Power Load Demand Research Articles

Coordination and Optimization of CCHP Microgrid Group Game Based on the Interaction of Electric and Thermal Energy Considering Conditional Value at Risk

With the continuous advancement of power market reform, a cluster system composed of multiple microgrids can effectively improve the mutual support of energy between microgrids and improve the stability of system operation. This article comprehensively considers cogeneration, heat pumps, electrical energy storage, and thermal energy storage equipment to establish a framework for a multi-microgrid system. Secondly, due to the heterogeneity of wind power output, load demand and equipment parameters of different microgrids, considering the possibility of collaboration among multiple microgrids, the essence of energy complementarity to increase overall revenue is explained. On this basis, a cooperative game optimization dispatching model for microgrid group of cooling and heating power sources considering energy interaction is proposed. The Shapley value distribution method is used to distribute the surplus value generated by the cooperation. Furthermore, considering the uncertainty of wind power and load in multi-micro grids, a stochastic programming model based on conditional value-at-risk is established. The simulation analysis shows that the model proposed in this paper can effectively improve the surplus power and heat absorption capacity of the microgrid cooperative alliance, while reducing the impact on the power interaction of the main grid. The value of the conditional risk considered is also multi-microgrid. The system provides a reference plan for the trade-off between economic benefits and risk levels.

Feasibility of Grid-connected Solar-wind Hybrid System with Electric Vehicle Charging Station

Recently, renewable power generation and electric vehicles (EVs) have been attracting more and more attention in smart grid. This paper presents a grid-connected solar-wind hybrid system to supply the electrical load demand of a small shopping complex located in a university campus in India. Further., an EV charging station is incorporated in the system. Economic analysis is performed for the proposed setup to satisfy the charging demand of EVs as well as the electrical load demand of the shopping complex. The proposed system is designed by considering the cost of the purchased energy, which is sold to the utility grid, while the power exchange is ensured between the utility grid and other components of the system. The sizing of the component is performed to obtain the least levelized cost of electricity (LCOE) while minimizing the loss of power supply probability (LPSP) by using recent optimization techniques. The results demonstrate that the LCOE and LPSP for the proposed system are measured at 0.038 $/kWh and 0.19% with a renewable fraction of 0.87, respectively. It is determined that a cost-effective and reliable system can be designed by the proper management of renewable power generation and load demands. The proposed system may be helpful in reducing the reliance on the over-burdened grid, particularly in developing countries.

A Common Capacitor Based Three Level STATCOM and Design of DFIG Converter for a Zero-Voltage Fault Ride-Through Capability

To meet the augmented load power demand, the doubly-fed induction generator (DFIG) based wind electrical power conversion system (WECS) is a better alternative. Further, to enhance the power flow capability and raise security margin in the power system, the STATCOM type FACTS devices can be adopted as an external reactive power source. In this paper, a three-level STATCOM coordinates the system with its dc terminal voltage is connected to the common back-to-back converters. Hence, a lookup table-based control scheme in the outer control loops is adopted in the Rotor Side Converter (RSC) and the grid side converter (GSC) of DFIG to improve power flow transfer and better dynamic as well as transient stability. Moreover, the DC capacitor bank of the STATCOM and DFIG converters connected to a common dc point. The main objectives of the work are to improve voltage mitigation, operation of DFIG during symmetrical and asymmetrical faults, and limit surge currents. The DFIG parameters like winding currents, torque, rotor speed are examined at 50%, 80% and 100% comparing with earlier works. Further, we studied the DFIG system performance at 30%, 60%, and 80% symmetrical voltage dip. Zero-voltage fault ride through is investigated with proposed technique under symmetrical and asymmetrical LG fault for super-synchronous (1.2 p.u.) speed and sub-synchronous (0.8 p.u.) rotor speed. Finally, the DFIG system performance is studied with different phases to ground faults with and without a three-level STATCOM.

Recurrent Neural Network for Nonconvex Economic Emission Dispatch

In this paper, an economic emission dispatch (EED) model is developed to reduce fuel cost and environmental pollution emissions. Considering the development of new energy sources in recent years, the EED problem involves thermal units with the valve point effect and WTs. Meanwhile, it complies with demand constraint and generator capacity constraints. A recurrent neural network (RNN) is proposed to search for local optimal solution of the introduced nonconvex EED problem. The optimality and convergence of the proposed dynamic model are given. The RNN algorithm is verified on a power generation system for the optimization of scheduling and minimization of total cost. Moreover, a particle swarm optimization (PSO) algorithm is compared with RNN under the same problematic frame. Numerical simulation results demonstrate that the optimal scheduling given by RNN is more precise and has lower total cost than PSO. In addition, the dynamic variation of power load demand is considered and the power distribution of eight generators during 12 time periods is depicted.

The stability control for isolated wind‐diesel power system based on the cross coupling effect model

In the isolated wind-diesel hybrid power system, the system voltage and frequency may be affected simultaneously by the fluctuated wind turbine output power and variable load, which can make the system crash in extreme cases without control strategy. Therefore, in order to reduce the voltage and frequency deviation caused by system power fluctuation, both the battery and super twisting algorithm sliding mode state observer (STATCOM) are equipped to adjust the active power and reactive power for load power demand in the isolated small-scale power system. Then, the system mathematical model is established which considers the cross-coupling effect exist in the small-scale power system. In order to improve the control effect of battery and STATCOM, the unified control strategy is designed for battery and STATCOM by using the super twisting sliding mode state observer and the adaptive sliding mode controller according to the constructed cross-coupling effect model. Furthermore, the parameters of controller are further optimized by using the fuzzy method. Finally, the simulation experiments are performed by the real-time digital simulator to validate the effectiveness of the proposed control strategy under different operation points.

Robustly coordinated operational scheduling of a grid‐connected seaport microgrid under uncertainties

The modern seaport system is becoming more electrified by integrating energy storage system, offshore renewable energy sources (RESs), and shore-to-ship power supply system. The energy management and operational scheduling aim to maximise the profit gain by transacting energy with the main grid, reduce the operation cost while minimising the emission at seaport territory. This work proposes a robustly coordinated operational scheduling method of a seaport microgrid as a grid-integrated energy hub under uncertain renewable energy sources power output and load demand. In the day-ahead operation planning, generators, unit commitment and shore-to-ship load schedules are optimised. To address the uncertainty in the renewable energy sources, the day-ahead operation planning is modelled as a two-stage robust optimisation model with conflicting objectives and solved with the column and constraints generation algorithm. These results are used as input parameters for the hour-ahead generation scheduling in the following day. With uncertainty realisation, a shorter time horizon with higher time resolution deterministic optimisation is carried out for the generation dispatch. The proposed method is verified with the IEEE-33 bus distribution network with different uncertainties sets. The simulation results have verified the robustness and effectiveness of the method in dealing with uncertainties. Coordination between day-ahead and hour-ahead not only improves the accuracy and performance of the final dispatch result but also meets the distribution network constraints at generation and load buses.

Closed Loop Control of PV System Using Grey Wolf Optimization Algorithm under Partial Shading Condition

Globally there is an increased awareness of the havoc that climate change and rising pollution are due to the over consumption of carbon riddled fossil fuels making the environment unfit for living. Thus, it is important to make discerning choices to incorporate more clean energy to produce power. Therefore, Renewable energy emerges as an obvious alternative. Renewable resources like solar and wind are now being utilized for power generation. The power output of a solar panel depends on the amount of irradiance of sunlight which is also called insolation. The main drawback in solar is the power output of a PV panel for a particular irradiance is not a linear function of voltage and the power is maximum only at a particular voltage called optimum voltage. When the solar panel is subjected to non-uniform irradiance which is referred to us partial shaded condition, then there will be multiple power peaks in the P-V characteristics and it becomes unable to meet the load requirements. The proposed system will help to overcome this drawback as it consists of two cascaded boost converters. A battery is connected in parallel to output of MPPT boost converter so that load power demand is met by parallel combination of PV panel and battery. The system is optimized for best performance using multi objective GWO optimization technique. Thus, maximum power is extracted even under partial shading condition and constant power is supplied.

Quantification of distribution network security with high penetration of distributed generators

With the access of distributed generators (DGs), it is increasingly difficult to deal with the uncertainties of DG outputs. It is more important to maintain the secure operation of distribution networks (DNs). The power supply and load demand cannot balance at node. Therefore, the imbalanced energy are further transported in branches and feeders, which leads to the complex and uncertain characteristics of the whole DN. The cooperation of power electronic devices provides opportunities to maintain the security of DN. However, it is difficult to coordinate and schedule multiple types of controllable devices. In which reason the controllable devices cannot effectively improve the security of DN. In this paper, to generally quantify the security of DN, the power balance at node is considered firstly. Then the security of network is further discussed, including constraints of line power and node voltage. After that, security is quantified by evaluation indexes in the aspects of amplitude, frequency and intensity. Additionally, the improvement of system security brought by controllable devices are evaluated by the proposed indexes. Finally, IEEE 33-node system is adopted to conduct the case study. Results show that with the integration of controllable devices, the system security is effectively improved.

New soft‐switched high gain three‐port DC–DC converter with coupled inductors

In this study, a new high step-up non-isolated three-port DC–DC converter is proposed. A bidirectional buck–boost converter is used to interface photovoltaic battery and non-isolated load port. Compared to the other three-port converters, the presented topology has fewer component counts, which is the main merit of the proposed converter. The output voltage of the converter can be increased by using a three winding coupled inductor, a diode and a capacitor. Furthermore, since both main switches are turned on with zero voltage switching, switching losses is reduced and the efficiency of the converter is improved. Maximum power point tracking and maintaining the output voltage at a suitable level during the charging and discharging of the battery can be achieved by a simple controller. Moreover, according to the load power demand, three power flow paths will occur. The operation principle will be described in detail for three modes. Finally, the experiments with 400 W, 100 W, 40 V/400 V are implemented to verify the effectiveness of the converter.

A new flexible and resilient model for a smart grid considering joint power and reserve scheduling, vehicle-to-grid and demand response

The optimal, resilient and flexible operation of the power system is one of the most important challenges of the power grid. Fast resources as a backup capacity to provide power are one of the ways the power system to be more flexible and resilient. In this paper, a new joint power and reserve scheduling is done considering scheduling based on power instead of scheduling based on energy, the correct management of the thermal units’ ramp, the use of responsive loads includes a collection of commercial customers and plug-in electric vehicles (PEVs) in the secondary (15-minute) and tertiary (30-minute) reserves and discharge management of PEVs. A part of the power demand of these responsive loads is provided as free by renewable resources in times when there are no bad weather conditions. The use of responsive loads, correct management of the ramp of thermal units and a part of the discharge of PEVs can help restore the network quickly. The mixed-integer linear programming (MILP) method has been used to solve the joint power and reserve scheduling problem. The results show that the proposed model can lead to more flexibility and resiliency of the system and reduce the cost of the system.

Black Start Restoration of Islanded Droop-Controlled Microgrids

The electricity grid faces the possibility of outages due to extreme weather events, cyber-attack, and unexpected events. When these unwanted events occur, it is desired that electricity be restored as soon as possible to meet the power demands of critical loads. The microgrid approach to power restoration holds a lot of promise, since microgrids can operate in island mode. This paper presents a novel sequential restoration methodology for microgrid black start. The microgrid architecture considered is assumed to be operating in multi-master mode. The master distributed generators (DGs) are coordinated to operate together through droop control. Several operational constraints are formulated and linearized to realize a mixed-integer linear programming (MILP) problem. The method is studied on an islanded microgrid based on a modified IEEE 13 node test feeder. Detailed transient simulation in PSCAD was used to verify the accuracy of the restoration methodology. The developed restoration method can maximize the energy restored while ensuring good voltage and frequency regulation, and ensure that power scheduling mismatch is shared in the desired proportion.

Energy management of islanded microgrid for reliability and cost trade‐off with PV, energy storage, and diesel generator

Uncertainties in the solar photovoltaic (PV) power generation, random behaviour of consumer load power demand, and unexpected failures are the major factors for the consumer power interruption (CPI) hours, which reduce the reliable power supply rate or reliability index, of an islanded microgrid (IMG). One way to address this challenge is to complement the IMG with solar PV, energy storage system (ESS), and diesel generator (DG). This study first defines the reliability index of an IMG that equipped with solar PV, ESS, and DG. Then the authors propose an energy management strategy (EMS) for an IMG to maintain the reliability index above a given threshold limit while lowering the cost through higher utilisation of PV, lower CPI hours, and lower DG operating hours. They utilise real IMG consumers load power demand and solar radiance data for simulation studies to show how the proposed EMS achieves the desired trade-off in reliability and cost.

Real Time Simulation for Load Frequency Control of Multisource Microgrid System Using Grey Wolf Optimization Based Modified Bias Coefficient Diagram Method (GWO-MBCDM) Controller

This paper proposes a modified bias (MB) and coefficient diagram method (CDM) based PID controller as a first attempt in controlling frequency of a self-reliant microgrid (MG) system under extreme unfavourable scenarios. Recently developed meta-heuristic algorithm, Grey Wolf Optimizer (GWO), is used for optimizing the parameters of the proposed controller GWO). Frequency deviation arises in the system due to active power mismatch between load power demand and actual power generation. In order to overcome this problem the CDM based gain values and frequency biased parameters of the MG system are used for determining the ranges of the control parameters for optimization with GWO which ensures that the search points generated by the search algorithm are stable ones. Simulation of the proposed GWO optimized MB-CDM controller-based MG system has been successfully implemented in real time simulation platform using digital simulator OPAL-RT. The performance of the system is obtained using proposed controller under different real-life scenarios and results are minutely analysed. The results are further compared with other relevant recent controllers including particle swarm optimization (PSO) MB-CDM controller to demonstrate that the proposed controller is superior to all other controllers. In addition, sensitivity analysis of the proposed controller for the MG system is studied under varying system parameters. The Simulink results illustrate that the proposed controller gives the best dynamic response amongst all other considered controllers in terms of peak transient deviation and settling time.

Limits control and energy saturation management for DC bus regulation in photovoltaic systems with battery storage

Because of the considerable fluctuations of the power generation and load in Photovoltaic (PV) - Battery (BAT) systems, power management strategies become indispensable since BAT is needed to maintain the generation/load balance, and to regulate the DC bus. Indeed, energy management strategies must take into account the limits of the system, i.e. the nominal PV/BAT power rating and the state of charge (SOC) of BAT. However, the actual use might be different from the intended one, forcing the system to attain its limits. This paper is mainly focused on the limits control and energy saturation management applying to a sample standalone DC micro grid. It consists to share accurately the variable power loads among sources according to their ratings, including the regenerative breaking in minimum SOC'BAT case and the full supply of power load demand in maximum SOC'BAT case. Furthermore, the DC bus voltage is regulated to its predefined level, as a design parameter.The proposed control algorithms are detailed, and the system design during overstress and nominal conditions is given. The main advantage of this algorithm is its simplicity. The efficiency of the control strategy for energy saturation management is verified and analyzed through simulation/experimental system using Matlab/Simulink and DSpace. The results obtained show that the proposed technique can intelligently manage the energy flows and thus ensure that the system operates correctly and safely in the different modes: normal mode and saturated mode.

Decision making under wind power generation and load demand uncertainties: a two-stage stochastic optimal reactive power dispatch problem

ABSTRACT For the modern power systems with intensive renewable energy sources integration, the uncertainty analysis of its performance become necessary for desired decision making. An appropriate choice of modelling and handling methodology, for uncertain parameters associated with the renewable energy, remains one of major concerns for the power system engineers. This paper presents a stochastic optimization framework for some critical decisions making on reactive power dispatch in two consecutive stages by incorporating both generation outputs of wind farms along with load demand uncertainties. The proposed method is generic for optimal reactive power dispatch in any modern wind-integrated power system. A methodology based on scenario-based analysis is adopted for handling these uncertainties. Moreover, a hybrid fuzzy evolutionary algorithm (HFEA) is applied to obtain high-quality solutions for this complex two-stage stochastic optimization problem. Furthermore, the proposed HFEA-based stochastic optimization approach is tested on IEEE 14-bus power system with two distinct wind farms. The simulation results prove the robustness of HFEA for generating feasible and optimal solutions for all the considered scenarios.

A color harmony algorithm and extreme gradient boosting control topology to cascaded multilevel inverter for grid connected wind and photovoltaic generation subsystems

This paper introduces a hybrid control topology to cascaded multilevel inverter (CMLI) for grid connected hybrid system. The proposed control topology is joined implementation of color harmony algorithm (CHA) and extreme gradient boosting (XGBOOST). The modelling of CMLI is composed to gain the optimal control signal using the established controller. The proposed CMLI is composed with the decreased number of switches, diodes as well as sources. The aim of proposed control method is to meet the load power demand as well as to preserve the power regulation or maximal energy conversion of wind as well as solar subsystems. The proposed method strictly prohibits the difference present at output voltage of CMLI. Here, CHA is utilized for evaluating the optimal gain parameters in view of the variety of source currents from the normal value and it can be useful for building up optimal control signal dataset in offline way. In light of fulfilled dataset, the XGBOOST performs and predicts the most optimal control signals of the CMLI in the online way. The resultant control signals are utilized to control the insulated gate bi-polar switches (IGBT) of CMLI. Through, established model is implemented at MATLAB/Simulink working stage as well as implementation is considered by previous techniques. The efficiency for various sources using proposed and existing method is also analysed. The efficiency of PV and wind of the proposed technique are 99.3975% and 91.2138%.Overall, the outcomes of the comparison show the superiority of proposed method and confirm its potential to solve the issue.

Sizing and Control Algorithms of a Hybrid Energy Storage System Based on Fuel Cells

Growing consciousness of the threat posed by man-made climate change has spurred government institutions, industry, and science to find clean fuels to power economic activity. Fuel cells powered by hydrogen are one of the steps in gaining clean energy. To improve the efficiency of the fuel cell, the hybrid solutions are required. This article shows a new approach to the design and control of a hybrid energy storage system for portable applications. The methodology allows us to optimize the desired physical parameters of the elements (weight or size) in order to withstand the connected load power demand. Such an approach allows us to minimize weight, which is essential in portable systems. The methodology was proven by building a technology demonstrator. The measurements of physical objects verified the electrical parameters received during simulation and allowed a lower weight of the system, compared to the system based only on Li-ion batteries.

Peak Power Demand Management by Using SMC-Controlled Three-Level CHB-Based Three-Wire and Four-Wire SAPF

This article proposes a three-phase three-level cascaded H-bridge (CHB) based shunt active power filter (SAPF) for the management of peak power demand and the mitigation of multiple power quality problems. The proposed topologies are controlled by a sliding-mode control (SMC) for robustness and better dynamic response. The SMC is designed by mathematical modeling of SAPF. The proposed three-level SAPF for the three-wire system is developed by using three H-bridges and three coupling inductors. The same topology can be extended to the four-wire system without using any additional switches. The management of peak power demand of load is achieved by connecting batteries with the dc-link of the H-bridges. The three-wire topology can be used for harmonic mitigation, power factor correction, and compensation of current unbalances. The proposed topology in the four-wire network is required to suppress the neutral current flow in addition to the abovementioned power quality problems. The performances of proposed topologies are verified through MATLAB/ Simulink and validated through the experimental prototype developed in the laboratory.

Energy Management of Grid Interconnected Multi-Microgrids Based on P2P Energy Exchange: A Data Driven Approach

Grid interconnected multi-microgrids provides potential benefits to the consumers, where the microgrids (MGs) equipped with distributed generators (DGs), energy storage systems (ESSs), and diesel generators. However, intermittency of DGs, high cost of ESSs, and depleting fossil fuels are the major challenges for the economic operation of interconnected multi-microgrids. One potential way to address these challenges is to develop an energy management strategy (EMS) for the grid interconnected multi-microgrids. This paper proposes an EMS to reduce consumer energy consumption cost (ECC) using fuzzy-based peer-to-peer (P2P) energy exchange algorithm with dynamic pricing. In this context, the MGs consumers load power demand (LPD) and DGs output behaviors are modeled using random vector functional link network approach to predict future time slot values. Then, a fuzzy-based P2P energy exchange algorithm is developed to enable the surplus energy transfer to grid and/or MGs with dynamic pricing. Furthermore, an ESS charging/discharging energy control and diesel generator turn on strategies are developed based on the MGs deficit power. Then, the MGs consumer LPD reduction strategy is implemented based on the consumer ECC margin and energy consumption index. Finally, an EMS is proposed that includes on demand-supply strategy and consumer energy consumption cost reduction strategy based on the future time slot values. The novelty of the proposed work lies within the energy management of grid interconnected multi-microgrids and the reduction of consumers ECC through surplus energy transfer to grid and/or MGs using fuzzy-based P2P energy exchange algorithm with dynamic pricing. Historical data are used to demonstrate the effectiveness of the proposed EMS for grid interconnected multi-microgrids.

Smooth LMS‐based adaptive control of SPV system tied to grid for enhanced power quality

In this study, a novel smooth least mean square (LMS) algorithm for controlling PV inverter has been proposed to estimate the reference current for synchronisation of solar photovoltaic (SPV) to the grid. The proposed control extracts both active and reactive fundamental components of the load current with improved convergence rate. These currents are compared with sensed grid currents to generate gating pulses for a voltage source converter. It also compensates the load harmonics, reduces voltage fluctuation at point of common coupling and supplies the reactive power demand of the local load. The algorithm has been tested under steady state and transient conditions for input variation as well as load variation under the power factor correction mode of operation. The algorithm has been developed in MATLAB/Simulink. Further, the efficacy of the proposed control algorithm has been tested on prototype hardware setup developed in the laboratory using dSPACE1104. The total harmonic distortion at the grid side, obtained from simulated and hardware results are well within the IEEE standards.