Abstract
The foreseen participation of aggregators of prosumers in the electricity markets will require the development of computational tools to support them in the definition and delivery of market products. This paper proposes a new hierarchical model predictive control (MPC) to support an aggregator in the delivery of multiple market products through the real-time control of heterogeneous flexible resources. The hierarchical MPC covers the participation of an aggregator in both energy and secondary reserve markets. The results show that the aggregator is capable of delivering several combinations of energy and secondary reserve without compromising the comfort and preferences of its clients.

Abstract
The adoption of energy transition technologies for residential use is accelerated through incentive designs. The structure of such incentives affects technology adoption patterns, that is, the locations where new technologies are installed and used. These spatial adoption patterns influence network expansion costs and provide indication on potential cross-subsidization between population groups. While until today, most programs have been involuntarily favoring households with high-income and above-average educated population groups, incentive designs are currently under review. This paper presents a spatiotemporal technology adoption model that can predict adoption behavior of residential electric vehicle (EV) chargers and photovoltaic (PV) modules up to a predefined time horizon. A set of EV and PV adoption patterns for nine incentive design combinations are compared in order to assess potential synergies that may arise under orchestrated EV and PV adoption. Effects on adoption asymmetries are evaluated using an Information-Theoretic inequality metric. Results for Continental Portugal show that global network expansion costs can be reduced while minimizing technology adoption asymmetries, if specific incentive designs are combined.

Abstract

Abstract
The multi-energy systems (MES) contain key resources driving the evolution of the future systems. Various components and convertors that are available in a MES make it operationally flexible and a potential source to be deployed in system operation. Like any other resources in the system, the flexibility brought by MES needs to be fairly valued. One of the approaches is through market participation of these resources. In this regard, new agents and trade system need to be defined. This paper studies the interactions of a multi-energy aggregator on various trade levels defined within the multi-energy paradigm. The levels include the upstream multi-energy markets as well as local energy trades such as local resources and flexible demand. The results discuss the increased level of profit due to the availability of multi-energy trade to the aggregator.

Abstract
Vertical load is the power flow between electrical transmission and distribution networks. In the past, large-scale generators connected to transmission systems supplied consumers connected to lower voltage levels across distribution grids. Thus, vertical loads tended to be downward-oriented. This paper presents a spatiotemporal distributed energy resources (DER) diffusion model to analyze vertical load uncertainty resulting from different DER diffusion process representations currently used in the industry and academia. Network planners and operators can use such model to understand the long-term evolution of load at the T/D boundary. The proposal is applied to the Portuguese power system, combining, as first of its kind, highly granulated population census with georeferenced transmission and distribution network datasets. This application analyzes the 20-year evolution of such vertical load flows at the transmission-distribution boundary under a strong uptake of DER embodied in lower voltage levels in Portugal. © 2019 IEEE.

Abstract
The inclusion of new energy management technologies in buildings and increasing integration of distributed energy resources in electricity networks will require new operation and planning approaches from system operators. Currently, distribution network planning is rather inefficient as network assets are oversized to meet the peak demand of a worst case scenario which is unlikely to occur. In addition, flexibility provided by controllable loads is not taken into account at all. This paper presents an innovative approach that integrates the potential flexibility of distributed energy resources in the planning exercise. It incorporates two optimization problems: a low-level one to optimize the operation of controllable resources; and a high-level one based on an OPF that uses the available flexibility to solve network problems. The proposed method allows obtaining costeffective solutions that make a better use of the flexible resources available, avoiding high capital investments in network reinforcement.