Distributed reactive power feedback control for voltage regulation and loss minimization

We consider the problem of exploiting the microgenerators dispersed in the power distribution network in order to provide distributed reactive power compensation for power losses minimization and voltage regulation. In the proposed strategy, microgenerators are smart agents that can measure their phasorial voltage, share these data with the other agents on a cyber layer, and adjust the amount of reactive power injected into the grid, according to a feedback control law that descends from duality-based methods applied to the optimal reactive power flow problem. Convergence to the configuration of minimum losses and feasible voltages is proved analytically for both a synchronous and an asynchronous version of the algorithm, where agents update their state independently one from the other. Simulations are provided in order to illustrate the performance and the robustness of the algorithm, and the innovative feedback nature of such strategy is discussed

Distributed watermarking for secure control of microgrids under replay attacks

The problem of replay attacks in the communication network between Distributed Generation Units (DGUs) of a DC microgrid is examined. The DGUs are regulated through a hierarchical control architecture, and are networked to achieve secondary control objectives. Following analysis of the detectability of replay attacks by a distributed monitoring scheme previously proposed, the need for a watermarking signal is identified. Hence, conditions are given on the watermark in order to guarantee detection of replay attacks, and such a signal is designed. Simulations are then presented to demonstrate the effectiveness of the technique

Topology Detection in Microgrids with Micro-Synchrophasors

Network topology in distribution networks is often unknown, because most switches are not equipped with measurement devices and communication links. However, knowledge about the actual topology is critical for safe and reliable grid operation. This paper proposes a voting-based topology detection method based on micro-synchrophasor measurements. The minimal difference between measured and calculated voltage angle or voltage magnitude, respectively, indicates the actual topology. Micro-synchrophasors or micro-Phasor Measurement Units ({\mu}PMU) are high-precision devices that can measure voltage angle differences on the order of ten millidegrees. This accuracy is important for distribution networks due to the smaller angle differences as compared to transmission networks. For this paper, a microgrid test bed is implemented in MATLAB with simulated measurements from {\mu}PMUs as well as SCADA measurement devices. The results show that topologies can be detected with high accuracy. Additionally, topology detection by voltage angle shows better results than detection by voltage magnitude.Comment: 5 Pages, PESGM2015, Denver, C

Can the effects of anthropogenic pressures and environmental variability on nekton fauna be detected in fishery data? Insights from the monitoring of the artisanal fishery within the Venice lagoon

Nekton communities in transitional ecosystems are naturally adapted to stressful conditions associated with high environmental variability. Human activities in these systems are likely to determine additional stress with a possible effect on fish fauna, hence on fisheries. In order to test the relative importance of natural and anthropogenic factors in determining changes in nekton community, catches (incl. bycatch) from artisanal fisheries (fyke nets) were monitored seasonally in different areas of the Venice lagoon (Italy) between 2001 and 2013. Changes in nekton community composition and in the biomass of target and non-target species/groups were analysed, and the results were related to temporal factors, environmental characteristics and to the variability in anthropogenic pressures. Statistical tests were carried out using a model-based analysis of both univariate and multivariate data. Results highlighted that temporal factors and environmental conditions (i.e. the main chemico-physical descriptors) are more relevant than anthropogenic pressures in explaining spatial and temporal changes in the lagoon nekton assemblage, but that several characteristics of the assemblage, in particular the biomass of some particular categories and of the whole assemblage, are sensitive to human impacts. A particularly negligible effect seemed to be associated with fishing effort, thus suggesting that the monitoring of the local artisanal fishery is suitable also to provide useful information on the evaluation of the status of nekton assemblage

Constraints on OPF Surrogates for Learning Stable Local Volt/Var Controllers

We consider the problem of learning local Volt/Var controllers in distribution grids (DGs). Our approach starts from learning separable surrogates that take both local voltages and reactive powers as arguments and predict the reactive power setpoints that approximate optimal power flow (OPF) solutions. We propose an incremental control algorithm and identify two different sets of slope conditions on the local surrogates such that the network is collectively steered toward desired configurations asymptotically. Our results reveal the trade-offs between each set of conditions, with coupled voltage-power slope constraints allowing an arbitrary shape of surrogate functions but risking limitations on exploiting generation capabilities, and reactive power slope constraints taking full advantage of generation capabilities but constraining the shape of surrogate functions. AC power flow simulations on the IEEE 37-bus feeder illustrate their guaranteed stability properties and respective advantages in two DG scenarios

Modeling, Control and Identification of a Smart Grid

We are in front of an epochal change in the power distribution and generation scenario. The increasing request of energy, the energy dependency of several countries from few foreign nations endowed with oilfield or gas field, and, on the other hand, the climate change and environmental issues are the main explanation of the recent development and spread of renewable distributed energy generation technologies. Examples of them are photovoltaic panels, wind turbines or geothermal, biomass, or hydroelectric. They are called small-size generators, or micro-generator, since the amount of power they can produce is significantly lower than the one produced by the huge, classical power plants. These distributed energy resources (DERs) are located close to where electricity is used, in the distribution network. Furthermore, they are connected to the electrical grid via electronic interfaces, the inverters, that could allow us to control the power injected into the grid. This thesis is focused on the study of some crucial aspects of this new energetic scenario: 1. Modeling: we recall the classical models and a recent linearized one of the power systems, that will be very useful for the design and the analysis of our algorithms. 2. Optimal Reactive Power Flow (OPRF) problem: in this part we recall classical and recent algorithms that deal with the reactive power regulation. In particular, we focus on the ones that solve the OPRF problem, i.e. the problem of the amount of reactive power to be injected by each micro-generators, in order to achieve “optimal” performance. We choose, as an optimality achievement, the minimization of the line losses. Finally we derive and propose our OPRF algorithm, providing formal proves of its convergence to the optimal solution. 3. Optimal Power Flow (OPF) problem: the OPF problem’s aim is to find an operating point of the power system that optimize a cost function (tipically the generation cost) satisfying the power demand and some operative constraints. After recalling the most popular algorithms that solve the OPF problem, we propose two of them. In this framework there are mainly two possible scenarios. The first is related to the “utility point of view”, where the total cost accounts for the production cost of the energy (that comes from big generation plants such as nuclear or hydro-electrical plants) and for the remuneration to be paid to the owners of DERs. In this framework, the utility imposes a behavior procedure to be followed by the producers to compute the amount of energy they have to inject into the grid to minimize the total cost. The first algorithm deal with this scenario. The second one is related to the “producer point of view”. Since the owners of the DERs are paid proportionally to the energy that they inject, they would like to maximize the power they inject, while keeping satisfied some operative constraints. The result is a game among the agents. A first treatment on this scenario is given by the second algorithm. 4. Switches monitoring for topology identification: in this part, after a literature review, we propose a algorithm for the identification of switches actions. They modify the topology of the electrical grid, whose knowledge is fundamental for monitoring, control and estimation. This algorithm works analyzing how the phasorial voltage profile vary and recognize a kind of signature left by the switches status change