Abstract
This paper aims at contributing to personalize anesthetic drug administration during surgery. This study devel-ops an online robust model to predict the maintenance dose of atracurium necessary for the resulting effect, i.e. neuromuscular blockade, to attain a target profile. The model is based on the patient's neuromuscular blockade (NMB) response to the initial bolus only, overcoming the need for information on the patient's weight, age, height and Lean Body Mass usually associated to pharmacokinetic and pharmacodynamic models. To achieve this, a statistical analysis of the response of the patient to the initial bolus is carried out and a set of variables is established as predictors of the maintenance dose. The prediction is accomplished using Classification and Regression Trees, CART, which is a supervised learning method. Simulated data from a stochastic model for the NMB induced by atracurium is used as training set. All the 5000 doses predicted by the model lead to NMB level between 5% and 10%, which supports the proposed predictive model since it is clinically required that the steady state NMB level lies between this two values. The methodology is applied both to simulated and to clinical data sets and is found appropriate for online dose prediction.

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
Considering the Brazilian energy policy's future, the perspective of a more decentralized energy system must be accounted for in the face of technological, business, and energy matrix changes. Therefore, the prosumer's figure combined with new Business Models (BM) brings opportunities and challenges for the sector. This paper aims to solidify knowledge, identify and understand the main regulatory barriers and enablers for the development of prosumers and prosumer-driven BMs in the Brazilian energy market. A comprehensive review of existing regulations provides a starting point for improving the relevant legal frameworks for prosumers' aggregation. Then, an analysis of innovative BMs in the Brazilian regulatory framework is carried out, seeking to guide the decisions for the country to develop its political and regulatory environment in the future. The paper concludes with policy recommendations to promote prosumers aggregation in the Brazilian energy sector. We conclude that the main barriers to prosumers' integration are of regulatory and technological nature, and the exploration of innovative BMs is crucial for the sector development. Redefining the role and responsibilities of utilities is a key factor, together with exploring collective self-consumption.

Abstract

Abstract
Demand Response (DR) programs are essential for easing end-user demand on the power system, adding benefits across the power sector by reducing peak demand and power flow congestion. With the modernization of power grids, DR programs ensure the integration of Distributed Energy Resources (DER) in a controlled manner through Advanced Metering Infrastructure (AMI), which enables communication between grid operators, prosumers and consumers. However, the diversity of DR programs, the spread of DERs, the advent of prosumers, and the several types of power trading among system entities make network and market operation more complex. In this context, optimization methods have been widely applied in distribution grids and market operation, assisting in the decision-making of DER management, prosumer's and consumers' welfare, and DR program applications. This work will address the main market models comprising DR programs to assess opportunities in prosumers' decision-making with the help of optimization tools. Thus, different optimization techniques are introduced that have been addressed in the literature aiming at the application of market models, taking into account the pro -sumer framework. As a whole, this review paper aims to present the main perspectives of energy market models with demand-side management actions considering the prosumer design.

Abstract
In recent years, there has been an increase of Renewable Energy Sources (RES) in energy markets that has to lead their agents to become more proactive. In this scenario, a market structure based on Peer-to-Peer (P2P) transactions is very promising but presents challenges for the network operation. A critical challenge is to ensure that network constraints are not violated due to energy trades between peers and neither due to the use of reserve capacity. In this paper, it is proposed a new iterative sequential approach for energy and reserve P2P market that ensures the feasibility of both energy and reserve transactions under network constraints. The methodology considers the interaction between the prosumers and the Distribution System Operator (DSO) in making the final market/operation decision and can be integrated into the existing distribution system. The proposed approach includes the estimation of reserve requirements based on the RES uncertain behavior from historical generation data, which allows identifying RES patterns. The proposed model is assessed through a case study that uses a 14-bus system, under the technical and economic criteria. The results show that the approach can ensure a feasible network operation encompassing energy and reserve markets.