325results about "Systems intergating technologies" patented technology

The invention discloses a disperse relaxation factor tidal current model based minimum electricity generating cost incremental quantity obtaining method. When a minimum electricity generating cost incremental quantity model only containing one balance node tidal current model is solved, the total demand unit change of a system is fixed on a balance node, and an obtained lambda, namely electricity generating cost minimum incremental quantity cannot reflect actual operation of the system in most cases during total demand unit change of a system. The disperse relaxation factor tidal current model based minimum electricity generating cost incremental quantity obtaining method adopts solves the provided model by means of an original antithesis interior point method, and the lambda of the system is controllable according to selected disperse relaxing factors.

The invention relates to the field of power distribution control, and particularly discloses a self-healing control system and method based on multi-agent collaboration, and the system comprises a regional agent and a local agent which are disposed in a power distribution network. Wherein the local intelligent agent is configured to obtain real-time operation data of a monitoring point in the power distribution network, and perform rapid fault detection on the real-time operation data; the regional intelligent agent is configured to fuse the fault analysis information of the plurality of local intelligent agents to determine fault position information when the power distribution network has a fault, generate a self-healing control strategy according to the fault position information, and send the self-healing control strategy to the local intelligent agents for execution; through cooperative work of the distributed intelligent agents, the problems of low response speed, low positioning precision, weak autonomous capability and the like in traditional power distribution network fault management are solved. In addition, the system does not need to depend on centralized control of a master station, can still operate autonomously when communication is interrupted, and improves the efficiency and reliability of fault processing through cooperation of multiple agents.

The invention discloses a broadband random power quality adaptive monitoring system, which relates to the field of power grid monitoring and comprises a broadband signal acquisition module, a synchronous phasor measurement module, an edge calculation module, a cloud edge collaborative analysis module and a local traceability module. The broadband signal acquisition module performs high-frequency sampling on a power grid signal and ensures integrity; the synchronous phasor measurement module is used for realizing time synchronization of multiple monitoring points and generating data with time marks; the edge calculation module is used for studying and judging disturbance and early warning through deep learning, and uploading data to the cloud; the cloud edge collaborative platform aggregates data, deduces regional power quality and issues an optimized AI model; the local traceability module quantifies harmonic responsibility and positions a broadband disturbance source. The system innovatively adopts an ensemble empirical mode decomposition and variational mode decomposition parallel strategy, combines a spectrum kurtosis maximization algorithm to determine the number of modes and accurately separate transient and steady components, solves the problem of feature confusion of a traditional method, and realizes the crossing from single analysis to multi-mode fusion research and judgment.

The invention relates to the technical field of industrial big data, in particular to a transformer consumption reduction intelligent control method and system based on a power generation end, and the method comprises the steps: building a source-load space-time correlated industrial big data set, determining an operation reference, and synchronously monitoring real-time electrical parameters; load component decoupling is executed, a basic load component is stripped, and a power fluctuation deviation parameter is extracted; reconstructing equivalent control power of a power generation end based on a nonlinear fluctuation compensation strategy; and constructing a power grid energy efficiency function to execute loss minimization optimization, determining a power supply voltage setting value and driving on-load voltage regulation. Through multi-dimensional data fusion and non-linear load reconstruction, the problem that a traditional method is difficult to deal with random fluctuation of the load is solved, collaborative optimization of transformer loss and line transmission loss is achieved, and operation energy consumption of a power supply loop of a power generation end is effectively reduced.

The invention provides a high-efficiency energy-saving transformer structure design optimization method and system and a storage medium, and the method comprises the steps: determining optimization parameters based on a transformer design scheme, and determining constraint conditions based on a use standard of a transformer; based on the optimization parameters, constructing a target function with the minimization of the main material cost of the transformer as a target; under the action of the objective function, constructing an optimization mathematical model based on the optimization parameters; solving the optimized mathematical model by using a particle swarm optimization algorithm to obtain an optimal solution; under a constraint condition, screening the optimal solution by adopting a feasibility rule method to obtain an optimal electromagnetic optimization parameter combination; and optimizing transformer structure parameters based on the optimal electromagnetic optimization parameters. According to the method, the operation stability and energy-saving performance of the transformer are improved, the balance of economy, reliability and applicability is achieved, and the design efficiency and quality are greatly improved.

The invention discloses a low-voltage distribution area topology identification method, system and device and a storage medium, and the method comprises the following steps: deploying a synchronous measurement unit in a low-voltage distribution area, and obtaining the outgoing line current phasor and voltage phasor data with a synchronous time scale of a whole network; constructing an incoming line and outgoing line current phasor set, and performing adaptive descending sorting according to amplitudes; determining that the nodes corresponding to the incoming line current phasors and the found nodes corresponding to the one or more outgoing line current phasors are in a father-son relationship, and iterating the process until all sets are empty, thereby completing the identification of the topological relationship of the power distribution side; and according to the equipment number contained in the obtained voltage phasor data, determining a meter box connected with the user electricity meters, and then clustering the user electricity meters connected to the same meter box according to the voltage phase angle to obtain the connection phase sequence of each user electricity meter. The problem of key information missing is solved from a data source, and accurate and efficient identification of topology is realized by fusing physical constraints.

The invention discloses a power distribution network short-circuit parameter real-time measurement method, system and device based on PMU cooperation and a medium, and belongs to the technical field of power systems and automation, and the method comprises the steps: collecting PMU real-time measurement data, loading preset parameters, and constructing a PMU cooperation measurement network; carrying out a synchronous sampling algorithm, carrying out comprehensive preprocessing on real-time measurement data, and carrying out state reconstruction and inhibiting the influence of abnormal data according to a state estimator; establishing a short-circuit parameter identification model, and executing short-circuit parameter identification; performing multi-dimensional evaluation on the identification result, and evaluating the real-time performance of the algorithm; and based on the evaluation result, updating the key parameters, and executing adaptive adjustment of the system parameters. According to the invention, through high-precision synchronous acquisition, adaptive signal processing and closed-loop optimization mechanisms, comprehensive improvement of the real-time measurement precision, reliability and adaptability of the short-circuit parameters of the power distribution network is realized.

The invention relates to the technical field of power system stability control, and discloses a hybrid synchronous phase modifier quick response coordination control system with inertia support. According to the invention, wide-area data such as voltage phase, frequency deviation and the like are collected and verified through the data sensing module; the modal evaluation module calculates a global motion modal cooperation coefficient G to quantify the dynamic cooperation degree of the system; the coordination control module dynamically switches an emergency instability or preventive damping mode based on G, and generates a coordination control instruction of the phase modifier and the SVG; and the execution feedback module forms a closed loop and optimizes parameters, and realizes efficient response in combination with a layered distributed architecture. According to the invention, deep cooperative control of the two is realized, the disturbance resistance and stability maintenance capability of the power system are improved, and the method is suitable for a power grid with high-proportion renewable energy access.

The invention relates to the technical field of line fault analysis, in particular to a high-voltage line fault identification method based on phasor analysis, which comprises the following steps of: performing multi-time window nesting decomposition on voltage phasors and current phasors acquired in the operation process of a high-voltage line, extracting a phasor dynamic response sequence, and calculating the phasor dynamic response sequence; identifying a main disturbance mechanism characteristic triggered by a fault, and constructing a main disturbance mechanism type label; a driving response dominant phasor disturbance factor is identified, a phasor factor mapping graph is constructed, factor stripping operation is executed, and a dominant purification phasor set is generated; and performing phase evolution analysis on the dominant purification phasor set, and determining a fault initial phase transition boundary and a cross-phase offset trend. According to the method, the stability and the physical consistency of identification are ensured, and the finally output fault type and phase structured result not only has clear logic traceability, but also highly meets the requirements of dispatching automation and quick response of a protection system.

The invention discloses a power grid power flow real-time calculation and state estimation method and system based on a PMU, and belongs to the technical field of electric measurement and electric fault positioning. The method comprises the following steps: synchronously measuring electrical variables, including a voltage phasor and a current phasor, of a power grid node through PMU equipment to obtain synchronous phasor data, and verifying time and topology consistency; the power grid observability grade is judged based on PMU configuration node distribution corresponding to the verified electric measurement data; directly generating a real-time state estimation result through linear calculation based on PMU electric measurement data if the whole domain is observable; and if a part is observable, fusing PMU and SCADA data, carrying out nonlinear state estimation through a weighted least square method, distributing a high weight for the PMU electrical measurement data, and dynamically adjusting the SCADA weight to suppress bad data. According to the method, through observability adaptive judgment, the precision and efficiency of state estimation are improved, a data basis is provided for power grid fault positioning, and the method is suitable for practical application scenes of various PMU coverage degrees.

The invention discloses a low-cost precise time keeping method, system and device based on a gating circulation unit, and relates to the technical field of power grid measurement. The method is executed when the synchronous phasor measurement device cannot receive external signals, and comprises the following steps: monitoring operation parameters which influence the frequency stability of an internal crystal oscillator of the phasor measurement unit in real time; calculating a current frequency error of the crystal oscillator in real time by using a crystal oscillator frequency drift prediction model based on a gated cycle unit network based on the operation parameters; generating a time correction amount according to the current frequency error; and applying the time correction to a local clock of the phasor measurement unit to compensate the frequency drift of the crystal oscillator so as to realize accurate time keeping. According to the invention, through accurate prediction of crystal oscillator errors and lightweight software compensation, the synchronous phasor measurement device adopting a low-cost crystal oscillator can also realize long-time high-precision time keeping, the hardware cost is obviously reduced, and the reliability of power grid monitoring during the Beidou / GPS lock losing period is improved.

The invention relates to the technical field of intelligent power distribution network safety detection and fault processing, in particular to a multi-source coupling leakage current accurate traceability and cooperative suppression method and system for a power distribution network, and the method comprises the steps: collecting leakage current, voltage phase and power fluctuation data through a synchronous phasor measurement device; based on the collected data, constructing a four-dimensional feature library, carrying out decoupling processing on leakage current signals, and then realizing accurate traceability positioning of the leakage current according to a matching result of the leakage current signals and the four-dimensional feature library and a time difference between sensors; data are uploaded to a distribution network dispatching center, leakage current is evaluated based on a dynamically adjusted safety threshold value, and then operation states of a photovoltaic inverter, an energy storage converter and a charging pile are cooperatively controlled to realize active suppression of the leakage current; and performing preliminary diagnosis on the leakage current at the edge side, uploading a result to a cloud end, and determining a final diagnosis conclusion. According to the invention, the accuracy of multi-source coupling leakage current tracing and the accuracy of cooperative suppression of the power distribution network are improved.

The invention relates to the technical field of power system transient stability assessment, and discloses a power system transient stability assessment method based on FTF-ACGAN and space-time attention. According to the method, an original data set reflecting different power flow operation modes and fault conditions is generated, and transient electrical quantities are extracted as input characteristics; generating an adversarial network through a fuzzy transfer field-auxiliary classifier to extract modals with different characteristics of a sample, and revealing transient characteristics of the electrical signal; and establishing a mapping relation between original high-dimensional input and a system stability or instability label according to the processed transient measurement data of the power system by considering respective capturing capabilities of a spatial feature extraction module and a time feature extraction module in the dual-module multi-head space-time attention network on space-time local association and global dependency features. The method can consider the time-frequency domain information of the electric power system sample, construct a data set with moderate and abundant sample characteristics, and accurately judge the actual operation condition of the electric power system.

The invention discloses a wide-area oscillation source positioning method and system based on physical feature embedding and a graph attention network, and the method comprises the steps: obtaining synchronous phasor data of a power system, carrying out the modal parameter identification of subsynchronous oscillation and / or super-synchronous oscillation based on the synchronous phasor data, constructing a topological graph of the power system, and carrying out the positioning of a wide-area oscillation source. And constructing the oscillation amplitude, the attenuation factor and the phase of each node obtained by identification into a feature vector of each node in a topological graph, inputting the topological graph and the feature vector into a graph attention network, and outputting an oscillation source positioning result, so that high-frequency recording data after an accident does not need to be waited, and the positioning accuracy of the oscillation source is improved only on the basis of synchronous phasor data. The identified modal parameters are used as physical characteristics to be embedded into the graph attention network, and the interpretability of a physical mechanism and the graph structure mining capability of deep learning are fused, so that subsynchronous oscillation and super-synchronous oscillation are accurately positioned.

Disclosed is a system and method for automated outage and workflow planning system in a distributed electrical power grid with planned de-energization of electrical equipment as opposed to responding to an unplanned power outage. An automated system provides core conflict resolution and power outage planning. The present invention automatically notifies requestors of upcoming work orders. In addition, the present invention reduces scheduling inefficiencies by requiring requestors to confirm, decline, or edit on the fly their pending work order(s). The system also determines if all the orders are not completed and places the order back on the calendar for another day.

The invention relates to a new energy power station configuration optimization method based on an agent model and multi-objective optimization. The method comprises the steps of obtaining historical power system configuration parameters and corresponding historical stability characteristic values, and performing preprocessing; inputting the preprocessed historical power system configuration parameters into a neural network agent model based on a multi-layer perceptron architecture, performing offline training in combination with corresponding historical stability characteristic values and physical prior constraints, and outputting predicted stability characteristic values; taking the prediction stability characteristic value as an optimization target, and constructing a target function of multi-target Bayesian optimization; and iteratively solving a Pareto optimal solution set based on the objective function, and determining an optimal new energy power station configuration scheme. According to the method, multi-objective optimization and Bayesian optimization are combined, a multi-objective acquisition function is adopted to approach the Pareto frontier between stability characteristic values, precision and multi-objective tradeoff can be considered, and a more flexible and scientific configuration scheme is provided for new energy station construction.

The invention provides a power distribution network early fault section identification method and system based on multi-dimensional feature probability mapping, and belongs to the technical field of power system power distribution network fault detection. The method comprises the following steps: collecting zero-sequence voltage of a power distribution network bus and zero-sequence current signals of head ends of all feeder lines, and obtaining derivative signals of the zero-sequence voltage and the zero-sequence current signals; calculating the third harmonic energy of the zero-sequence current of each feeder line, and when the third harmonic energy exceeds a set threshold value, judging that the feeder line has an early fault; processing the zero-sequence current signal, and extracting an IMF1 component; calculating a correlation characteristic quantity and a dot product characteristic quantity for each section formed by the current difference values of the adjacent measuring devices based on the IMF1 component; and respectively carrying out standardized transformation on the correlation characteristic quantity and the dot product characteristic quantity, substituting the correlation characteristic quantity and the dot product characteristic quantity into a Laplacian cumulative distribution function, calculating a probability value of a fault in each section, and judging a fault section according to a set probability threshold value. The method can effectively and reliably identify the early fault section of the power distribution network.

The invention discloses a distribution network overhead line fault self-healing method, system and device and a medium, and belongs to the technical field of power system fault self-healing, and the method comprises the steps: laying a synchronous phasor measurement unit, and generating a unified phasor reference through cloud edge cooperative calculation; the edge coordination engine calculates the load flow change after loop closing by means of a unified phasor reference and an instantaneous topological state to form an action sequence; the local controller obtains a coordination coefficient and controls the pre-compensation of the flexible interconnection device and the closing time of the section switch; pushing the temperature rise prediction value to a wire thermal model; and the edge controller circularly and adaptively corrects the compensation parameter of the flexible interconnection device, and writes the event into the self-healing knowledge base. According to the invention, automation and intelligentization of fault self-healing are realized, the efficiency of fault self-healing is significantly improved, and long-term stable operation of the power distribution network after fault recovery is ensured; and through intelligent and adaptive design, a brand new technical path is provided for long-term reliable operation of the distribution network.

The invention discloses a wide area measurement system abnormal data identification method, system and related device, and the method comprises the steps: carrying out the single electrical interval data abnormity identification of a single PMU at a plant station end, and obtaining a first abnormal data identification result; according to the first abnormal data identification result, when a certain measurement data in a single electrical interval is abnormal, comparing and identifying data anomalies of a plurality of PMUs at a plant-station end to obtain a second abnormal data identification result; if the same PMU is accessed to a plurality of electrical intervals on the same bus, performing wide-area level correlation comparison analysis on wide-area measurement system data at a master station end, and performing wide-area measurement system abnormal data identification through a power grid topology connection relation to obtain a third abnormal data identification result; and integrating the obtained abnormal data identification result, and obtaining an abnormal data identification result of the wide-area measurement system through collaborative analysis of a main station and a plant station. According to the method, the identification accuracy of the WAMS abnormal data is improved, and the work of diagnostic analysis of a master station is reduced.

The application relates to an intelligent power meter which comprises a core module, a first communication module and a second communication module. The core module is in local communication with a photovoltaic grid-connected inverter, the core module is in remote communication with a SEMS platform, the core module is used for bidirectional metering of electric parameters of a photovoltaic grid-connected system, judging whether local communication between the core module and the photovoltaic grid-connected inverter is normal, receiving electric parameters of the photovoltaic grid-connected system sent by the photovoltaic grid-connected inverter and uploading the electric parameters to the SEMS platform to realize remote load monitoring, and uploading the metered electric parameters of the photovoltaic grid-connected system to the SEMS platform to realize remote load monitoring; the first communication module is used for realizing local communication between the core module and the photovoltaic grid-connected inverter; and the second communication module is used for realizing remote communication between the core module and the SEMS platform. The application is suitable for a photovoltaic grid-connected end, cooperates with the photovoltaic grid-connected inverter to realize multiple functions such as energy consumption analysis, remote load monitoring and anti-backflow, can realize household use and industrial and commercial use, and has scalability.

The application relates to a cascade hydropower station power generation optimization scheduling method and device and computer equipment. The method comprises the following steps: according to historical wind power generation data, historical solar power generation data, historical water power generation data and power generation related parameters, estimated results of multiple resource parameters are calculated; according to the estimated results of the multiple resource parameters, an unbalanced risk constraint condition is constructed; the unbalanced risk constraint condition represents a constraint condition required to be met by monthly reservoir regulation of the cascade hydropower station in the case that wind power generation and solar power generation appear continuous shortages; under the constraints of the unbalanced risk constraint condition and system operation constraint conditions, a cascade hydropower station power generation optimization scheduling model is solved with the minimum operation cost as the target, and cascade hydropower station power generation scheduling results are obtained. The method can make up for the defect that the limited fluctuation ability of water power in cooperation with wind power and solar power in the month is ignored in the traditional annual reservoir power generation scheduling plan.

The invention discloses a real-time dynamic division-based regional inertia online estimation method, which relates to the field of regional inertia estimation and comprises the following steps of: 1) dividing a power system region in real time based on an aggregation type hierarchical clustering algorithm; 2) selecting a regional inertia frequency measuring point based on a Pearson product-moment correlation coefficient of power-frequency; and 3) estimating the regional inertia on line based on a difference type inertia estimation method. The invention also discloses a regional inertia online estimation system based on real-time dynamic division. According to the invention, when a disturbance event occurs in a power system, the power system region can be reasonably divided in real time; frequency measuring points more conforming to regional power change characteristics can be selected, and the regional inertia estimation accuracy is improved; the regional inertia can be accurately and stably estimated in real time, an important basis is provided for optimizing system inertia response and guaranteeing frequency stability, and the method has great significance in supporting safe and stable operation of a power grid with high-proportion new energy access.

The invention relates to the field of power grid dispatching, and discloses a generator set dispatching method, system and device and a storage medium. The generator set scheduling method comprises the following steps: acquiring generating capacity information and driving flow information of a plurality of generator sets; calculating the power generation efficiency of each generator set in a unit time period based on the power generation information and the driving flow information; and in response to the generated power adjusting instruction, controlling the opening degree of a driving valve which corresponds to the generator set and is used for controlling the driving flow of the generator set, so as to improve the power of the generator set with the highest generating efficiency and / or reduce the power of the generator set with the lowest generating efficiency. The method provided by the embodiment of the invention can realize rapid regulation and control of the power grid, improve the power generation efficiency and reduce the power generation cost.

The invention relates to the technical field of power system recovery control, in particular to a power grid black-start system and method based on cascade hydroelectric characteristics, and the method comprises the steps: constructing a software and hardware integrated system integrating physical equipment and intelligent control; situation awareness is carried out through the software and hardware integrated system, a power failure range after large-area power failure of a power grid is automatically identified, available cascade hydropower stations are positioned, and a black start plan is automatically triggered; the central decision-making unit simultaneously instructs a plurality of upstream hydropower stations to start units according to a preset rule so as to establish a plurality of independent power islands; after the frequency and voltage of each power island are stabilized, power is supplied to a next-stage transformer substation or power station in parallel, and partition collaborative recovery is carried out; dynamically distributing a load to be recovered, and performing synchronous parallel operation by using real-time phase angle difference data provided by a synchronous phasor measurement unit (PMU); and carrying out synchronous parallel operation on a plurality of subsystems which are stably operated, and gradually expanding a power grid architecture.

This invention provides a method and system for intelligent monitoring of synchronized phasors in a wide-area power grid based on quantum sensing, belonging to the field of power monitoring technology. The method includes: deploying a set of quantum sensing nodes and a set of conventional sensing nodes in a wide-area power grid; collecting phasor data from the quantum nodes for reliability analysis; screening out identified quantum sensing nodes with values ​​exceeding a preset threshold; constructing a wide-area power grid topology model; using the identified quantum sensing nodes to generate reference anchor point constraints to perform error propagation calculations on the wide-area topology model; obtaining a node error dataset for synchronization phasor calibration; and inputting the data into a monitoring terminal for processing. This invention solves the technical problems of insufficient monitoring accuracy and poor data reliability in existing wide-area power grid technologies. It achieves the technical effect of intelligent monitoring of synchronized phasors in a wide-area power grid based on quantum sensing technology, combined with node reliability analysis and reference anchor point error propagation, thereby improving the monitoring accuracy and data reliability of the wide-area power grid.

This invention provides an inertia estimation system, an inertia estimation device, a simulated inertia inverter, and a program that can calculate inertia in a power grid and control a simulated inertia inverter. [Solution] The inertia estimation system of the embodiment comprises an inertia estimation device and a simulated inertia inverter. The inertia estimation device comprises a measuring instrument database which includes at least the locations in the power system of measuring instruments that acquire measurement information used for inertia estimation, an inertia estimation unit which estimates the inertia in the power system, a setting calculation unit which calculates an inertia setting value to be set in the simulated inertia inverter, a communication unit which communicates the calculated inertia setting value, and an inertia calculation unit which calculates the inertia in the power system based on the inertia estimated by the inertia estimation unit and the inertia setting value. The simulated inertia inverter comprises a simulated inertia control unit which simulates the inertial operation of a generator, an inverter communication unit which receives the inertia setting value, and a constant setting unit which sets the inertia setting value in the simulated inertia control unit.

Various embodiments include a method for operating a control platform for energy exchanges between a plurality of energy systems. The method may include: receiving information related to an intended energy exchange from the energy systems; calculating optimum energy exchanges between the energy systems; receiving a plurality of possible energy exchanges s from at least one of the energy systems; for each of the received possible energy exchanges s, performing an optimization method, and therefore calculating an associated partial solution Z(ζs); calculating the total solution from the plurality of partial solutions Z(ζs) depending on their probability values ζs; and controlling energy exchanges between the plurality of energy systems by the control platform on the basis of the determined total solution.

An operation control device according to an embodiment of the present invention is an operation control device for an energy storage system that includes a battery and is linked to a power grid, and includes at least one processor; and a memory that stores at least one instruction executed through the at least one processor, wherein the at least one instruction may include an instruction to set a power price linkage mode selected by an operator or user when power supply from the power grid is available; an instruction to set a reference power for an inverter of the energy storage system according to the power price linkage mode; and an instruction to transmit the set reference power for the inverter to the inverter, and in the power price linkage mode, charging and discharging of the energy storage system can be controlled according to the power price provided by the power grid.

The invention provides an investment strategy optimization method and device based on an asset wall risk level, and relates to the technical field of power data processing. The method comprises the steps of determining a first asset wall risk level and a second asset wall risk level of a to-be-optimized power grid, the first asset wall risk level being determined based on the influence of a current year stock asset wall and a current year increment asset wall of the to-be-optimized power grid on current year asset wall risks; the second asset wall risk level is determined based on the influence of a medium-and-long-term stock asset wall and a medium-and-long-term increment asset wall of the to-be-optimized power grid on medium-and-long-term asset wall risk; determining a target asset wall risk level based on the first asset wall risk level and the second asset wall risk level; and optimizing the technical improvement investment strategy of the to-be-optimized power grid based on the voltage drop of the target asset wall risk level. The overall economic benefit of the power grid can be improved, and the investment benefit is remarkably improved while asset wall risk voltage drop is achieved.

The present application relates generally to Volt-VAR optimization for power distribution systems having advanced metering infrastructure (AMI). Distributed energy resources (DER) such as photovoltaic arrays are becoming prevalent in distribution systems. These DER systems inject power into the distribution system which can cause unfavorable changes, such as a rise in voltage across the feeder lines of the distribution system. Existing control proposals suffer from a number of shortcomings, drawbacks and disadvantages. In some instances, traditional controllers for distribution systems with DER systems may require information related to the arrangement of the distribution system which is unknown and cannot be provided by the advanced metering infrastructure. There remains a significant need for the apparatuses, methods, systems and techniques disclosed herein.