different models: constant, linear, and piecewise linear. Second, we introduce formulations to include losses in market clearing algorithms. Carrying numerical tests for a whole year, we find that accounting only for HVDC or AC losses may lead to lower social welfare for a non-negligible amount of time. To counter this, this paper introduces a framework for including both AC and HVDC losses in a zonal or nodal pricing environment. We show both theoretically and through simulations that such a framework is guaranteed to increase social welfare. [ABSTRACT FROM AUTHOR]

The concept of segmented AC power systems interconnected by means of HVDC is becoming more and more significant for many cases worldwide. Such systems already exist and will become more complex with the increasing emergence of HVDC links and grids. The concept of a grid composed of multiple subgrids motivates the need to define the governing roles of Interconnecting Power Converters (IPC) which connect the different subgrids. Such IPC can have various operation modes which are presented and analyzed in this paper. In addition, the principles of operation needed for each individual subgrid and for the overall system are introduced and discussed. The resulting fundamental equations are outlined and combined in a power flow formulation of the overall system. A simple case study is presented to illustrate the power flow formulation in a grid of multiple subgrids, also introducing example dynamic simulations of transitions between different operating points. [ABSTRACT FROM AUTHOR]

The concept of adjustable combinatorial products within the scope of the day-ahead electricity market is introduced in this paper. These adjustable products comprise simple and linked profile block offers/bids, with a variable energy quantity profile during the block periods. In the proposed formulation, these blocks can be partially cleared, namely, the indivisibility of the classical profile blocks that are present in European markets is relaxed. This flexibility allows the elimination of paradoxically accepted and rejected blocks and, thus, the elimination of iterative heuristic procedures for their handling. Such modeling is not possible as a mixed-integer linear programming problem, due to the inherent indivisibility denoted by the use of binary variables. Additionally, advanced profile bids are formulated for demand entities, called “joint demand profile block bids” in this paper, which involve not only inter-temporal relations, but also spatial relations with each other. This two-dimensional relation between demand profile blocks is novel and is deemed feasible with the model presented here. These advanced profile orders are incorporated in a day-ahead market problem, formulating a mixed complementarity problem model, which is solved using commercial solvers. The model is validated using the IEEE RTS-96 system; nevertheless, its scalability to large real-world power systems is straightforward. [ABSTRACT FROM PUBLISHER]

Securing profits from energy, reserve capacity and balancing markets is critical to ensure the profitability of battery energy systems (BES). However, the intimate connection between offers on these trading floors combined with the limited energy storage capacity of BES renders its scheduling very complex. In this paper, we develop a bilevel optimization problem for strategic participation of a BES in the day-ahead energy-reserve and balancing markets, improving the state-of-the-art by (i) considering the conditional-value-at-risk; (ii) ensuring the real-time feasibility of the obtained day-ahead schedule; (iii) addressing the operational underperformance risk stemming from inaccurate battery modeling. In a case study, we illustrate how the proposed model allows risk-averse BES owners to hedge their day-ahead position without jeopardizing their expected profit, while ensuring the feasibility of their day-ahead schedule. [ABSTRACT FROM AUTHOR]

The integration of the spot electricity markets in Europe shall lead to multi-area power exchanges that will substitute the local markets. In such scheme, market prices are affected by physical (e.g., network) constraints, yet they should sometimes follow regulatory policy rules, which do not necessarily reflect or depend on physical characteristics. In some cases, complex pricing rules should be implemented, which impose price discrimination for supply and demand entities within the same area. The methodology presented in this paper enables the balancing of supply and demand in a multi-area market considering energy and reserve bids, under complex pricing rules, which mix energy and reserve prices. A demand bid corresponds to the whole cost a demand entity is willing to pay for its participation in the energy market, including the cost for the procurement of the necessary reserves. The approach attains price integration of energy and reserves markets, simultaneous settlement of energy and reserves, and significant decrease of the payments through the uplift accounts. The main principle is the formulation of a mixed complementarity problem for the system equilibrium conditions, in which supply and demand are associated to explicitly or implicitly defined prices, which may be different even in the same zone. [ABSTRACT FROM PUBLISHER]