Power Flow Management Research Articles

Hierarchical genetic optimization of a fuzzy logic system for energy flows management in microgrids

Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are nowadays widely adopted as hybrid techniques in improving goods and services. In this paper we present an interesting application of the fuzzy-GA paradigm to the problem of energy flows management in microgrids, concerning the design, through a data driven synthesis procedure, of an Energy Management System (EMS). The main aim consists in performing decision making for power flow management tasks in the proposed microgrid model, equipped by renewable sources and an energy storage system, aiming to maximize the accounting profit in energy trading with the main-grid. In particular this study focuses on the application of a Hierarchical Genetic Algorithm (HGA) for tuning the Rule Base (RB) of a Fuzzy Inference System (FIS), trying to discover a minimal fuzzy rules set as the core inference engine of an an EMS. The HGA rationale focuses on a particular encoding scheme, based on control genes and parametric genes, applied to the optimization of the FIS parameters, allowing to perform a reduction in the structural complexity of the RB. A performance comparison is performed with a simpler approach based on a classic fuzzy-GA scheme, where both FIS parameters and rule weights are tuned, while the number of fuzzy rules is fixed in advance. Experiments shows how the fuzzy-HGA approach adopted for the synthesis of the proposed controller outperforms the classic fuzzy-GA scheme, increasing the accounting profit by 67% in the considered energy trading problem, yielding at the same time a simpler RB.

Hybrid PV-Wind-Battery Based System for Household Applications Using DC-DC Converter

In this project, a control strategy for power flow management of a grid-connected hybrid PV-wind-battery based system with an efficient multi-input transformer coupled bidirectional dc-dc converter is presented. The proposed system aims to satisfy the load demand, manage the power flow from different sources, inject surplus power into the grid and charge the battery from grid as and when required. A transformer coupled boost half-bridge converter is used to harness power from wind, while bidirectional buck-boost converter is used to harness power from PV along with battery charging/discharging control. A single-phase full-bridge bidirectional converter is used for feeding ac loads and interaction with grid. The proposed converter architecture has reduced number of power conversion stages with less component count, and reduced losses compared to existing grid-connected hybrid systems. This improves the efficiency and reliability of the system.

An Isolated Three-Port Bidirectional DC-DC Converter with Enlarged ZVS Region for HESS Applications in DC Microgrids

In this paper, a two-stage three-port isolated bidirectional DC-DC converter (BDC) for hybrid energy storage system (HESS) applications in DC microgrids is proposed. It has an enlarged zero-voltage-switching (ZVS) region and reduced power circulation loss. A front-end three-phase interleaved BDC is introduced to the supercapacitor (SC) channel to compensate voltage variations of SC. Consequently, wide ZVS range and reduced circulation power loss for SC and DC bus ports are achieved under large-scale fluctuating SC voltage. Furthermore, a novel modified pulse-width-modulation (PWM) and phase-shift (PHS) hybrid control method with two phase-shift angles is proposed for BA port. And it contributes to an increasing number of switches operating in ZVS mode with varying battery (BA) voltage. Phase shift control with fixed driving frequency is applied to manage power flow. The ZVS range as well as the current stress of resonant tanks under varying port voltages is analyzed in detail. Finally, a 1 kW prototype with peak efficiency of 94.9% is built, and the theoretical analysis and control method are verified by experiments.

Power Flow Management of a Grid Tied PV-Battery System for Electric Vehicles Charging

The prospective spread of electric vehicles (EV) and plug-in hybrid EV raises the need for fast charging rates. High required charging rates lead to high power demands, which may not be supported by the grid. In this paper, an optimal power flow technique of a PV-battery powered fast EV charging station is presented to continuously minimize the operation cost. The objective is to help the penetration of PV-battery systems into the grid and to support the growing need of fast EV charging. An optimization problem is formulated along with the required constraints and the operating cost function is chosen as a combination of electricity grid prices and the battery degradation cost. In the first stage of the proposed optimization procedure, an offline particle swarm optimization (PSO) is performed as a prediction layer. In the second stage, dynamic programming (DP) is performed as an online reactive management layer. Forecasted system data is utilized in both stages to find the optimal power management solution. In the reactive management layer, the outputs of the PSO are used to limit the available state trajectories used in the DP and, accordingly, improve the system computation time and efficiency. Online error compensation is implemented into the DP and fed back to the prediction layer for necessary prediction adjustments. Simulation and 1 kW prototype experimental results are successfully implemented to validate the system effectiveness and to demonstrate the benefits of using a hybrid grid tied system of PV-battery for fast EVs charging stations.

On the Exploitation of Admittance Measurements for Wired Network Topology Derivation

The knowledge of the topology of a wired network is often of fundamental importance. For instance, in the context of Power Line Communications (PLC) networks it is helpful to implement data routing strategies, while in power distribution networks and Smart Micro Grids (SMG) it is required for grid monitoring and for power flow management. In this paper, we use the transmission line theory to shed new light and to show how the topological properties of a wired network can be found exploiting admittance measurements at the nodes. An analytic proof is reported to show that the derivation of the topology can be done in complex networks under certain assumptions. We also analyze the effect of the network background noise on admittance measurements. In this respect, we propose a topology derivation algorithm that works in the presence of noise. We finally analyze the performance of the algorithm using values that are typical of power line distribution networks.

A Transformerless Bipolar Multistring DC–DC Converter Based on Series-Connected Modules

This paper proposes a transformerless bipolar multistring dc–dc converter based on series-connected submodules. It is intended for converting dc voltage and managing power flow for medium-voltage high-power dc networks. This new converter has a flexible structure of multistrings and each string consists of four valves with their middle points crossly connected through two cost-effect dc capacitors to form power balancing channels between valves. Its transformerless solution and single-stage configuration greatly reduce the converter volume, weight, cost, and power loss. In this paper, voltage ratio range and its influence on submodule design are analyzed. Moreover, a control strategy with focus on current sharing control and submodule capacitor voltage control is proposed. A simulation model rated at ±10 kV 2 MW verifies the feasibility of the proposed dc–dc converter. Experimental results obtained from a 100-V 1.5-kW laboratory setup also confirm the validation of the proposal.

Robust Power Management Control for Stand-Alone Hybrid Power Generation System

This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.

A Flexible DC Voltage Balancing Control Based on the Power Flow Management for Star-Connected Cascaded H-Bridge Converter

This paper presents the flexible dc capacitor voltages balancing control method for star-connected cascaded H-bridge converters. In this paper, the power flows are analyzed by investigating all the converter's control freedoms. Based on the analyses, users can accomplish the dc capacitor voltage balancing with both negative-sequence current and zero-sequence voltage. These two kinds of control options are further integrated together with the defined weighting factor $K$ . The low-voltage ride-through operation of a proposed control method is also discussed in this paper. The control method is verified with a 220-V 1-kVA static synchronous compensators based on the star-connected cascaded H-bridge converters, and the experimental test results show that all the dc voltages are well regulated at the commanded value with different weighting factor $K$ .

Toward an Intelligent High Frequency AC Distributed Power System - Part I: Conceptual Design

High frequency AC (HFAC) distributed power systems (DPS), where electric power is delivered at up to multi-kHz via cables, is an alternative means to conventional centralized power systems. When armed with on-line data, the HFAC DPS can perform intelligent management of power flow and lends itself to a host of emerging applications. The key enabling feature to realizing intelligent management in the DPS is the creation of a communication framework that allows the various sources and loads in the system to communicate their status seamlessly with each other. Whilst data communication over conventional power grid lines has been routinely implemented, there is remarkably no evidence of similar development in DPS where potential benefits would be significant. One key challenge is that DPS systems invariably operate at high frequency, thus squeezing allowable bandwidths for data. This paper explores the means by which real-time information can be achieved without installing additional physical communication channels on an existing 50 kHz current-fed HFAC DPS in lighting applications. A communication protocol is methodologically developed to facilitate robust and efficient inter-device real-time communication. The conceptual design of an intelligent HFAC DPS is proposed and the fundamental requirements and communication challenges of the modem are presented.

Energy management of a grid-connected hydrokinetic system under Time of Use tariff

In this work, the optimal power scheduling for a grid-connected hydrokinetic-battery hybrid system is proposed to sufficiently explore hydrokinetic energy and to benefit customers at demand side. The developed model for the hybrid system’s optimal power flow management aims to minimize electricity cost subject to the power balance, hydrokinetic and battery storage outputs as well as other operational constraints. With respect to demand side management, an optimal control method is developed to schedule the power flow of hybrid system over 24-h. Simulations are performed using MATLAB (R2016a), and the results demonstrate that operating the proposed hybrid system under the developed optimal energy management model can reduce the operation cost and allow consumers to generate substantial income by selling power to the grid.

DC Networks Including Multiport DC/DC Converters: Fault Analysis

DC networks that include storage systems, renewable sources, dc loads, and front-end converters can provide some advantages as compared with ac grids. However, the interruption of fault currents is difficult due to no-zero crossing of the current. Moreover, the fault clearing time of traditional dc circuit breakers can be too long for protecting power electronics switching components. Multiport converters seem to be a good solution for solving the aforementioned problem. The introduction of a multiport dc/dc converter, along with its configuration and a centralized control for power flow management, is proposed in the initial sections of this study. After this, this paper focuses on the study of system behavior during fault functioning conditions. Both pole-to-pole and pole-to-ground faults are investigated. The authors propose some control strategies and hardware solutions to overcome dc protection issues during several fault types. Some numerical simulation results are provided.

A Distributed Model Predictive Control Strategy for Back-to-Back Converters

In recent years, model predictive control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. MPC offers many advantages over more traditional control techniques such as the ability to avoid cascaded control loops, easy inclusion of constraint, and fast transient response. On the other hand, the controller computational burden increases exponentially with the system complexity and may result in an unfeasible realization on modern digital control boards. This paper proposes a novel distributed MPC (DMPC), which is able to achieve the same performance of the classical MPC while reducing the computational requirements of its implementation. The proposed control approach is tested on a ac/ac converter in a back-to-back configuration used for power flow management. Simulation results are provided and validated through experimental testing in several operating conditions.

Grid-Connected PV-Wind-Battery-Based Multi-Input Transformer-Coupled Bidirectional DC-DC Converter for Household Applications

In this paper, a control strategy for power flow management of a grid-connected hybrid photovoltaic (PV)–wind-battery-based system with an efficient multi-input transformer-coupled bidirectional dc–dc converter is presented. The proposed system aims to satisfy the load demand, manage the power flow from different sources, inject the surplus power into the grid, and charge the battery from the grid as and when required. A transformer-coupled boost half-bridge converter is used to harness power from wind, while a bidirectional buck-boost converter is used to harness power from PV along with battery charging/discharging control. A single-phase full-bridge bidirectional converter is used for feeding ac loads and interaction with the grid. The proposed converter architecture has reduced number of power conversion stages with less component count and reduced losses compared with existing grid-connected hybrid systems. This improves the efficiency and the reliability of the system. Simulation results obtained using MATLAB/Simulink show the performance of the proposed control strategy for power flow management under various modes of operation. The effectiveness of the topology and the efficacy of the proposed control strategy are validated through detailed experimental studies to demonstrate the capability of the system operation in different modes.

Matlab/Stateflow based-Multiagent System Application for Energy Management of Microgrid with Stand-alone Operation

Considering the environmental concerns, limitation of natural resources and power demand pressure, there is a great need to involve the distributed energy resource (DER) which can be operated as interconnected or as stand-alone mode from the main power grid. This paper proposes an application of Matlab/Stateflow-based MAS for energy management and control in a hybrid energy system including diesel generation system. An overall power management strategy is designed for the proposed system to manage power flows among different energy sources and the storage unit in the system. A simulation model for the hybrid energy system was developed using Matlab/Simulink and SimPowerSystems. The system performance under the different scenarios was verified by carrying out simulation studies using practical load demand profile and real weather data.

Gossip Algorithms for Decentralized Congestion Management of Distribution Grids

The paper proposes a gossip algorithm-based architecture for managing power flows on radial distribution grids applying decentralized management of demand. Demand flexibility is associated with a cost-like utility function expressing the inconvenience caused by curtailment. Every node of the distribution grid participates in power flow management by sending locally measured and calculated values to its neighboring nodes following a peer-to-peer architecture. The proposed algorithm is based on the application of gossip algorithms to estimate locally critical physical quantities by reaching a global consensus. More specifically, the solution implements gossip algorithms to achieve consensus in aggregated demand and in minimum cost for curtailment of flexible loads/increase of controllable distributed generators.

Real-Time Monitoring System for a Utility-Scale Photovoltaic Power Plant.

There is, at present, considerable interest in the storage and dispatchability of photovoltaic (PV) energy, together with the need to manage power flows in real-time. This paper presents a new system, PV-on time, which has been developed to supervise the operating mode of a Grid-Connected Utility-Scale PV Power Plant in order to ensure the reliability and continuity of its supply. This system presents an architecture of acquisition devices, including wireless sensors distributed around the plant, which measure the required information. It is also equipped with a high-precision protocol for synchronizing all data acquisition equipment, something that is necessary for correctly establishing relationships among events in the plant. Moreover, a system for monitoring and supervising all of the distributed devices, as well as for the real-time treatment of all the registered information, is presented. Performances were analyzed in a 400 kW transformation center belonging to a 6.1 MW Utility-Scale PV Power Plant. In addition to monitoring the performance of all of the PV plant’s components and detecting any failures or deviations in production, this system enables users to control the power quality of the signal injected and the influence of the installation on the distribution grid.

Integrated Voltage and Power Flow Management Considering the Cost of Opera in Active Distribution Networks

The increasing penetration of distributed energy resources on the distribution networks have brought a number of technical impacts where voltage and thermal variations have been identified as the dominant effects. Active network management in distribution networks aims to integrate distributed energy resources with flexible network management so that distributed energy resources are organized to make better use of existing capacity and infrastructure. This paper propose active solutions which aims to solve the voltage and thermal issues in a distributed manner utilizing a collaborative approach. The proposed algorithms have been fully tested on a distribution network with distributed generation units.

Central versus localized optimization-based approaches to power management in distribution networks with residential battery storage

In this paper we propose two optimization-based algorithms for coordinating residential battery storage when solar photovoltaic (PV) generation in excess of load is compensated via net metering. Our objective is to balance increases in daily operational savings that accrue to customers with the management of reverse power flows and/or peak loads approaching a network capacity. To achieve this objective we present a central quadratic program (QP)-based algorithm, where residential customers implement a distributor-specified day-ahead battery schedule. We also present a local QP-based algorithm, where each residential customer implements a day-ahead battery schedule subject to three distributor-specified weights. To complete our assessment of the distributor benefit, both QP-based scheduling algorithms are applied to measured load and generation data from 145 residential customers located in an Australian distribution network. The results of this case study confirm both QP-based scheduling algorithms manage reverse power flow and peak loads within a distribution network. In the context of net metering, all customers exhibit the same operational savings when implementing the central QP-based algorithm, while the local QP-based algorithm disproportionately penalizes some customers.

Performance Analysis of Multi Functional VSC Based FACTS Devices in Power Flow Management

This paper illustrates the application of Voltage Source Converter (VSC) based Flexible AC Transmission systems (FACTS) controllers such as Static shunt Compensator (STATCOM) and Unified Power Flow Controller (UPFC) for power flow control. A unique modelling framework incorporating these FACTS controllers in Newton Raphson load flow solution is discussed. The effectiveness of both the devices for real power flows, power loss, reactive power injection and voltage profile improvement are analysed. The modes of operation of each device with respect to specified voltage are analysed. The performance of these devices under single line contingency is also discussed. Test results on standard 5 bus system and IEEE 30 bus test system are analysed which justifies the potency of these devices for the above said applications.

New Robust Energy Management Model for Interconnected Power Networks Using Petri Nets Approach

The problematic of energy management, particularly in terms of resources control and efficiency, has become in the space of a few years an eminently strategic subject. Its implementation is both complex and exciting as the prospects are promising, especially in relation with smart grids technologies. The deregulation of the electricity market, the high cost of storage, and the new laws on energy transition incite some significant users (collectivities, cities, regions, etc.) to form themselves into local producers in order to gain autonomy and reduce their energy bills. Thus, they may have their own sources (classic and/or renewable energy sources) to satisfy their needs and sell their excess production instead of storing it. In this idea, the territorial interconnection principle offers several advantages (energy efficiency, environmental protection, better economic balance). The main challenge of such systems is to ensure good energy management. Therefore, power distribution strategy must be implemented by matching the supply and the demand. Such systems have to be financially viable and environmentally sustainable. This allows among others to reduce the electricity bill and limit the systematic use of the national power network, typically using non-renewable sources, and thereby support sustainable development. This paper presents an original model for aid-decision in terms of grid configurations and control powers exchanged between interconnected territories. The model is based on Petri nets. Therefore, an iterative algorithm for power flow management is based on instantaneous gap between the production capability (photovoltaic, wind) and the demand of each user. So, in order to validate our model, we selected three French regions: the PACA region, the Champagne-Ardenne region and the Lorraine region. Due to their policy, their geographical and climatic features, we opted for two renewable sources: “wind” and “photovoltaic”. The numerical simulations are performed using the instantaneous productions of each region and their energy demand for a typical summer day. A detailed economic analysis is performed for two scenarios (with or without interconnections). The results show that the use of renewable energy in an interconnection context (i.e. pooling), offers serious economic and technical advantages.