Andres Ovalle

Decentralized Control of Voltage Source Converters in Microgrids Based on the Application of Instantaneous Power Theory

In this paper, a new strategy to control microgrids highly penetrated by voltage source converters (VSCs) is proposed. The strategy is based on the instantaneous measurements and calculations of voltages and currents and the application of instantaneous power theory. This approach employs each VSC along with an LC filter as a current source. The grid parameters are not known to the controller, only the filter inductance and capacitance. The approach characterizes a theoretical methodology to define a grid status parameter that provides multiple alternatives to operate the VSC autonomously. Moreover, one of those alternatives is sharing load among VSCs by regulating the voltage of the local connection bus. This grid status parameter is an external voltage contribution vector defined by the operation of the other VSCs in the microgrid. Because of the definition of this parameter, frequency manipulation is not employed as a communication link between VSCs, avoiding perturbation to the grid stability. The approach provides an approximation of the equivalent impedance of the system seen from the filter output. The load-sharing scheme under the proposed strategy is fully described. An experimental validation is performed in order to test the proposed approach for load sharing between three VSCs and the inclusion of nonlinear load.

Optimal management and integration of electric vehicles to the grid: Dynamic programming and game theory approach

This paper provides a Dynamic Programming (DP) approach to optimally manage the charging schedule of electrical vehicles (EV) based on a decentralized global optimization frame given by the use of a Game Theory approach. The paper provides a detailed explanation of a forward induction DP algorithm and shows its adaptation to the problem of optimal charging of one EV with the corresponding constraints of limiting power consumption, minimal and maximal states of charge, desired states of charge, etc. The extension to multiple EVs is provided by the adaptation of a N-person non-cooperative game approach. In this game, the payoff of each player is based on a utility function that aims to reduce the distance between the total load and the average load, achieving load curve flattening.

Improvements to MPPT for PV generation based on Mamdani and Takagi-Sugeno fuzzy techniques

The positive impact of solar generation in the current power systems is growing rapidly due to energy increasing demands, depletion of fossil fuel sources and the environmental requirements of pollution reduction. Maximum Power Point Tracking (MPPT) methods are integrated with Photo Voltaic (PV) systems in order to maximise the energy obtained under every weather conditions and deal with the associated current - voltage nonlinearities. Two of the most applied and studied MPPT methods are the well known Perturb and Observe (P&O) and Incremental Conductance (IC). In this document, the design of a Mandani and Takagi - Sugeno (T-S) Fuzzy Logic Controllers (FLC) for the enhancement of these MPP trackers are presented. The basics of P&O and IC methods are shown and compared with the given approaches under a simulation basis. The energy extracted performance index and the speed up of convergence show significant achievements of the fuzzy controllers proposed.

A comparative study of low sampling non intrusive load dis-aggregation

Non-intrusive load monitoring (NILM) deals with the identification and subsequent energy estimation of the individual appliances from the smart meter data. The state of the art applications typically runs once per day and reports the detected appliances. In this work, data driven models are implemented for two different sampling rates (10 seconds and 15 minutes). The models are trained for 20 houses in the Netherlands and tested for a period of 4-weeks. The results indicate that the disaggregation methods is applicable for both sampling cases but with different use-case.

Voltage support by optimal integration of plug-in hybrid electric vehicles to a residential grid

This paper provides a linear approach to compute the voltages at any node on a residential grid based on the house instantaneous load and the presence of charging Plug-In Hybrid Electric Vehicles (PHEV) on the grid (and the corresponding instantaneous consumption or injection). Based on this linear operation, the paper provides a detailed Linear Programming (LP) formulation of the problem of charging the PHEVs while providing a voltage support service to the grid. The approach gives optimal charging schedules for each PHEV in a centralized way, looking for benefit on the customers perspective. Multiple evaluation cases are included in order to test the ability of the approach to maintain voltages within safety limits and provide optimal consumption/injection policies. An additional case is included to prove the potential of the PHEVs to solve existing voltage technical issues on a residential grid. The formulation is proposed as a benchmark to identify possible benefits and elements that could be useful for more realistic applications.

Escort Evolutionary Game Dynamics Approach for Integral Load Management of Electric Vehicle Fleets

This paper proposes an application of an evolutionary game dynamics called the escort dynamics (ED) for the decentralized load management of plug-in electric vehicles (PEV). Different from earlier contributions, in the present approach, PEVs work together in a fair scheme in order to provide several ancillary services to the grid: Load shifting, active power balancing, and partial supply of reactive power demand on each phase of the distribution transformer. Meanwhile, batteries are guaranteed to be fully charged according to the constraints imposed by the owners. In the proposed formulation, chargers can be either three phase or single phase; however, in this paper, only three-phase chargers are considered. The key concepts behind ED, especially for escort functions, are provided at the beginning of this paper. Based on these concepts, the assumptions and analogies followed for the construction of the proposed approach are explained in detail, especially for the proposed definition of escort functions. A multipopulation scenario is proposed for the interaction of several PEVs using local ED routines. This interaction among populations follows another well-known evolutionary game dynamics called the best reply dynamics. Performance is evaluated using real data measured from a distribution transformer from the SOREA utility grid company in the region of Savoie, France.

A Flexible Nonorthogonal-Reference-Frame-Based SVPWM Framework for Multilevel Inverters

A generalized SVPWM framework is proposed based on the convenient definition of three nonorthogonal static reference frames, alternative to the

Online forecasting of electrical load for distributed management of plug-in electric vehicles

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Kite generator system: Grid integration and validation

-frame. The definition of these reference frames is exploited in order to get appropriate switching sequences and duty cycles taking into account the redundancy property of constructive vectors. The redundancy property is transparent to the algorithm, given that the proposed method takes advantage of it by following a straightforward algebraic procedure, without postprocessing stages or lookup tables. Furthermore, according to the number of levels and the region of the control space, a detailed analysis on the viability of time averaged common-mode voltage (CMV) elimination, is given. If it is viable, the algorithm achieves zero time-averaged CMV by selecting appropriate switching sequences and duty cycles. The method is based on very simple, low-dimensional, algebraic matrix computations, which make it flexible for implementation. Every detail on the algorithm and its theoretical base is carefully provided in the manuscript. Both, the proposed strategy that optimally provides switching sequences eliminating CMV, and its viability analysis, are applicable to other types of modulation approaches based on orthogonal or nonorthogonal reference frames. A test is proposed on a real-time emulated five-level cascaded H-bridge topology.

Step-size fuzzy control to maximum power point tracking algorithms for PV microgrid arrays

The paper aims at making online forecast of electrical load at the MV-LV transformer level. Optimal management of the Plug-in Electric Vehicles (PEV) charging requires the forecast of the electrical load for future hours. The forecasting module needs to be online (i.e update and make forecast for the future hours, every hour). The inputs to the predictor are historical electrical and weather data. Various data driven machine learning algorithms are compared to derive the most suitable model. The results indicate that an online forecasting method has an error between 2-5% for the future 24-hour. The decentralized management system works well with the forecasting data.