This paper explores a revenue maximization problem for distributed energy resources in a local day-ahead and balancing market. The local market creates opportunities for competition among distributed energy resources, however it may also lead to exercising market power. In the day-ahead market, the strategic revenue maximization of the distributed energy resources is modelled through a bi-level optimization. The upper-level in the bi-level optimization is from the strategic distributed energy resource’s perspective and the lower-level problem is from the local market operator’s perspective. The balancing market (where there is perfect competition) is modelled by the shrinking rolling horizon approach. A wind farm with a storage system is considered as a case study of a strategic distributed energy resource to evaluate its profitability within the proposed revenue maximization problem. The revenue of the wind farm in the local market is compared with the one in a (business-as-usual) centralized market where it cannot exercise market power. Sensitivity analysis regarding the effect of changing the distribution system parameters e.g. the branch resistances and the loads, on the revenue of the wind farm and its bidding behaviour is performed. Moreover, the role of the storage system on the revenue of the wind farm is studied. Results show that an overloaded or weak distribution system will positively influence the strategic position of the wind farm. Finally, it is shown that depending on the existence of market power, a storage system can bring extra revenues for the wind farm, by hedging against its uncertain output.
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Farrokhseresht et al. (2020) studied this question.
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