arXiv subjects

Zacharie De Grève

Publications and source records attributed to Zacharie De Grève.

6 recordsLinked to original sources

arXiv2026

On the Complementarity of Shared Electric Mobility and Renewable Energy Communities

Driven by the ongoing energy transition, shared mobility providers are emerging actors in power systems aiming to shift combustion-based vehicles towards electric ones. Meanwhile Energy Communities are deployed to promote investment in distributed renewable production and enhance the local usage of it. The complementarity in their electrical demand, enhanced by a coordinated operational planning, can help both actors reduce the electricity supply cost. Considering this original collaboration, this paper presents a Mixed-Integer Quadratic Programming problem which jointly optimizes the EC members and EVs flexibility usage to take advantage of the local production. Besides economic benefits comparison, authors analyses the impact of grid tariffs and bi-directional charging on the distribution network. Results from a Belgian mobility case study show that coordination can help reducing the yearly cost up to 15.6% compared to their stand-alone situation and that it may reduce by 30.8% the stress on the substation transformer when subject to peak penalties from the grid operator.

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arXiv2026

A Decision-Making Framework for New Member Integration in Renewable Energy Communities under Prospect Theory

This paper introduces an original approach to an underexplored issue: the integration of a new member into an existing renewable energy community. The problem involves actions with both long-term consequences, such as investment and local pricing, and short-term operational ones, such as daily energy and financial flow management. Long-term decision-making is modeled using finite extensive-form game theory, while short-term day-ahead scheduling decisions are formulated as a generalized Nash equilibrium problem. This framework explicitly accounts for heterogeneous stakeholder preferences and bounded rationality, modeled through prospect theory. The proposed approach is flexible and general, making it applicable to various objectives and decision-making contexts in the evolving landscape of renewable energy communities. It is applied to two communities with five members, eleven candidate users, multiple preference configurations and a comparison with heuristic metrics from the literature is also addressed. The model also exhibits that equilibrium outcomes and stakeholder behavior are influenced by the order of decisions, their preference criteria, and prospect theory parameters particularly the reference point selection.

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arXiv2026

Explicit Reward Mechanisms for Local Flexibility in Renewable Energy Communities

Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes.

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arXiv2023

Valuing the Electricity Produced Locally in Renewable Energy Communities through Noncooperative Resources Scheduling Games

We propose two market designs for the optimal day-ahead scheduling of energy exchanges within renewable energy communities. The first one implements a cooperative demand side management scheme inside a community where members objectives are coupled through grid tariffs, whereas the second allows in addition the valuation of excess generation in the community and on the retail market. Both designs are formulated as centralized optimization problems first, and as non cooperative games then. In the latter case, the existence and efficiency of the corresponding (Generalized) Nash Equilibria are rigorously studied and proven, and distributed implementations of iterative solution algorithms for finding these equilibria are proposed, with proofs of convergence. The models are tested on a use-case made by 55 members with PV generation, storage and flexible appliances, and compared with a benchmark situation where members act individually (situation without community). We compute the global REC costs and individual bills, inefficiencies of the decentralized models compared to the centralized optima, as well as technical indices such as self-consumption ratio, self-sufficiency ratio, and peak-to-average ratio.

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arXiv2022

Embedding Dependencies Between Wind Farms in Distributionally Robust Optimal Power Flow

The increasing share of renewables in the electricity generation mix comes along with an increasing uncertainty in power supply. In the recent years, distributionally robust optimization has gained significant interest due to its ability to make informed decisions under uncertainty, which are robust to misrepresentations of the distributional information (e.g., from probabilistic forecasts). This is achieved by introducing an ambiguity set that describes the potential deviations from an empirical distribution of all uncertain parameters. However, this set typically overlooks the inherent dependencies of uncertainty, e.g., spatial dependencies of weather-dependent energy sources. This paper goes beyond the state-of-the-art models by embedding such dependencies within the definition of ambiguity set. In particular, we propose a new copula-based ambiguity set which is tailored to capture any type of dependencies. The resulting problem is reformulated as a conic program which is kept generic such that it can be applied to any decision-making problem under uncertainty in power systems. Given the Optimal Power Flow (OPF) problem as one of the main potential applications, we illustrate the performance of our proposed distributionally robust model applied to i) a DC-OPF problem for a meshed transmission system and ii) an AC-OPF problem using LinDistFlow approximation for a radial distribution system.

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arXiv2020

A New Cooperative Framework for a Fair and Cost-Optimal Allocation of Resources within a Low Voltage Electricity Community

This paper presents an original collaborative framework for power exchanges inside a low voltage community. The community seeks to minimize its total costs by scheduling on a daily basis the resources of its members. In this respect, their flexibility such as excess storage capacity, unused local generation or shiftable load are exploited. Total costs include not only the energy commodity, but also grid fees associated to the community operation, through the integration of power flow constraints. In order to share the community costs in a fair manner, two different cost distributions are proposed. The first one adopts a distribution key based on the Shapley value, while the other relies on a natural consensus defined by a Nash equilibrium. Outcomes show that both collaboration schemes lead to important savings for all individual members. In particular, it is observed that the Shapley-based solution gives more value to mobilized flexible resources, whereas the Nash equilibrium rewards the potential flexibility consent of end-users.

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