This PhD thesis consists of two parts. The first part focuses on the development of energy scheduling and power quality improvement algorithms (energy management systems) for small-scale smart grids, known as microgrids. A microgrid may comprise distributed energy resources (photovoltaic, wind, storage, etc.) and controllable loads (electric vehicles, heating, ventilation, and air-conditioning, etc.). An energy management system (EMS) decides the optimal planning and operation of methods to control both energy production and consumption in a microgrid aiming at total cost reduction and improvement of energy efficiency. In order to investigate the impact of renewable generation and load unpredictability on EMS operation, the photovoltaic production and the electric load of the microgrid are modeled considering a broad number of possible scenarios. We further extend the EMS by developing an integrated tool for the cooperative evaluation of optimal demand-response operation in a microgrid combined with a concurrent power quality assessment. The unique characteristic of the developed tool is that it does not only provide the optimal solution based on a specific operational objective, but it also ensures power quality compliance for all microgrid components. In addition, we develop a binary-based framework (incorporated in the optimization algorithm) to model the potential energy interaction between the microgrid and any other interested entity (e.g., the distribution system operator or an electricity utility company). This energy interaction may include flexibility and/or additional ancillary services. The framework operates on the basis of financially - incentivized power signals requests. Numerical results demonstrate the efficacy of the extended energy management integrated tool in both achieving the economic objectives in scheduling microgrid's operation and in effectively mitigating its power quality issues. The second part of this thesis focuses on the design of a local energy market which consists of consumers, prosumers (customers who actively manage their own consumption and production of energy), renewable producers, and energy storage (ES) owners. We specifically investigate the position and the role of ES in such local energy markets (in day-ahead and real-time layers) by implementing, among others, the concept of physical storage rights (PSRs). As a market product, PSRs are provided by an ES owner and enable the local market participants to access the ES. First, we investigate how ES owners can monetize their unused capacity in the form of PSRs, while other market participants aiming at additional flexibility, compete to obtain the PSRs on a short-term basis. Afterwards, we examine whether the passive utilization of ES in the form of PSRs can result in a less risky but the same profitable strategy for the ES owner, evaluating at the same time how the total system cost is affected. In addition, we investigate how the decisions of the rest market participants are affected by the position of ES in the local market. The most remarkable result to emerge from the simulations is that in a risk-neutral setting, the payoff does not depend on whether a storage owner maximizes expected profit from inter-temporal arbitraging or from selling PSRs. Each business model is evaluated numerically through several illustrative case studies.

Collaboration with the ELMA group of DTU with As. Prof. Jalal Kazempour, Prof. Pierre Pinson and Dr. Athanasios Papakonstantinou leading to a publication of a journal paper in IEEE Transactions on Power Systems.