Power System Resources Research Articles

A quasi-optimal energy resources management technique for low voltage microgrids

The increasing penetration of Distributed Energy Resources (DERs) in modern power systems is introducing new challenges for system stability and control. The stochasticity of Renewable Energy Sources (RESs) and the unpredictable behaviour of demand, make it necessary to develop intelligent Energy Resources Management (ERM) methodology, able to actively regulate the actors of the electrical network. This paper proposes a new quasi-optimal control algorithm, designed for LV breaker devices, aiming to manage DERs in a distributed and scalable approach. The developed ERM technique is able: (1) to control the energy consumption at the Point of Common Coupling (PCC) (with the possibility to join Active Demand Response (ADR) programs or to provide flexibility/energy reserve), when the microgrid itself is connected to the main grid; (2) to control the frequency profile when the microgrid is operating in islanded mode, using information provided by real time measures.

Integration of Smart Grid Resources into Generation and Transmission Planning Using an Interval-Stochastic Model

In the power industry, the deployment of smart grid resources in power systems has become an issue of major interest. The deployment of smart grid resources represents an additional uncertainty in the integrated generation and transmission planning that raises uncertainties in investment-related decision making. This paper presents a new power system planning method for the integration of electric vehicles (EVs) and wind power generators into power systems. An interval-stochastic programming method is used to account for the heterogeneous uncertainties attributable to natural variability and lack of knowledge. The numerical results compare the multiple integration scenarios and verifies the effectiveness of the proposed method in terms of cost distribution and regret cost.

On the Performance of Quickest Detection Spectrum Sensing: The Case of Cumulative Sum

Quickest change detection (QCD) is a fundamental problem in many applications. Given a sequence of measurements that exhibits two different distributions around a certain flipping point, the goal is to detect the change in distribution around the flipping point as quickly as possible. The QCD problem appears in many practical applications, e.g., quality control, power system line outage detection, spectrum reuse, and resource allocation and scheduling. In this letter, we focus on spectrum sensing as our application since it is a critical process for proper functionality of cognitive radio networks. Relying on the cumulative sum (CUSUM), we derive the probability of detection and the probability of false alarm of CUSUM based spectrum sensing. We show the correctness of our derivations using numerical simulations.

Validation of Novel PLL-driven PI Control Schemes on Supporting VSIs in Weak AC-Connections

The integration of distributed energy resources (DERs) in modern power systems has substantially changed the local control capabilities of the grid since the majority of DERs are connected through a controlled dc/ac inverter interface. Such long-distance located DER installations, usually represented by current regulated dc sources, can inject large amounts of power into the main ac grid at points where the strength of the ac connection is low. The efficient and stable performance of such a power scheme is related to the capability of the control applied to retain the power extraction close to the maximum and simultaneously to regulate the dc-side voltage as well as the ac-side voltage magnitude at the weak ac connection point. This is implemented by designing the controllers of the voltage source inverters (VSIs) in a manner that reliably satisfies the above tasks. To this end, decentralized cascaded control schemes, driven by novel, locally implemented phase locked loops (PLLs), suitable to work in weak ac connections, are proposed for the VSI performance regulation by using new fast inner-loop proportional-integral (PI) current controllers. A decisive innovation is proposed by inserting an extra damping term in the inner-loop controllers to guarantee stability and convergence to the desired equilibrium. This is analytically proven by a rigorous analysis based on the entire nonlinear system model, where advanced Lyapunov-based methods are deployed in detail. As a good transient response of the VSI interface is indeed critical for the energy and grid system management, the conducted simulation and experimental results confirm that the proposed scheme efficiently supports the ac- and dc-side voltages of the VSI under different varying conditions in the power production or any voltage changes of the main grid.

Two-stage stochastic scheduling model of wind-photovoltaic-storage providing flexible ramp capacity

The increasing penetration of renewable energy resources in power system has contributed to the increasing demand for operation flexibility. To address the deficiency of flexibility in wind-photovoltaic-storage hybrid system with deepening penetration of intermittent and uncertain renewable energy resources, this paper proposes emerging flexible resources including wind, photovoltaic and energy storage providing flexible ramp capacity to improve flexibility. Considering the uncertainty of load and intermittent generation, the wind-photovoltaic-storage providing flexible ramp capacity are integrated into a two-stage stochastic dispatch model including 1h day-ahead unit commitment and 15min real-time economic dispatch. To test the efficiency of the proposed model, simulation are carried out on a modified IEEE 118-bus with 54 thermal units, the results indicate that wind-photovoltaic-storage providing flexible ramp capacity can effectively alleviate the deficiency of operation flexibility, and improve the overall economic benefit.

Flexibility Estimation and Control of Thermostatically Controlled Loads With Lock Time for Regulation Service

A virtual battery model is a simple and general method to quantify aggregate flexibility from thermostatically controlled loads (TCLs), enabling grid operators to effectively coordinate a large number of flexible building loads with supply-side resources in power systems. Lockout controls are designed to avoid wear and tear resulting from short-cycling of hardware. The lock on/off time could significantly affect aggregate flexibility from TCLs to provide ancillary services and may even fail control algorithms designed without considering the lock time constraints. This paper focuses on flexibility estimation and control design for TCLs with lock time constraints to provide frequency regulation service. We first investigate the potential impacts of lock time on TCLs' aggregate flexibility and control performance. Both control-dependent and control-independent power bounds are then derived, based on previous TCL switching operations and regulation signals, respectively. While the control-dependent method provides aggregate flexibility for a given control method, the control-independent method calculates the theoretical maximum of power bounds. Finally, two control algorithms are proposed to better distribute flexibility over time and thereby improve signal tracking performance. The proposed methods are illustrated and validated through simulations.

The role of geothermal resources in sustainable power system planning in Iceland

The aim of this paper was to understand the relevance of accounting for geothermal resource dynamics for sustainable energy system planning in Iceland. This included assessing the implications of transition to electric vehicles as a decarbonisation strategy in Iceland. Therefore, the energy and transport system model (UniSyD_IS) was linked to a geothermal resource dynamics model. This allowed to capture the effects of geothermal resource utilization for electricity production on a national energy systems level. A total of 16 different scenarios that vary in the rate of economic growth, conditions for electric vehicles and consideration of geothermal resource dynamics were analysed in relation to production patterns, cost, resource availability and emissions. Incorporating geothermal resource dynamics allows to provide more holistic insights for sustainable energy system planning in Iceland, especially regarding the availability of geothermal resources and production cost.

Driving Simulator for Electric Vehicles Using the Markov Chain Monte Carlo Method and Evaluation of the Demand Response Effect in Residential Houses

It is essential to secure flexible resources in power systems to increase the proportion of variable renewable energy generation systems. One flexible resource is demand response (DR) of the batteries of electric vehicles (EVs). In this study, we propose an electric vehicle driving simulator using the Markov chain Monte Carlo (MCMC) method and an EV demand response evaluation model. The former is a highly versatile EV driving simulator that can produce a random driving pattern based on actual EV fleet data, taking into account various features. The latter is a residential DR evaluation model that minimizes a household electricity bill based on the simulated fleet data and enables realistic DR operation using three processes: forecasting, planning, and operation. The contribution of this paper is to enable evaluation of realistic EV battery value in various housing and EV utilization combinations. We found that the EV battery control provides an economic benefit of US$62 (5% of the night-charging case cost) with only charge control and US$370 (31%) with charge and discharge control, as the average expected value based on our assumption of evaluation. Because 40-kWh EV batteries have a sufficiently large capacity to store surplus power from a rooftop PV, they can be operated by determining the operation schedule based on a fixed-fee structure without forecasting or planning.

A Heat Current Model for Heat Transfer/Storage Systems and Its Application in Integrated Analysis and Optimization With Power Systems

Introduction of electric-heat conversion and heat transfer/storage (EHCHTS) units into power systems is a feasible solution to reduce the curtailment of renewable energy resources in power systems and supply heat in a green way simultaneously. However, different transmission natures of heat and electricity make it complex and difficult to analyze and optimize the power system with EHCHTS units. This paper constructs a heat current model of a district heating network including an EHCHTS unit and applies Ohm's and Kirchhoff's laws to deduce the corresponding heat transport matrix, which is further integrated with the admittance matrix network equation of power systems to construct a unified power flow model of the power system with EHCHTS units. On this basis, the optimization cases show that the EHCHTS unit reduces the wind power curtailment from 22.9% to 13.4%, and most importantly, the heat transfer constraints should be carefully constructed and integrated into the entire system model for accuracy. Besides, heat storage capacity improvement, heat transfer enhancement, and thermal insulation performance upgrade all effectively reduce the total coal consumption and the wind power curtailment simultaneously.

A Day-Ahead Scheduling of Large-Scale Thermostatically Controlled Loads Model Considering Second-Order Equivalent Thermal Parameters Model

Among various kinds of flexible loads resources in power system, the thermostatically controlled loads (TCLs) are considered as the excellent candidates for the demand response (DR) programs due to the heat/cool storage characteristics. Effective operation and coordination of TCLs in DR programs requires an accurate model to capture the aggregate power. One appealing approach is the equivalent energy storage (EES) method, which describes the change of aggregate power offered by the TCLs as the dynamic of an energy storage model with limits on the output power and the energy capacity. In this paper, an EES model with the second-order equivalent thermal parameters (second-order ETP) model is established for interpretation of TCLs dynamic characteristics. Considering the internal and external heat exchange of the TCLs, the relationships between the heat exchange power and energy storage of the TCLs EES model are redefined. In order to exert the actual potential of TCLs in day-ahead scheduling, the time-varying charging-discharging power and energy storage constraints of the TCLs EES model are developed. By this way, more feasible scheduling results can be obtained. The performance of the proposed method is verified by the testing results.

Intelligent orchestration of database resources in power system

With the continuous development of cloud computing technology, the size of database clusters is getting larger and larger. The database resources in existing power systems need to be manually deployed, which puts great pressure on operation and maintenance personnel. Therefore, resource orchestration and automatic deployment are proposed and realized. This method implements a visual orchestration interface through the GoJS framework, establishes a deployment template, uses Spring template to encapsulate task execution scripts, orchestrates database instances, high-availability standby machines, and logical replication at one time, simplifying the deployment process. Practice shows that this method can be effective Reduce deployment time and improve work efficiency.

Multiscale Dynamic Correlation Analysis of Wind-PV Power Station Output Based on TDIC

The stochastic characteristics of wind power and photovoltaic (PV) make the resource allocation of power system difficult. Therefore, it is necessary to consider the correlation between the power generation of wind and PV power stations to avoid resource waste and guarantee system power supply, while the traditional correlation analysis method cannot accurately describe the multiscale and time-varying characteristics of the correlation. In this article, based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the time series of the wind and PV power generation was decomposed into multiscale components. Moreover, the time-dependent intrinsic correlation (TDIC) is introduced to excavate the local correlation of the power generation time series under the framework of a multi-time scale, the dynamic change of a correlation is captured by analyzing the TDIC plots. The analysis shows that the strength and nature of the association between wind and PV vary with time scales and time spells, reflecting rich, dynamic characteristics. The correlation variation of different scale components in local time is of great significance to power system operation, planning, and resource optimal allocation.

Investigation of different system earthing schemes for protection of low‐voltage DC microgrids

DC microgrids are expected to play an important role in maximising the benefits of distributed energy resources in future low carbon smart power systems. One of the remaining complex challenges is the requirement for effective DC protection solutions. The advancement of DC protection is hindered by the lack of good understanding and development of reliable and effective earthing schemes which can enable safe and secure operation of DC microgrids in both on-grid and off-grid modes. Therefore, this study discusses different DC microgrid earthing opportunities, and comprehensively evaluates through detailed simulation studies the influence of different earthing methods on the fault behaviour of DC microgrid. A transient model of an active DC microgrid is developed in PSCAD/EMTDC and used for the paper studies.

Application of renewable energy resources in a microgrid power system

In order to meet the power prerequisites of their citizens, many countries are heavily dependent on the utilization of fossil fuels for power generation. This has reduced the natural reserve of fossil fuels and caused a large percentage of greenhouse gas emissions (GHGs). It is imperative to harness energy from renewable energy resources (RERs) as a measure to supplement the authors’ daily energy needs from the conventional units. The proposed microgrid system deals with the incorporation of the wind turbine generator (WTG), diesel generator, hydro turbine, photovoltaic and battery storage system for optimisation of net present cost (NPC), annualised cost of the system (ACS), GHG, fuel cost, operating costs and cost of energy (COE) by using hybrid optimisation model for electric renewables using HOMER software. The system is designed with the energy demand of 618 kWh/day at a peak load of 72.5 kW. The values of NPC, COE, ACS and fuel consumption obtained in the optimised configuration are $942,654/yr, $ 127,415, $0.327/kWh and 51,236 L/yr. The simulation results obtained from the optimised scenario reveal that the utilisation of RERs has been found to be a cost effective means to supply remote areas.

A Novel Adaptive Supervisory Controller for Optimized Voltage Controlled Demand Response

Recently, it has been shown that voltage-controlled demand response (VCDR), which is based on the principle of the dependence of the active power of demand on the system voltage, can provide ancillary services to future power systems. Voltage control devices used for VCDR can improve system frequency stability to various extents, depending on their locations, load size and load-voltage dependency in the grid. Thus, designing a supervisory controller to guarantee that such devices are optimally utilized for VCDR is necessary, as this can contribute in enhancing system frequency stability. In this paper, a novel adaptive supervisory controller (ASC) is proposed to optimally use VCDR resources in large power systems for such purposes. To ensure the effective operation of the ASC, an assessment of the impacts of on-load tap changer (OLTC) transformers on the system frequency is essential. In this regard, clustering techniques and principal component regression are used as offline tools to evaluate the influences of OLTCs transformers on VCDR in large-scale power systems using the IEEE 39-bus test system. Also, to estimate the effects of the OLTC transformer clusters on VCDR, a comprehensive sensitivity analysis with respect to the gain of the modified OLTC controllers’ frequency input is conducted.

Flexible, reliable, and renewable power system resource expansion planning considering energy storage systems and demand response programs

This study presents a flexible, reliable, and renewable power system resource planning approach to coordinate generation, transmission, and energy storage (ES) expansion planning in the presence of demand response (DR). The flexibility and reliability of the optimal resource expansion planning are ensured by means of appropriate constraints incorporated into the proposed planning tool where thermal generation units, ES systems, and DR programs are considered as flexibility resources. The proposed planning tool is a mixed-integer non-linear programming (MINLP) problem due to the non-linear and non-convex constraints of AC power flow equations. Accordingly, to linearise the proposed MINLP problem, the AC nodal power balance constraints are linearised by means of the first-order expansion of Taylor's series and the line flow equations are linearised by means of a polygon. Additionally, the stochastic programming is used to characterise the uncertainty of loads, a maximum available power of wind farms, forecasted energy price, and availability/unavailability of generation units and transmission lines by means of a sufficient number of scenarios. The proposed planning tool is implemented on the IEEE 6-bus and the IEEE 30-bus test systems under different conditions. Case studies illustrate the effectiveness of the proposed approach based on both flexibility and reliability criteria.

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

The small signal stability of power systems integrated with fallback large‐scale distributed energy resources is of utmost importance during the perturbation conditions. Among the various renewable resources in power systems: photovoltaic, fuel cell, wind turbine, diesel engine, aqua electrolyser, battery, ultra‐capacitor, and flywheel is becoming more favored in last decades. AGC, a main control system of frequency modulation, must correctly alleviate the low frequency oscillations caused by the perturbation and variable output power of renewable resources. In this regard, FOBELBIC is here introduced to enhance the damping capability of AGC. Since both the frequency and tie‐line power oscillations must be concomitantly alleviated, the small signal stability problem has been multi‐objectively formulated. Due to the exploration capability of MOALO, it has been chosen to extract the optimal parameters of FOBELBIC. Furthermore, MOPSO, MOBA, and NSGA‐II have been studied to demonstrate the capability of MOALO. To verify and validate the damping performance of suggested controller, it has been evaluated in three‐area reconstructed power system under the load perturbations as well as wind speed and sun radiation variations, and at the same time compared with BELBIC and PID controllers. Finally, the simulation results have evidently confirmed the damping the performance of MOALO‐based FOBELBIC to enhance the small signal stability of hybrid power system. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019

Islanding Detection Method of Distributed Generation Based on Wavenet

Due to the increasing need to distributed energy resources in power systems, their problems should be studied. One of the main problem of distributed energy resources is unplanned islanding. The unplanned islanding has some dangers to the power systems and the repairman which are works with the incorrect devices. In this paper, a passive local method is proposed. The proposed method is based on wavelet transform and a new classifier named as wavenet. The wavelet transform is used to extract features from the current waveform of current at the point of common coupling (PCC) point. PCC is assumed as the connection point of distributed generation to the distribution system. The proposed method is implemented on a 15 bus grid in MATLAB/SIMULINK software. The results show the high accuracy of islanding detection of the proposed method. In this paper, one wind turbine is assumed as a distributed resource.

Day-ahead stochastic multi-objective economic/emission operational scheduling of a large scale virtual power plant

The reduction of global greenhouse gas emissions is one of the key steps towards sustainable development. The integration of Distributed Energy Resources (DERs) in power systems will help with emissions reduction. Virtual Power Plants (VPPs) can overcome barriers to participation of DERs in system operation. In this paper, a model is proposed for the energy management of a VPP including PhotoVoltaic (PV) modules, wind turbines, Electrical Energy Storage (EES) systems, Combined Heat and Power (CHP) units, and heat-only units. The multi-objective operational scheduling of DERs in the VPP focuses on maximizing the expected day-ahead profit of the VPP and minimizing the expected day-ahead emissions. The uncertainty of wind speed, solar radiation, market price, and electrical load is modeled using scenario based approach. Also, two-stage stochastic programming is implemented for modeling the VPP energy management. Three cases have been investigated for evaluating the proposed method: single-objective scheduling of VPP to maximize profit, single-objective scheduling of VPP to minimize emission and multi-objective economic/emission scheduling of VPP. The results indicate the appropriate economic and environmental performance of the proposed method, which provides the possibility of selecting a compromise solution for the VPP operator in accordance with environmental restrictions and economic constraints.

Design and Implementation of a Fully Controllable Cyber-Physical System for Testing Energy Storage Systems

Cyber-physical power systems integrate the various devices, which provide ancillary system services. In this paper, the design and implementation of a fully controllable cyber-physical system are presented. This system simulates the behavior of the real power systems and additionally assures controllable repeatable testing conditions, enabling investigations of energy storage systems. Ancillary system services provided by energy storages are especially crucial in the context of renewable energy sources and electromobility sector development. Credible tests of control strategies, realizing system services, require controllability of test parameters. Such investigations are impossible in a real power system, due to its inherent variability. The novel approach presented in this paper enables the management of power system resources supplied by various producers and ensures flexibility in the realization of assumed scenarios of power system operation. Such an controllable cyber-physical power system constitutes a suitable environment for tests of the effectiveness of ancillary services provided by energy storage systems because the system is independent of inherent variability of the real power system and enables flexible realization of the control algorithms developed for all of the system components (power source, loads, and energy storages). The voltage profile improvement in low-voltage grids has been shown in a case study confirming the applicability of the proposed approach.