Modelling and assessing the impact of the DSO remuneration strategy on its interaction with electricity users

Abstract

This paper presents a simulation-based methodology for assessing the impact of employing different distribution system operator's remuneration strategies on the economic sustainability of electrical distribution systems. The proposed methodology accounts for the uncertainties posed by the integration of distributed electricity generation resources, and the roll out of smart meters. The different remuneration strategies analysed in this paper include notably new distribution tariffs based on individual peak power consumption and time-dependent rates that are contingent on the time of energy consumption, both requiring smart meters to work. The distributed electricity generation resources are modelled through an optimisation framework and an investment decision process that gradually deploys household photovoltaic installations depending on their profitability and the electricity charges, including the distribution rates. The impact of the distribution system operator's remuneration strategy is measured by an accurate modelling of the remuneration mechanism of this entity, which can adapt to various distribution tariff designs. We analyse this impact over a discrete time horizon. Our methodology is illustrated with several examples of distribution tariffs including old-based on energy consumption or on per-connection fees-as well as new-based on power consumption or time-of use fees-designs. Finally, we provide a comprehensive sensitivity analysis of the proposed simulation environment to the main parameters of the methodology.

Financial Optimization of Renewable Energy Communities Through Optimal Allocation of Locally Generated Electricity

“…Equation ( 9) computes the optimised allocated production. Equation (10) sets the total allocated production equal to the total production sold by the REC members. Equation (11) limits the production sold to the total available production.…”

“…This type of approach, however, demands for regulatory frameworks that effectively address the new needs of final consumers, who can now be electricity generation owners (i.e., prosumers). Indeed, the lack of adequate frameworks for consumers and prosumers challenges the power system operation, as shown in [7]- [10], and may hinder the integration of decentralised generation [11]. A potential solution to this problem is the creation of local consumercentric electricity markets, where consumers and prosumers can trade electricity locally, replacing partial or totally their traditional retailer contracts [12], [13].…”

Network tariffs and the integration of prosumers: The case of Wallonia

“…We rely on a multi-agent model to simulate the impact of distribution tariffs on residential consumers' investments in PV modules and batteries. The model is introduced in Manuel de Villena et al (2019) and described in further details in Manuel de Villena et al (2021). Appendix 7.2 contains the mathematical formalization of the simulator.…”

“…This MILP returns the LVOE of each potential prosumer, which is the objective function, as well as the optimal sizing configuration leading to this LVOE, given the input parameters specified previously. For an accurate description of these parameters the reader is referred to Manuel de Villena et al (2021). For simplicity, let MILP(inputs) denote the general objective function of the MILP presented in the previous section, depending on the inputs.…”

“…This paper analyzes how different distribution tariff regulations impact the consumption, production, and (possibly) storage behaviors of residential households. For this purpose, we rely on a tariff simulator developed by Manuel de Villena et al (2021) and we use regional-specific load and solar irradiance profile curves to apply the model to the case of Wallonia. Compared with other simulators used in Kubli (2018) or Schittekatte et al (2018) to study a related research question, we use an agent-based modeling approach incorporating the region-specific consumption and production profiles of several thousands of heterogeneous households.…”