## 2 Materials and Methods  
As mentioned in the previous sections, the simulations have been done by an optimization model that provides the economic dispatch and clearing of the day-ahead electricity market. The model developed in a recent paper [15] is further extended to incorporate the impact of bilateral contacts, which is a supplementary mechanism to the energy exchange that clears the wholesale market. In Greece, the wholesale market is currently organized as a mandatory pool, where all producers and retailers are obliged to participate. Producers submit energy offers for their power plants, while retailers submit load declarations for the consumers they represent, while traders in the interconnections submit bids for imports and exports. Public Power Corporation (PPC) is a Dominant Power Producer (DPP), owning nineteen thermal plants, fourteen lignite and five natural gas plants, while Independent Power Producers (IPPs) own five natural gas combined cycle plants. The dominant role of DPP is expected to be eliminated, to enhance competition. For environmental reasons, six lignite plants will complete their remaining operating hours within 2019, so practically they will be decommissioned, while binding offers for the purchase of three DPP owned lignite units are expected to be submitted in early 2019. Therefore, in the examined scenarios, DPP owns five lignite plants of 1.5 GW installed capacity and five natural gas plants of 2.6 GW, while IPPs own 0.8 GW of lignite plants and 2.1 GW of natural gas plants. IPPs also own 0.4 GW of natural gas plants, characterized as an open cycle or Combined Heat and Power (CHP). Moreover, DPP own 3.2 GW of big hydro plants. Those figures show that DPP still has a dominant role in power production, besides the latest developments. Moreover, the adoption of the \"target model\" will allow bilateral contracts among producers and retailers, which is the focus of the paper. The decision to cap the allowed bilateral contracts is a crucial issue for decision maker by the regulator, expected to take place within 2019. The model is developed in the Generic Algebraic Modelling System (GAMS) environment [19], supplemented by an interface for running the model and showing the results. Figure 1 provides the interface of the model developed, showing the hourly energy mix of a representative typical day. The model developed is ready for use by market participants in the real market. The model incorporates bilateral contracts with committed generating capacity from producers, as well as dynamic bidding strategy per market participant. Therefore, market participants have the option to use bilateral contracts or to participate in voluntary energy exchange. However, in the case with a participant with a dominant position, the level of allowed bilateral contracts (defined as the allowed share, in percentage, of their load in the retail market that can be met by its power units), is important for the wholesale market price and the mix of rest participants. We, therefore, examine how the level of bilateral contracts for the market participant can affect the electricity market. The formation of a bidding strategy is a crucial issue, as it strongly affects model outputs. [PERSON] et al. [20] proposed a model for an optimal bidding strategy of an energy hub, employing specific features, such as multi-disciplinary and flexibility. [PERSON] et al. [21] presented an optimal bidding strategy from the consumption side, by examining the active participation of an aluminum electrolysis company on the primary balancing market for the provision of ancillary services on demand, such as balancing power. [PERSON] et al. [22] proposed an optimal bidding strategy on the production side, by examining how wind power producers can be active participants in pay-as-bid power markets. In the paper, we choose to form a dynamic bidding strategy, compared to the identification of an optimum strategy, as the focus of the paper is not the maximization of benefits for a producer or a consumer.