A system for dynamically managing and controlling distributed energy resources in a transmission/distribution power grid is disclosed. A plurality of regions within a transmission/distribution power grid is autonomously managed using regional control modules. Each regional control module oversees the management and control of the transmission/distribution power grid and is further associated with a plurality of local control modules that interface with distributed energy resources within a region. Power production and power consumption are monitored and analyzed by the enterprise control module which, upon determining that power consumption within a region does not match power producing capability, dynamically reallocates distributed energy resources throughout the grid keeping the system balance. Power flow at key nodes within the network are monitored and analyzed by the local control modules, regional control modules, and enterprise control modules with compensating actions taken in the event that system parameter risks violating safety, stability, or operational thresholds.

Dynamic Distributed Power Grid Control System

A building manager includes a communications interface configured to receive information from a smart energy grid. The building manager further includes an integrated control layer configured to receive inputs from and to provide outputs to a plurality of building subsystems. The integrated control layer includes a plurality of control algorithm modules configured to process the inputs and to determine the outputs. The building manager further includes a fault detection and diagnostics layer configured to use statistical analysis on the inputs received from the integrated control layer to detect and diagnose faults. The building manager yet further includes a demand response layer configured to process the information received from the smart energy grid to determine adjustments to the plurality of control algorithms of the integrated control layer.

Smart building manager

Systems and methods for building automation system management are shown and described. The systems and methods relate to fault detection via abnormal energy monitoring and detection. The systems and methods also relate to control and fault detection methods for chillers. The systems and methods further relate to graphical user interfaces for use with fault detection features of a building automation system.

Automated fault detection and diagnostics in a building management system

Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern electrical power systems over multiple periods. PyPSA includes models for conventional generators with unit commitment, variable renewable generation, storage units, coupling to other energy sectors, and mixed alternating and direct current networks. It is designed to be easily extensible and to scale well with large networks and long time series. In this paper the basic functionality of PyPSA is described, including the formulation of the full power flow equations and the multi-period optimisation of operation and investment with linear power flow equations. PyPSA is positioned in the existing free software landscape as a bridge between traditional power flow analysis tools for steady-state analysis and full multi-period energy system models. The functionality is demonstrated on two open datasets of the transmission system in Germany (based on SciGRID) and Europe (based on GridKit). Funding statement: This research was conducted as part of the CoNDyNet project, which is supported by the German Federal Ministry of Education and Research under grant no. 03SF0472C. The responsibility for the contents lies solely with the authors

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PyPSA: Python for Power System Analysis

A system for electric grid utilization and optimization, comprising a communications interface executing on a network-connected server and adapted to receive information from a plurality of iNodes, the plurality of iNodes comprising a source iNode, a sink iNode, and a plurality of transmission or distribution iNodes, an event database coupled to the communications interface and adapted to receive events from a plurality of iNodes via the communications interface, a modeling server coupled to the communications interface, and a statistics server coupled to the event database and the modeling server, wherein the modeling server, on receiving a request to establish an allocation of at least one of transmission losses, distribution losses, and ancillary services to a specific sink iNode, computes at least one virtual path for flow of electricity between a source iNode and the specific sink iNode and wherein the modeling server further computes, for each transmission or distribution iNode included in the computed virtual path, at least one energy loss and allocates a portion thereof to the specific sink iNode, is disclosed.

System and method for electric grid utilization and optimization

The Holomorphic Embedding Load Flow is a novel general-purpose method for solving the steady state equations of power systems. Based on the techniques of Complex Analysis, it has been granted two US Patents. Experience has proven it is performant and competitive with respect established iterative methods, but its main practical features are that it is non-iterative and deterministic, yielding the correct solution when it exists and, conversely, unequivocally signaling voltage collapse when it does not. This paper reviews the embedded load flow method and highlights the technological breakthroughs that it enables: reliable real-time applications based on unsupervised exploratory load flows, such as Contingency Analysis, OPF, Limit-Violations solvers, and Restoration plan builders. We also report on the experience with the method in the implementation of several real-time EMS products now operating at large utilities.

The Holomorphic Embedding Load Flow method

A system and method for monitoring and managing electrical power transmission and distribution networks through use of a deterministic, non-iterative method using an holomorphic embedding and algebraic approximants for determining the real-time load flow in a power generating system having an electrical grid. Such method may be employed for real-time or off-line applications for electric power systems reliability assessment, and is capable of determining whether or not a physical solution to the load flow problem exists, or if the system is in a state of voltage collapse.

System and method for monitoring and managing electrical power transmission and distribution networks

The Holomorphic Embedding Loadflow Method is extended here from AC to DC-based systems. Through an appropriate embedding technique, the method is shown to extend naturally to DC power transmission systems, preserving all the constructive and deterministic properties that allow it to obtain the white branch solution in an unequivocal way. Its applications extend to nascent meshed HVDC networks and also to power distribution systems in more-electric vehicles, ships, aircraft, and spacecraft. In these latter areas, it is shown how the method can cleanly accommodate the higher-order nonlinearities that characterize the I-V curves of many devices. The case of a photovoltaic array feeding a constant-power load is given as an example. The extension to the general problem of finding DC operating points in electronics is also discussed, and exemplified on the diode model.

The Holomorphic Embedding Loadflow Method for DC Power Systems and Nonlinear DC Circuits

The Holomorphic Embedding Load-Flow Method (HELM) was recently introduced as a novel technique to constructively solve the power-flow equations in power grids, based on advanced complex analysis. In this paper, the theoretical foundations of the method are established in detail. Starting from a fundamental projective invariance of the power-flow equations, it is shown how to devise holomorphicity-preserving embeddings that ultimately allow regarding the power-flow problem as essentially a study in algebraic curves. Complementing this algebraic-geometric viewpoint, which lays the foundation of the method, it is shown how to apply standard analytic techniques (power series) for practical computation. Stahl's theorem on the maximality of the analytic continuation provided by Pade approximants then ensures the completeness of the method. On the other hand, it is shown how to extend the method to accommodate smooth controls, such as the ubiquitous generator-controlled PV bus.

Antonio Trias

Papers

The Holomorphic Embedding Load Flow method

System and method for monitoring and managing electrical power transmission and distribution networks

The Holomorphic Embedding Loadflow Method for DC Power Systems and Nonlinear DC Circuits

Fundamentals of the Holomorphic Embedding Load-Flow Method

A Padé-Weierstrass technique for the rigorous enforcement of control limits in power flow studies