Abstract

Abstract
This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer's individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers' energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer's new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

Abstract
Prosumers can organize themselves in collective self-consumption (CSC) structures and renewable energy communities (RECs) to share energy they produce locally. In addition, through their contracted balancing responsible party (BRP), i.e., retailer and aggregator, they could become flexibility providers for system services to solve, for example, local grid constraints. Since CSC and REC structures are progressively being regulated in many countries, local energy markets (LEMs) and local flexibility markets (LFMs) to be developed with these structures should find the way to comply with existing CSC rules to settle energy transactions and flexibility activation, both, locally and with the wholesale markets (WSMs) settlement, and the existing barriers and regulatory improvements should be identified to allow future implementations. Indeed, the integration of local and WSMs is still a matter of development, demanding innovative solutions, one of the main issues being, for example, the impact of the flexibility activation by one BRP into another BRP's expected delivery commitment in the WSM. This work proposes innovative designs for LEM and LFM based on common CSC rules of existing regulations, and a conceptual approach to integrate them together and with the WSM balancing responsibilities of the BRPs involved, identifying existing regulatory barriers. While many LEMs in the literature operate as WSMs, with future markets and delivery commitments for prosumers, we propose the use of a post-delivery LEM that can be cleared even after the delivery of energy, which strongly simplifies prosumers participation avoiding the need of these a priori unrealistic commitments. The business model, the main roles involved, and the contractual framework to connect the BRPs while allowing prosumers to freely contract the BRP of their choice for both energy supply and flexibility provision are described and can serve as a guide for future regulatory improvement of the common regulatory frameworks.

Abstract
This work exploits the nexus of agricultural activities, water, and electrical and thermal energies to propose a framework to develop efficient circular renewable energy communities for the agricultural sector, by analyzing and optimizing the resources and the energy flows among them, profiting from the energy sources available. In this framework, local industries and agricultural facilities can invest in solar PV plants, livestock residues digestors to produce biogas, and cogeneration plants to supply the thermal and electrical energy needs. A simplified case study is presented, based on using biomass residues from livestock processed in an anaerobic digestor to produce biogas for a cogeneration plant. Their optimal capacities are computed considering the optimal supply of thermal and electrical energy needs and the supply from the public electricity and gas grids.

Abstract
This paper presents a new hybridization approach to improve CEVESA, a multi-zonal hydro-thermal equilibrium model for the joint dispatch of energy and secondary reserve capacity for the Iberian Electricity Market (MIBEL). Like similar fundamental models, CEVESA provides market prices that typically show an average systematic bias compared to real market prices. This is because these models do not always capture the true variable production costs of the generation units or the additional markups that generation companies may include in their pricing strategy. Based on real market outcomes, this paper proposes a new methodology built on a previous hybridization approach that estimated a constant monthly markup per thermal offering unit [1]. This new methodology is based on a functional estimation of the offering unit cost (or bidding price), using as input the initial CEVESA production costs based on the fuel and emissions commodities' prices, correcting the power plants' markup.

Abstract
In deregulated electrical systems, production schedule for power plants is the result of an auction process. In the Spanish case, this schedule includes two main concepts: energy production (to be actually produced) and secondary reserve (to maintain available). The generation company faces the problem of converting energy schedule into a power schedule, respecting the reserve schedule as well as technical constraints, and trying to accomplish different goals: to minimise the production costs, to obtain smooth shapes for the power schedules and to optimise eventual compensation in schedules. A weighted goal mixed integer programming model with a real-size application to deal with this problem is presented.