Small Power System Research Articles

Modelling and complementary analysis of a small hybrid hydro-photovoltaic power system

Renewable energy sources, especially solar power combined with pumped hydro storage generation (PHSG), have emerged as a remedy to conventional power generation, providing important opportunities for the safe operation of electricity. However, renewable energy is intermittent and random due to unreliable solar radiation. In view of these considerations, this paper focuses on the flexible complementary regulation of the PHSG responding to the fluctuation of solar power generation. To implement the analysis, a mathematical model of the small hybrid hydro-photovoltaic power system is established. Based on the established model, the complementary characteristic between these two renewable energies is simulated at the second scale. The results show that the PHSG has the ability to respond to the disturbance of solar power due to the flexible transition between generator mode and pump mode. The implemented model and obtained conclusions help promote the efficient use of renewable energy systems and reduce power failure accidents.

Energy optimization mechanism using metastable-smart grid (MSSG)

The Smart Grid model uses energy from renewable sources and utilities to manage energy in a way that ensures uninterrupted power supply for users. In order to operate independently from the main power grid, a DC micro grid is a small power system that generates and uses its own DC electricity. Solar panels, fuel cells, and wind turbines are the most typical power sources for DC micro grids, with batteries used to store any extra energy. The independence of the power grid is one feature of a DC micro grid that promotes increased lifetime. Building owners have more latitude to pursue their sustainability goals since they have control over the production, delivery, and consumption of power. Super-twisting provides a dependable method and an effective instrument for the control of uncertain nonlinear systems by addressing the basic flaws of conventional sliding mode control, notably large control effort and chattering. Fractional order controllers provide greater design freedom than conventional integer order controllers. The purpose of this work was to create a metastable-smart grid(MSSG) user end model that could dynamically manage and optimize energy produced by renewable energy sources and the utility to ensure that customers always have access to electricity. Controlling these many power sources using MSSG and delivering energy in accordance with each user’s unique power plan is the responsibility of the central control unit of the distribution grid. The supply is only switched to solar by the central control unit if a user’s power consumption falls below a predetermined threshold. Giving consumers with less purchasing power more clout as a result.

Fast Frequency Support Through LED Street Lighting in Small Non-Synchronous Power Systems

Small-sized non-synchronous islands, which are inherently characterized by low system inertia, will face in the next years the challenge of integrating larger and larger amount of renewable energy sources, leading to further reduction of inertia. Several means to support inertia and frequency transients have been proposed in the literature, including energy storage systems, distributed generation, and demand response. LED street lighting systems are widespread control resources, which in a smart grid scenario, can be regulated by means of local or remote control signals. This article investigates the possibility to regulate the power consumption of LED street lighting to provide frequency support in a system characterized by reduced total inertia. Tests are carried out integrating the simulation of the non-synchronous power system of an Italian small island with the response of an actual LED street lamp, in a Power Hardware-in-the-Loop testing environment. Both synthetic inertia and fast frequency response approaches are tested and discussed.

Independent power producers and deregulation in an island based small electricity system: The case of Papua New Guinea

The small island economy of Papua New Guinea (PNG) is facing severe electricity shortages and is therefore turning to implementing broader power sector reforms as a vehicle to attract private capital and investments in electricity generation. This study, based on a case-study approach, revisits the reform progress and plans in the electricity sector of PNG alongside the development and integration of IPPs in its small power system. Lessons of reform experiences and IPPs integration are drawn from three other smaller systems of Nepal, Nicaragua and the Northern Territory of Australia including stakeholder consultations, which includes two IPPs of PNG. We find a widening gap between reform ‘theory’ and ‘practice’ in the PNG power sector. Cost reflective pricing is implemented while cost recovery is never achieved by the vertically integrated state-owned utility and the insolvency of this state-owned single buyer poses the greatest perceived revenue risk to the IPPs. This lack of revenue reimbursement to the IPPs by the single buyer is a barrier towards attracting private capital into electricity generation. We recommend that strong political will and strengthening of institutional arrangements are urgent reform measures to attract private capital in power generation as political instability continue.

A grid frequency control on small scale power system by introduction of variable speed diesel‐driven power plant

AbstractThis paper proposes the application of an adjustable speed diesel engine‐driven power plant employing a doubly‐fed induction generator to an isolated small‐scale power system including renewable power sources. This type of power plant can contribute to fast and flexible power balancing regulations under vacillating power supplies such as wind, solar, and other renewable power sources. Installation of a battery system is also considered, which can assist coordinately with the power plant to augment renewable power sources in the isolated power system.

Suppression of Chaotic Oscillations in Small Energy Systems

The paper considers the suppression of chaotic oscillations in small energy systems that occur in emergency modes and lead to the phenomenon of voltage collapse, which corresponds to the process of voltage drop in the network, which can be accompanied by a complete shutdown of the affected area. The paper also presents a method that has been developed and that allows changing the spectrum of Lyapunov’s characteristic indicators and converting chaotic oscillations in a small power system to regular dynamic modes. The method of synthesis of control actions is based on the theorem of topological equivalence of hyperbolic nonlinear systems and their linearized models as well as on and the use of numerical integration of nonlinear differential equations describing the behavior of power systems in order to construct a phase portrait and calculate Lyapunov’s characteristic exponents. The results of the work consist in the synthesis of feedback, which ensures the formation of a spectrum of Lyapunov’s characteristic indicators with negative values. The suppression of chaotic regimes occurs by forming a spectrum of negative Lyapunov’s characteristic indicators in a closed system. The parameters of the regulator in the feedback circuit are determined using the modal control method based on the solution of the matrix algebraic Sylvester equation. The solution of the problem of transition from a chaotic regime to a regular movement in a small power system is considered. To test the operability of the proposed method of chaos suppression, the spectrum of Lyapunov’s characteristic indicators is calculated and trajectories in the phase space of the initial nonlinear system and the system with control action are constructed. For energy systems with chaotic dynamics, synthesized feedback makes it possible to suppress chaotic fluctuations and switch to regular modes, thereby preventing the occurrence of emergency modes.

Fitness-distance balance based artificial ecosystem optimisation to solve transient stability constrained optimal power flow problem

ABSTRACT The Transient Stability Constrained Optimal Power Flow (TSCOPF) has become an important tool for power systems today. TSCOPF is a nonlinear optimisation problem, making its solution difficult, especially for small power systems. This paper presents a new optimisation method that incorporates Fitness-Distance Balance (FDB) with the Artificial Ecosystem Optimisation (AEO) algorithm to improve the solution quality in multi-dimensional and nonlinear optimisation problems. The proposed method, named the Fitness-Distance Balance Artificial Ecosystem Optimisation (FDBAEO), also has the capacity to solve the TSCOPF problem efficiently. In order to evaluate the proposed algorithm, it was tested on IEEE CEC benchmarks and on an IEEE 30-bus test system for the TSCOPF problem. Simulation results were compared with the basic AEO algorithm and other current meta-heuristic methods reported in the literature. The results showed that the proposed method was more effective in converging at the global optimum point in solving the TSCOPF problem compared to the other algorithms. This situation indicates that the design changes made in the decomposition phase of the AEO were more suitable for simulating the operation of the algorithm in the real world. The FDBAEO has exhibited a promising performance in solving both single-objective optimisation and constrained real-world engineering design problems.

Coordinated Control of Wind turbine and Energy storage system for Microgrid Stability

In recent decades, the development of renewable energy has accelerated significantly due to several factors such as changing energy needs, the problem of global warming, and the depletion of fossil fuels. Wind energy is one of the renewable generation sources that can be used to achieve the EU's 2030 targets at a lower cost. However, its intermittent and stochastic nature could significantly impact the reliability and stability of the electricity system. Therefore, there is a clear necessity to mitigate power fluctuations to make the most of wind energy. To fill this gap, this paper presents a centralized control strategy based on a droop controller and a storage-integrated controller for a grid-connected variable speed wind power system (permanent magnet synchronous generator) (PMSG) to manage and stabilize the power output during intermittency periods. The main objective is to provide a stable U/f when a fluctuation event occurs. A grid failure scenario was tested to see how the control system behaves in the event of an unexpected fluctuation and its role in the stability of the power system under varying wind speed and load conditions. The effectiveness of the proposed control method was tested using MATLAB/Simulink on a small power system. The simulation results demonstrate the control system’s performance in the stability of the U/f during grid interruption.

A Grid Frequency Control on Small Scale Power System by Introduction of Variable Speed Diesel-Driven Power Plant

A Grid Frequency Control on Small Scale Power System by Introduction of Variable Speed Diesel-Driven Power Plant

Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization

Owing to the environmental concerns and fossil fuel shortage, power generation from renewable energy source is becoming an alternative source and lead to hybrid power generations in the modern power system. The hybrid power systems are operated for efficient exploitation of clean and renewable energy. Consequently, optimal economic generation planning of hydrothermal plants with renewable energy sources constitutes the main thoughts of this research work. The novelty of this paper is to propose a new quasi-oppositional turbulent water flow optimization for the solution of hydrothermal generation scheduling problem with the integration of pumped storage and solar power systems, and to develop a hybrid power system model by taking into account the spillage effects of hydro plants, and the valve point loading effects, transmission losses and multi-fuel sources of thermal power plants. The effectiveness of the developed model is examined on a small, medium and realistic large-scale hybrid power systems and compared with the performance of other erstwhile approaches. Conclusively, the simulation studies show that: (1) the developed model affirms the maximum utilization of clean energy production, (2) the quasi-oppositional learning strategy unified with turbulent water flow optimization approach offers superior optimal solutions and computational efficiency in contrast with other whilom metaheuristic algorithms, and (3) precisely, the pollutant emissions can be reduced by 11.62 and 12.90% when thermal power generation is backed down by pumped storage power generation, and combined pumped storage and solar power generation respectively for the realistic large-scale hybrid power system. Critics of this study is that the proposed approach can offer better optimal solutions than other erstwhile approaches with regard to the solution quality and computational efficiency.

Direct Damping Feedback Control Using Power Electronics-Interfaced Resources

This paper proposes a direct damping feedback control method against power system oscillations under small or large disturbances. For a targeted oscillation mode, this control method continuously minimizes the difference between the real-time estimated damping ratio and a desired value by changing power outputs of selected inverter-based resources. The method adopts a proportional-integral controller whose parameters are tuned using a nonlinear single-input-single-output model on damping estimation and control with a single-oscillator equivalent regarding the targeted power system mode. Also, optimization of these controller parameters considers both robustness and time performance in damping control. The paper also proposes utilizing a “zero-th order” parametric resonance phenomenon to simplify the controller design. Tests on a small power system and a 140-bus 48-machine Northeast Power Coordinating Council system validate the effectiveness of the proposed damping controller utilizing battery-based energy storage systems.

Fault diagnosis of power grid based on variational mode decomposition and convolutional neural network

The distribution network has complex topological structure and many branches. So, the fault location is easy to be wrongly located. Therefore, a novel hybrid method of combining variational mode decomposition (VMD) and convolutional neural network (CNN) for fault location and fault type identification is proposed in power grid. A fault feature extraction method based on VMD and Hilbert-Huang transform (HHT) is designed. In this method, the VMD is used to analyze the characteristic features from fault transient signals of the positive sequence current. The fault features of the intrinsic mode function with more fault features are extracted through HHT. The extracted fault feature vector is used as the input of CNN to build fault diagnosis model. Finally, the fault diagnosis report is obtained by comparing and analyzing the output results of SoftMax layer. The experimental results show that this method can identify the fault location and type in the small current grounding power system model of relay protection dynamic simulation equipment. Meanwhile, the method is less influenced by fault resistance and fault distance and has good accuracy, thus having better accuracy and generalization ability than traditional methods.

Consumer-Driven Demand-Side Management Using K-Mean Clustering and Integer Programming in Standalone Renewable Grid

Many countries have larger land areas and scattered communities. Therefore, to electrify them, small standalone power systems are the more preferred and cost-efficient solution as compared to utility grid extensions. The main objective of a standalone power system is to supply cleaner, cheaper, and uninterrupted electricity. However, for standalone power systems, demand-side management always remains a challenging task. In this paper, a load scheduling algorithm driven by K-mean clustering and linear integer programming to schedule consumers’ appliances for the upcoming day is proposed. In addition, the basic power to run the necessary appliances is kept available in the system all the time. Furthermore, to assist the consumer in every situation, the battery storage system and the overall system size reduction are also taken into consideration. Consumer input is also used in scheduling the appliances. The proposed method is evaluated on the publicly available real-world dataset; the simulation results demonstrate that the proposed approach performs better, due to which the reliability and continuity of the system are increased.

Battery Energy Storage Participation in Automatic Generation Control of Island Systems, Coordinated with State of Charge Regulation

Efficient storage participation in the secondary frequency regulation of island systems is a prerequisite towards their complete decarbonization. However, energy reserve limitations of storage resources pose challenges to their integration in centralized automatic generation control (AGC). This paper presents a frequency control method, in which battery energy storage systems (BESSs) participate in automatic frequency restoration reserve (aFRR) provision, through their integration in the AGC of an island system. A local state of charge (SOC) controller ensures safe operation of the BESS in case of disturbances, without jeopardizing system security when available energy reserves are diminishing. The aFRR participation factors of regulating units are altered when the storage systems approach their SOC limits, re-allocating their reserves to other load-following units. Restoration of BESS energy reserves is achieved by integrating SOC regulation in the real-time economic dispatch of the system, formulated as a mixed-integer linear programming problem and solved every few minutes to determine the base points of the AGC units. A small autonomous power system, comprising conventional units, renewable energy sources and a BESS, is used as a study case to evaluate the performance of the proposed method, which is compared with alternative approaches to secondary regulation with BESS participation.

Mechanism design of incentive retail electricity prices

We consider the modern methods of stimulating the users to load leveling during the day, in particular, through the formation of price-dependent demand. The article proposes an incentive pricing mechanism based on game-theoretic approaches to modeling the behavior of participants in the electric retail market: the contract theory and the mechanism design. The proposed tariff menu for electricity is incentive-rational, incentive-compatible for user groups with different user preferences, and it has stimulating properties for shifting load from peak zones. The resulting solution implements a separating equilibrium, avoiding the "adverse selection" problem. The effectiveness of this pricing mechanism is demonstrated in the example of a small electric power system using real consumption.

Multi-objective multi-verse optimization of renewable energy sources-based micro-grid system: Real case

Hybrid micro-grid systems (HMGS) are small scale power system where the energy sources are installed to supply local customers. These systems may be considered as promising energy solution to meet the increased in energy demand and traditional sources depletion. Cost of electricity, system reliability, and environmental impacts of the system are three design criteria that must be considered in obtaining the accurate parameters of hybrid renewable energy system components. In this paper, hybrid micro-grid renewable energy system includes photovoltaic system, (PV) wind energy system, (WES) battery bank, (BB) and conventional diesel generator (DG) are proposed to meet the energy requirements in remote area, located in Red Sea called city of Bernice, Egypt, at 23° 54′ 31″ N, 35° 28′ 21″ E. Optimization of Cost of Electricity (COE), Renewable Factor (RF), and Loss of Power Supply Probability (LPSP) are main objective of the designing process of the hybrid system considered as the objective functions. Then, Multi-objective multi-verse optimization (MOMVO) algorithm is used with considering two scenarios, the first one is renewable sources and the second is renewable/diesel energy source. All the possible HMGS configurations namely: PV/battery, wind/battery, PV/wind/battery and PV/battery/diesel, wind/battery/diesel, PV/wind/battery/diesel are studied and analyzed. Moreover, one year hourly meteorological weather data for case study are recorded. Reverse osmosis desalination (ROD) is considered in conjunction with the residential load. The proposed power management strategy is used to manage the system operation when supplying the load. A linear fuzzy membership function is used for purpose of decision making. The simulation results show that MOMVO produces appropriate components size and the PV/wind/battery/diesel is the optimum configuration with values of COE = 0.2720$/KWh, LPSP = 0.1397, and RF = 92.37% at w 1 = 0.5, w 2 = 0.3, and w 3 = 0.2. Sensitivity analysis is performed to show the effect of changing system parameters on the objective functions. It is also shown that the techno-economic feasibility of using HMGS for rural electrification systems and enhance energy access.

Home Energy Management System for Price-Responsive Operation of Consumer Technologies Under an Export Rate

Dynamic tariffs such as time-of-use (TOU) were introduced to motivate consumers to change the operation of their behind-the-meter (BTM) resources to reduce their power consumption during peak demand times. Recently, export rates have been implemented that reimburse consumers for electricity exported to the grid at a rate less than the retail rate to reduce reverse power flow in distribution power systems with high photovoltaic penetrations. Export rates are expected to be employed more widely, and therefore it is important to understand their impact on consumers, the operation of BTM resources, and the distribution grid. This paper presents a home energy management system (HEMS) capable of optimally scheduling BTM resources under a tariff with export rates. The proposed HEMS is formulated as a multi-objective model predictive control problem. In the paper, we analyze the performance of the proposed HEMS under an export rate including the operation of each BTM resource and the impact on the cost and comfort of homeowners. We also compare the performance of the proposed HEMS under an export rate with the HEMS under a TOU rate. Simulation results are presented for a small power system with several homes that employ the proposed HEMS to respond to an export rate. The simulation results show that the estimated energy cost savings for houses with HEMS and energy storage under an export rate is 20% compared to the baseline scenario with no HEMS. The results also demonstrate that the proposed HEMS responding to an export rate increases the self-consumption of buildings more than HEMS responding to a TOU rate.

System Modeling and Reliability Assessment of Microgrids: A Review

The world today is plagued with problems of increased transmission and distribution (T&D) losses leading to poor reliability due to power outages and an increase in the expenditure on electrical infrastructure. To address these concerns, technology has evolved to enable the integration of renewable energy sources (RESs) like solar, wind, diesel and biomass energy into small scale self-governing power system zones which are known as micro-grids (MGs). A de-centralised approach for modern power grid systems has led to an increased focus on distributed energy resources and demand response. MGs act as complete power system units albeit on a small scale. However, this does not prevent them from large operational sophistication allowing their independent functioning in both grid-connected and stand-alone modes. MGs provide greater reliability as compared to the entire system owing to the large amount of information secured from the bulk system. They comprise numerous sources like solar, wind, diesel along with storage devices and converters. Several modeling schemes have been devised to reduce the handling burden of large scale systems. This paper gives a detailed review of MGs and their architecture, state space representation of wind energy conversion systems & solar photovoltaic (PV) systems, operating modes and power management in a MG and its impact on a distribution network.

Techno-economic analysis and design of hybrid renewable energy microgrid for rural electrification

Abstract Electricity is the most sought after resource in this world and is crucial for the development of any community. The power system structure has been changing according to the evolving scientific technologies. A novel concept in this direction is a Microgrid (MG) which is a small power system having generation and distribution with negligible presence of transmission. A MG can operate in off-grid (standalone) or grid-connected mode. The objective of this study is to perform techno-economic analysis and to design a MG model for the purpose of rural electrification. The region being considered has different resources which are capable of providing reliable supply to the load. The proposed model is compared economically with the option of grid extension. The study considers power system reliability and economic feasibility as the primary objectives for MG modelling. The village of Jarre which is located in the eastern part of Ethiopian, Somali region, is selected for this study. Particle Swarm Optimization is implemented for obtaining the most economic and reliable MG having Hybrid Renewable Energy Sources (HRES). The simulation is performed using MATLAB and Homer.

Virtual Inertia Design Procedure for Energy Storage Systems to Increase Frequency Response Performance in Microgrids

The frequency instability caused by low system inertia is a common problem for small power systems such as microgrids since it can lead to stepping load shedding and generation tripping when disturbances occur. To alleviate the problem, this paper proposes a procedure for the virtual inertia design of an energy storage system (ESS) using the linear quadratic regulator (LQR) technique. The advantage of this proposed procedure is that it can separately manipulate the frequency response performance indices: the nadir and rate of change of frequency (RoCoF). The results confirm that the proposed procedure enables the microgrid to maintain frequency stability and avoid unnecessary load shedding whether operating in the grid-connected or islanding mode.