Renewable Power System Research Articles

Quantitative assessment and optimization strategy of flexibility supply and demand based on renewable energy high-penetration power system

Quantitative assessment and optimization strategy of flexibility supply and demand based on renewable energy high-penetration power system

Employing battery energy storage systems for flexible ramping products in a fully renewable energy power grid: A market mechanism and strategy analysis through multi-Agent Markov games

In high-proportion renewable energy power systems, flexible ramping products (FRPs) are critical for mitigating the volatility of renewable energy outputs and enhancing the adaptability of power systems. This paper aims to explore a fully renewable energy power system, with a battery energy storage system (BESS) as the sole provider of FRPs. An innovative market mechanism and new approaches to market equilibrium analysis are introduced. Initially, a common day-ahead (DA) market is established, covering both electricity and ancillary services with FRPs. The setup allows FRP providers to make bidding decisions and get rewarded based on actual ramping mileages. A bi-level multi-agent Markov game (MG) model is formulated. The upper level integrates the proposed strategies of wind power plants (WPP), photovoltaic power plants (PVP), and BESS, while the lower level encompasses the joint market clearing mechanism. An iterative solution algorithm, using reinforcement learning, is also introduced to address the model, effectively circumventing the privacy concerns associated with traditional mathematical programming methods. The proposed solution models and strategies are validated and demonstrated to be effective through two illustrative examples, highlighting their application and relevance in fully renewable energy power systems.

Robust Distributed Load Frequency Control for Multi-Area Power Systems with Photovoltaic and Battery Energy Storage System

The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs.

Double-pancake superconducting coil integrated with DFIG-based wind power systems under voltage-dip events: Design and performance analysis study

The doubly fed induction generator (DFIG)-based wind turbine provides massive development in power generation. Uncertain power oscillations and voltage-dip events affect the stability of the DFIG. To mitigate the effect of voltage-dips in short period, superconducting magnetic energy storage (SMES), which possess rapid energy exchange and high power density, is integrated with large-scale renewable power systems. SMES is integrated at the DC link of the DFIG to ensure the power balance and fault ride-through (FRT) capability. During this operation, frequent current changes occur in the high-temperature superconducting (HTS) coil, which leads to an increase in AC losses. As a remedy, an additional power converter structure controlled with a model-predictive controller (MPC) is proposed. Firstly, a scale-down HTS double-pancake coil model is designed using a finite element model by which transport current loss and magnetic field formulation are studied. Additionally, the critical coil current is also verified through experimental studies. The effectiveness of the proposed MPC-based SMES integrated DFIG on DC link voltage and grid current under IEC-61000-4-11 standard, symmetrical and asymmetrical voltage-dip cases are investigated. The obtained results demonstrate that the proposed system effectively reduces transients in DC link voltage and improves the FRT capabilities of the grid.

Method for Wind–Solar–Load Extreme Scenario Generation Based on an Improved InfoGAN

In recent years, extreme events have frequently occurred, and the extreme uncertainty of the source-demand side of high-ratio renewable energy systems poses a great challenge to the safe operation of power systems. Accurately generating extreme scenarios related to the source-demand side under a high percentage of new power systems is vital for the safe operation of power systems and the assessment of their reliability. However, at this stage, methods for extreme scenario generation that fully consider the correlation between wind power, solar power, and load are lacking. To address these problems, this paper proposes a method for extreme scenario generation based on information-maximizing generative adversarial networks (InfoGANs) for high-proportion renewable power systems. The example analysis shows that the method for extreme scenario generation proposed in this paper can fully explore the correlation between historical wind–solar–load data, greatly improve the accuracy with which extreme scenarios are generated, and provide effective theories and methodologies for the safe operation of a new type of power system.

Rolling planning model for high proportion renewable energy generation power system considering frequency security constraints

In this paper, a rolling planning model for high proportion renewable energy generation power systems is proposed, considering frequency security constraints, to address the frequency stability challenges posed by increased integration of wind and solar energy into the power grid under the “double carbon” goal. First, this study establishes a frequency response model for a thermal generation unit (TGU) and analyzes the impact of the high proportion of renewable energy on system frequency stability. Subsequently, a dynamic frequency security constraint is formulated, which can be used in generation planning to address the frequency issues. Second, a bi-level rolling planning model for high proportion renewable energy generation power systems considering dynamic frequency security constraints is established. The upper level focuses on investment decisions. The lower level incorporates frequency security constraints into the operational simulation to guarantee the frequency stability of the power system when making decisions on the size of newly built TGUs annually. Finally, case studies are conducted to demonstrate the validity and effectiveness of the proposed rolling planning model.

Conceptual hybrid energy model for different power potential scales: Technical and economic approaches

This research attempts to address the gap between the theoretical fundamentals of hybrid renewable energy systems and their practical implementation at different scales through a new Conceptual Hybrid Energy Model (COHYBEM). The main objective was to develop a multi-variable model to allow a new complete and comprehensive techno-economic analysis of the performance of possible hybrid renewable power systems at different scales. The purpose is to evaluate the influence of critical parameters by changing key parameters in the developed model and identifying their impacts. It covers big data analyses, simulation and optimization of hybrid energy solutions, combining wind, solar and hydropower energy sources with the energy storage technology of pump hydropower storage. The research also denoted the Pareto front with the increasing power installed, for the maximum efficiency and total satisfied demand by Wind + PVSolar and by Hydro converges to a higher percentage, while a minimum waste by Wind + PVSolar is also progressing towards the increasing scales. In terms of investment costs for the 243 analyzed case studies, it varies between 45 k€ to 2.1 M€, resulting in a net present value (NPV) between 18 and 600 k€ and a payback period around 6–17 years depending on the power scale analyzed.

Comprehensive assessment and energetic-exergetic performance optimization of a new solar thermal electricity system based on Scheffler-type receivers combined with screw-type volumetric machines

This study explores the potential of a novel solar-powered cascade Rankine cycle system based on Scheffler-type receivers combined with screw expanders. Specifically, in this solar power system, steam is generated in the Scheffler-type receiver, which proves to be well performing compared with other technological solutions to exploit solar energy, due to satisfactory efficiency of the focal receiver that is able to curtail heat losses, even at high evaporation temperatures. Subsequently, steam expands in the screw machines which, unlike conventional steam turbines, are specially fitting in energy conversion with vapor-liquid mixes in the field from tens to hundreds of kW. In the present study, comprehensive assessment of this renewable energy power system is thoroughly conducted in a large range of operating states. For this purpose, specific numerical models and basic criteria fixed for the screw expanders and Scheffler receivers part-load behavior are combined with thermodynamic formulations established for energetic-exergetic performance optimization of the entire solar thermal electricity plant. Hence, parametric optimization of the major thermodynamic factors involved at part-load operating situations is conducted to enhance the energetic and exergetic efficiencies of the designed solar thermal power system.

Commercial EV fleet smart charging for cost reduction and renewables integration: A case study in Germany

The transition to electric mobility reduces transportation carbon emissions but presents challenges in integrating growing electricity demand with renewable electricity generation and power systems. Smart charging emerges as a key technology to minimize operational costs and support higher utilization of green electricity for electric vehicles (EVs). Market analysis indicates a trend towards dynamic electricity tariffs, incentivizing EV charging at times favourable to the electricity grid, yet existing literature fails to address smart charging technology in sync with times of lower electricity prices and higher renewables integration. This work examines different smart charging strategies for a commercial EV fleet in Germany, considering a Real-Time Pricing (RTP) tariff indexed to day-ahead market prices and renewable electricity integrations. HOMER Grid is used to model these smart charging strategies and generate new EV load profiles. Direct and indirect CO2 emissions and renewable electricity usage ratios are calculated based on detailed electricity grid and self consumption data. The resulting Levelized Cost of Energy (LCOE) is minimized, by adjusting solar PV and battery capacities. The adoption of an RTP tariff decreases the LCOE from €0.530 to €0.314 per kWh. A smart charging strategy designed to reduce peak demand and schedule charging at lower price times further reduces the LCOE to €0.283 per kWh. The lowest LCOE of €0.281 per kWh is achieved with 34.4 kWp of solar PV capacity and no batteries. The carbon impact is minimized with larger solar PV and battery capacities. The performed work indicates a favourable framework for EV charging integrators to maximize cost savings and renewable energy integration for an EV fleet charging use case.

A voltage-decoupled Zn-Br2 flow battery for large-scale energy storage

The flow battery represents a highly promising energy storage technology for the large-scale utilization of environmentally friendly renewable energy sources. However, the increasing discharge power of rechargeable battery results in a higher charge voltage due to its coupling relationship in charge-discharge processes, intensifying the burden of renewable energy power systems. Herein, we proposed a voltage-decoupled Na+-conducting Zn-Br2 flow battery (Ud-Na-ZBFB). Within a pH-regulation strategy, both neutral Zn/Zn2+ and alkaline Zn/Zn(OH)42− negative redox couples are integrated into one device, so as to increase discharge voltage a 0.5 V theoretical increase while remains a low charge voltage. The proof-of-concept Ud-Na-ZBFB demonstrates an unprecedented voltage characteristic, achieving a discharge voltage of up to 2.18 V while maintaining a remarkably low charge voltage of 1.78 V at a current density of 20 mA cm−2. Benefiting from the high discharge voltage, the peak power density of Ud-Na-ZBFB reaches 580 mW cm−2, nearly twice higher than the traditional ZBFB. Besides, the Ud-Na-ZBFB cycling operates for 45 h with excellent stability and resilience. With the “cycle-to-stage” operational mode, battery state of Ud-Na-ZBFB can be completely recovered after a long-term operation stage with several cycles, which electrolyte utilization efficiency of one stage is up to 41 %. This work offers a brand-new utilization pattern for high-power rechargeable battery that possesses a great potential in energy storage application scenes.

A novel enhanced performance-based differential search algorithm for the optimization of multiple renewable energy sources-based hybrid power system

A novel enhanced performance-based differential search algorithm for the optimization of multiple renewable energy sources-based hybrid power system

Optimal Battery Storage Configuration for High-Proportion Renewable Power Systems Considering Minimum Inertia Requirements

With the continuous development of renewable energy worldwide, the issue of frequency stability in power systems has become increasingly serious. Enhancing the inertia level of power systems by configuring battery storage to provide virtual inertia has garnered significant research attention in academia. However, addressing the non-linear characteristics of frequency stability constraints, which complicate model solving, and managing the uncertainties associated with renewable energy and load, are the main challenges in planning energy storage for high-proportion renewable power systems. In this context, this paper proposes a battery storage configuration model for high-proportion renewable power systems that considers minimum inertia requirements and the uncertainties of wind and solar power. First, frequency stability constraints are transformed into minimum inertia constraints, primarily considering the rate of change of frequency (ROCOF) and nadir frequency (NF) indicators during the transformation process. Second, using historical wind and solar data, a time-series probability scenario set is constructed through clustering methods to model the uncertainties of wind and solar power. A stochastic optimization method is then adopted to establish a mixed-integer linear programming (MILP) model for the battery storage configuration of high-proportion renewable power systems, considering minimum inertia requirements and wind-solar uncertainties. Finally, through a modified IEEE-39 bus system, it was verified that the proposed method is more economical in addressing frequency stability issues in power systems with a high proportion of renewable energy compared to traditional scheduling methods.

Challenges of New Energy Power Systems

At present, in the context of global energy transition, China is actively promoting the construction of a high-proportion renewable energy power system, but it faces multiple challenges. First of all, the increasing demand for new energy installed capacity and the challenge of power balancing ability make the system operation face complexity and uncertainty. Secondly, the reshaping of market mechanisms and business models, as well as complex challenges at the technical level, are also constraints. The key technologies involved include innovation and application in simulation analysis and mechanism cognition, system construction, energy frame and stability control.

Comparative analysis and optimal allocation of virtual inertia from grid‐forming and grid‐following controlled ESSs

AbstractA broad consensus of neutralizing the carbon dioxide emissions facilitates the transition to the renewable energy power system. Meanwhile, the concerns about the volatility of renewable energies are growing as the rotational inertia of power system becomes inadequate. To maintain the frequency stability of power system, some studies for configuring inertia energy storage systems (ESSs) are carried out, mainly focusing on the allocation of virtual inertia from grid‐forming ESS. In contrast, the allocation of virtual inertia from grid‐following ESS has not been well elaborated and the differences in virtual inertia provided by these two modes are yet to be revealed. Based on ‐norm and Kron reduction, firstly, the state‐space model of post‐disturbance system is established, together with the transient performance evaluation. Then the inertia characteristics of both grid‐forming and grid‐following devices are formulated, followed by the unified gradient descent optimization method for allocating virtual inertia. A modified IEEE 39‐bus system and its time‐domain simulations help in the verification of the contribution of this paper. Through the comparative analysis of corresponding optimal results, the conclusions from two aspects are drawn: in terms of transient frequency support, the grid‐forming devices can provide no less than better inertia support; with the higher power capacity and similar energy capacity, the grid‐forming devices can relieve the response pressure of other generators by approximately .

Improved load frequency control in dual-area hybrid renewable power systems utilizing PID controllers optimized by the salp swarm algorithm

Improved load frequency control in dual-area hybrid renewable power systems utilizing PID controllers optimized by the salp swarm algorithm

Optimal Sizing of Isolated Renewable Power Systems With Ammonia Synthesis: Model and Solution Approach

Optimal Sizing of Isolated Renewable Power Systems With Ammonia Synthesis: Model and Solution Approach

Optihybrid: a modified firebug swarm optimization algorithm for optimal sizing of hybrid renewable power system

AbstractIn areas where conventional energy sources are unavailable, alternative energy technologies play a crucial role in generating electricity. These technologies offer various benefits, such as reliable energy supply, environmental sustainability, and employment opportunities in rural regions. This study focuses on the development of a novel optimization algorithm called the modified firebug swarm algorithm (mFSO). Its objective is to determine the optimal size of an integrated renewable power system for supplying electricity to a specific remote site in Dehiba town, located in the eastern province of Tataouine, Tunisia. The proposed configuration for the standalone hybrid system involves PV/biomass/battery, and three objective functions are considered: minimizing the total energy cost (COE), reducing the loss of power supply probability (LPSP), and managing excess energy (EXC). The effectiveness of the modified algorithm is evaluated using various tests, including the Wilcoxon test, boxplot analysis, and the ten benchmark functions of the CEC2020 benchmark. Comparative analysis between the mFSO and widely used algorithms like the original Firebug Swarm Optimization (FSO), Slime Mold Algorithm (SMA), and Seagull Optimization Algorithm (SOA) demonstrates that the proposed mFSO technique is efficient and effective in solving the design problem, surpassing other optimization algorithms.

Performance analysis of IoT-enabled hydro-photovoltaic power systems considering electrical power mission chains

Synergistically and complementarily managing the operation of hydropower plants and other weather-dependent renewable energy generation plants (e.g., solar energy plants) provides an effective measure to improve the performance efficiency (PE) of renewable energy. However, environmental uncertainty and physical system unavailability pose challenges in assessing the PE of the power generation. This paper proposes an approach to synergistically and complementarily managing the operation of hydro-photovoltaic (HPV) power systems in IoT under uncertain environments and develops a mission chain-based PE model for quantifying the capacity of the fulfilment of a power supply mission to satisfy users’ demand for power. An importance measure-based restoration strategy is then proposed to enhance the PE of an HPV power system (PEPS). The approach is examined by taking a large-scale HPV in China in the case study. The results show that, in winters and in summers, the PEPS is higher than PE of a photovoltaic power system and a hydropower system, respectively, and the PEPS with the importance measure-based restoration strategy is higher than that under the random restoration strategy, respectively. The findings not only lay the foundation for the complementary operation of hybrid renewable energy power systems but also provide a reference for the restoration in case of power cuts.

Stability analysis of grid-connected inverter under full operating conditions based on small-signal stability region

Impedance analysis is a practical approach for assessing the small-signal stability of renewable energy power systems. However, existing research predominantly focuses on specific operating conditions, neglecting the fundamental principles governing stability evolution under time-varying operating conditions. This paper presents a methodology to develop the small-signal stability region (SSSR) for grid-connected inverters using the impedance method. A comprehensive stability analysis for grid-connected inverter systems is performed based on the stability region. Firstly, the multi-parameter SSSR of the grid-connected inverter is defined according to both the aggregated impedance criterion and the generalized Nyquist criterion. Furthermore, a polynomial approximation expression for the SSSR boundary is derived. Secondly, the sensitivity analysis of operating points and control parameters is performed under full operating conditions to investigate their impact on stability based on the quantified boundary. The analyses reveal that the stability of the grid-connected inverter system near the SSSR boundary decreases with increasing active power and decreasing reactive power but exhibits an initial increase followed by a decrease with a larger PLL bandwidth. Finally, the accuracy of the stability region and the influence of key parameters are verified through case studies and experiments. The study in this paper can be used for quantitative analysis of stability margins and decision guidance of control optimization for grid-connected inverters.

Applications of the Internet of Things in Renewable Power Systems: A Survey

Applications of the Internet of Things in Renewable Power Systems: A Survey