A coordinated control method of voltage and reactive power for active distribution net-works based on soft open point

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribu-tion networks (ADNs). The conventional voltage regulation de-vices limited by the physical constraints are difficult to meet the requirement of real-time voltage and VAR control (VVC) with high precision when DGs fluctuate frequently. However, soft open point (SOP), a flexible power electronic device, can be used as the continuous reactive power source to realize the fast voltage regu-lation. Considering the cooperation of SOP and multiple regula-tion devices, this paper proposes a coordinated VVC method based on SOP for ADNs. Firstly, a time-series model of coordi-nated VVC is developed to minimize operation costs and eliminate voltage violations of ADNs. Then, by applying the linearization and conic relaxation, the original nonconvex mixed-integer non-linear optimization model is converted into a mixed-integer sec-ond-order cone programming (MISOCP) model which can be efficiently solved to meet the requirement of voltage regulation rapidity. Case studies are carried out on the IEEE 33-node system and IEEE 123-node system to illustrate the effectiveness of the proposed method

Strong Stationarity Conditions for Optimal Control of Hybrid Systems

We present necessary and sufficient optimality conditions for finite time optimal control problems for a class of hybrid systems described by linear complementarity models. Although these optimal control problems are difficult in general due to the presence of complementarity constraints, we provide a set of structural assumptions ensuring that the tangent cone of the constraints possesses geometric regularity properties. These imply that the classical Karush-Kuhn-Tucker conditions of nonlinear programming theory are both necessary and sufficient for local optimality, which is not the case for general mathematical programs with complementarity constraints. We also present sufficient conditions for global optimality. We proceed to show that the dynamics of every continuous piecewise affine system can be written as the optimizer of a mathematical program which results in a linear complementarity model satisfying our structural assumptions. Hence, our stationarity results apply to a large class of hybrid systems with piecewise affine dynamics. We present simulation results showing the substantial benefits possible from using a nonlinear programming approach to the optimal control problem with complementarity constraints instead of a more traditional mixed-integer formulation.Comment: 30 pages, 4 figure

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

We propose a framework for the stability verification of Mixed-Integer Linear Programming (MILP) representable control policies. This framework compares a fixed candidate policy, which admits an efficient parameterization and can be evaluated at a low computational cost, against a fixed baseline policy, which is known to be stable but expensive to evaluate. We provide sufficient conditions for the closed-loop stability of the candidate policy in terms of the worst-case approximation error with respect to the baseline policy, and we show that these conditions can be checked by solving a Mixed-Integer Quadratic Program (MIQP). Additionally, we demonstrate that an outer and inner approximation of the stability region of the candidate policy can be computed by solving an MILP. The proposed framework is sufficiently general to accommodate a broad range of candidate policies including ReLU Neural Networks (NNs), optimal solution maps of parametric quadratic programs, and Model Predictive Control (MPC) policies. We also present an open-source toolbox in Python based on the proposed framework, which allows for the easy verification of custom NN architectures and MPC formulations. We showcase the flexibility and reliability of our framework in the context of a DC-DC power converter case study and investigate its computational complexity

A Review of Energy Management Systems and Organizational Structures of Prosumers

Thisreviewprovidesthestateoftheartofenergymanagementsystems(EMS)and organizationalstructuresofprosumers.Integrationofrenewableenergysources(RES)intothe householdbringsnewchallengesinoptimaloperation,powerquality,participationintheelectricity marketandpowersystemstability.AcommonsolutiontothesechallengesistodevelopanEMSwith differentprosumerorganizationalstructures.EMSdevelopmentisamultidisciplinaryprocessthat needstoinvolveseveralaspectsofobservation.Thispaperprovidesanoverviewoftheprosumer organizationalandcontrolstructures,typesandelements,predictionmethodsofinputparameters, optimizationframeworks,optimizationmethods,objectivefunctions,constraintsandthemarket environment.Specialattentionisgiventotheoptimizationframeworkandpredictionofinput parameters,whichrepresentsroomforimprovement,thatmitigatetheimpactofuncertainties associatedwithRES-basedgeneration,consumptionandmarketpricesonoptimaloperation.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.2 - Per a 2030, augmentar substancialment el percentatge d’energia renovable en el con­junt de fonts d’energiaObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.a - Per a 2030, augmentar la cooperació internacional per tal de facilitar l’accés a la investigació i a les tecnolo­gies energètiques no contaminants, incloses les fonts d’energia renovables, l’eficiència energètica i les tecnologies de combustibles fòssils avançades i menys contaminants, i promoure la inversió en infraestructures energètiques i tecnologies d’energia no contaminantObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version

Optimal Scheduling of Home Energy Management System with Plug-in Electric Vehicles Using Model Predictive Control

abstract: With the growing penetration of plug-in electric vehicles (PEVs), the impact of the PEV charging brought to the utility grid draws more and more attention. This thesis focused on the optimization of a home energy management system (HEMS) with the presence of PEVs. For a household microgrid with photovoltaic (PV) panels and PEVs, a HEMS using model predictive control (MPC) is designed to achieve the optimal PEV charging. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed. Furthermore, the hardware development of a microgrid prototype is also described in this thesis.Dissertation/ThesisMasters Thesis Engineering 201

Model Based Systems Engineering for a Typical Smartgrid

The complexity and heterogeneity of today’s large Cyber-Physical Systems (CPS) is addressed by model based design. This class of systems is a direct consequence of our entry into the new era of systems characterized by high complexity, increased software dependency, multifaceted support for networking and inclusion of data and services form global networks. Cyber-Physical Power Systems such as SmartGrids provide perfect example to emphasis heterogeneity and complexity of today’s systems. In this thesis we work towards augmenting the creation and demonstration of a framework for developing an integrated CPS modelling hub with powerful and diverse tradeoff analysis methods and tools for design exploration of CPS