Abstract
The adoption of Electric Vehicles (EVs) will revolutionize the storage capacity in the power system and, therefore, will contribute to mitigate the uncertainty of renewable generation. In addition, EVs have fast response capabilities and are suitable for frequency regulation, which is essential for the proliferation of intermittent renewable sources. To this end, EV aggregators will arise as a market representative party on behalf of EVs. Thus, this player will be responsible for supplying the power needed to charge EVs, as well as offering their flexibility to support the system. The main goal of EV aggregators is to manage the potential participation of EVs in the reserve market, accounting for their charging and travel needs. This work follows this trend by conceiving a chance-constrained model able to optimize EVs participation in the reserve market, taking into account the uncertain behavior of EVs and their charging needs. The proposed model, includes penalties in the event of a failure in the provision of upward or downward reserve. Therefore, stochastic and chance-constrained programming are used to handle the uncertainty of a small fleet of EVs and the risk profile of the EV aggregator. Two different relaxation approaches, i.e., Big-M and McCormick, of the chance-constrained model are tested and validated for different number of scenarios and risk levels, based on an actual test case in Denmark with actual driving patterns. As a final remark, the McCormick relaxation presents better performance when the uncertainty budget increases, which is appropriated for large-scale problems.

Abstract
Current developments in heat pumps, supported by innovative business models, are driving several industry sectors to take a proactive role in future district heating and cooling networks in cities. For instance, supermarkets and data centers have been assessing the reuse of waste heat as an extra source for the district heating network, which would offset the additional investment in heat pumps. This innovative business model requires complete deregulation of the district heating market to allow industrial heat producers to provide waste heat as an additional source in the district heating network. This work proposes the application of innovative market designs for district heating networks, inspired by new practices seen in the electricity sector. More precisely, pool and Peer-to-Peer (P2P) market designs are addressed, comparing centralized and decentralized market proposals. An illustrative case of a Nordic district heating network is used to assess the performance of each market design, as well as the potential revenue that different heat producers can obtain by participating in the market. An important conclusion of this work is that the proposed market designs are in line with the new trends, encouraging the inclusion of new excess heat recovery players in district heating networks.

Abstract

Abstract
The power system is facing a transition from its traditional centralized model to a more decentralized one, through the emergence of proactive consumers on the network, known as prosumers. This paradigm shift favors the emergence of new electricity market designs. Peer-to-Peer (P2P) based structures have been gaining prominence worldwide. In the P2P market, the prosumer assumes a more active role in the system, being able to directly trade its energy without the need for intermediaries. This paper contributes with a comprehensive overview of consumer-centric electricity markets, providing background on different aspects of P2P sharing, in particular the inclusion of peer preferences in the electricity trading process through product differentiation. A performance assessment of the different modeled preferences was carried out using key performance indicators (KPIs). Different user preferences under the product differentiation mechanism were simulated. The results demonstrate that consumer-centric markets increase the penetration of renewable energy sources into the network and tend to affect loads flexibility according to the renewable generation.

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
When the price of the energy shared within an energy community is based on a local energy market, it is the responsibility of each participant to bid adequately so that participating provides a larger benefit than not participating. Alternatively, centralized energy community bill minimization may be an option, but a mechanism to share the collective benefits among the members is needed. This mechanism should be fair and easy to explain, no members should be harmed with respect to their individual optimal behavior and should provide the right economic signal. This paper analyses and compares some common pricing mechanisms for the internal compensation for the energy shared among the members of an energy community centrally managed. Simple case examples are used to identify those pricing mechanisms that are fairer and provide the righter economic signals to the participants.