High Penetration Of Renewable Sources Research Articles

Optimal operation of an electricity-hydrogen DC microgrid with integrated demand response

Uncertainties introduced by the high penetration of renewable sources, plug-in-hybrid-electric vehicle load demand, and limited capacity of firm generation available in a DC microgrid make the energy scheduling task rather challenging. This paper proposes a decentralized energy management scheme with a real-time pricing-based demand response implementation for a DC microgrid, considering the sectoral coupling between electricity and hydrogen energy. The objectives of the scheduling strategy are to maximize the profit of the DC microgrid operator and reduce the cost of energy use by the consumers, considering the interaction and interdependence of the electrical and hydrogen systems with a detailed DC microgrid network model and associated network constraints. The DC microgrid operator schedules flexible resources under its control (power procurement from the upstream grid, microturbines, battery energy storage, hydrogen storage, electrolyzer and fuel cell) and sets real-time prices. The consumers set their consumption patterns according to the real-time price. The DC microgrid operator side flexibilities are coordinated with the consumer side flexibilities (thermostatically controlled load like air-conditioner and plug-in-hybrid electric vehicle) using the decentralized “Alternating Direction Method of Multipliers” approach. The probabilistic Copula theory models correlated input uncertainties. Simulation results on a six-bus DC microgrid test system reveal that the operating cost of the DC microgrid operator reduces by ∼11.06% while the energy use cost of consumers reduces by ∼4.80% using the proposed approach for the system under study.

Control and Intelligent Optimization of a Photovoltaic (PV) Inverter System: A Review

PV power generation is developing fast in both centralized and distributed forms under the background of constructing a new power system with high penetration of renewable sources. However, the control performance and stability of the PV system is seriously affected by the interaction between PV internal control loops and the external power grid. The impact of the PV system on the reliability, stability, and power quality of power systems has restricted them to further participate in power supplies with a large capacity. Traditional control methods have become ineffective at dealing with these problems as the PV system becomes increasingly complex and nonlinear. Intelligent control as a more advanced technology has been integrated into the PV system to improve system control performance and stability. However, intelligent control for the PV system is still in the early stages due to the extensive calculation and intricate implementation of intelligent algorithms. Further investigations should be carried out to effectively combine intelligent control with the PV system to constitute an intelligent PV power system with multiple functions, high stability, and high-performance. This paper provides a systematic classification and detailed introduction of various intelligent optimization methods in a PV inverter system based on the traditional structure and typical control. The future trends and research topics are given to provide a reference for the intelligent optimization control in the PV system.

Multi-period network equilibrium in power system with energy storage on generation side

Due to the intermittency and unpredictability of wind and photovoltaic power, a power system with high penetration of renewable sources is always imbalanced. Energy storage on generation side can enhance the quality and reliability of such power systems. To study the impact of energy storage on power system networks, this study proposes a framework that regards the renewable energy power system with storage as a multi-period power supply chain network (PSCN). The equilibrium conditions are presented using the variational inequality theory and solved with a modified projection algorithm, followed by several examples based on real-world data to illustrate these findings. It is shown that energy storage enhances the reliability of power systems and increases the penetration of renewable power. Notably, the utilization efficiency of energy storage is lower than 50%, which is limited by the single utilization of energy storage facilities.

Impact of interconnections and renewable energy integration on the Philippine–Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah, Malaysia, as part of the Association of Southeast Asian Nations (ASEAN) Power Grid. This study focuses on modeling and evaluating the dynamic performance of the interconnected system, considering the high penetration of renewable sources. Power flow, small signal stability, and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances, utilizing the Power Systems Analysis Toolbox (PSAT) software in MATLAB. All components used in the model are documented in the PSAT library. Currently, there is a lack of publicly available studies regarding the implementation of this specific system. Additionally, the study investigates the behavior of a system with a high penetration of renewable energy sources. Based on the findings, this study concludes that a system is generally stable when interconnection is realized, given its appropriate location and dynamic component parameters. Furthermore, the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented

China’s role in scaling up energy storage investments

Accelerating the planning and development of a new power system that is more renewable energy-based is a strategic priority of achieving “dual carbon” goals (peaking carbon emissions before 2030 and becoming carbon neutral before 2060) in China. The large-scale development of energy storage technologies will address China’s flexibility challenge in the power grid, enabling the high penetration of renewable sources. This article intends to fill the existing research gap in energy storage technologies through the lens of policy and finance. Results indicate that policy uncertainties in renewable energy might undermine domestic investor confidence in energy storage technologies, while insufficient economic incentives may crowd out private sector participation. Drawing on international best practices, blended concessional finance, supported by development partners, can play a significant role in closing energy storage financing gaps in China and in countries of the Belt and Road Initiative (BRI). To deliver on China’s domestic and international climate commitments, this article makes three policy recommendations: (1) moving forward with a carbon pricing agenda that incentivizes energy storage investments in China; (2) tapping the potential of the domestic capital market to close financing gaps for novel energy storage technologies; (3) scaling up energy storage supply chains in BRI countries through multilateral cooperation.

Low-Voltage dc System Building Blocks: Integrated Power Flow Control and Short Circuit Protection

Low-voltage direct current (LVdc) systems are a promising technology for systems with a high penetration of renewable sources and storage that operate with bidirectional power flow. In this article, a fundamental building block for LVdc is presented for different applications, such as charge controllers, voltage regulation in street-lighting systems, and current limiters in meshed dc grids. The developed building block integrates a solid-state circuit breaker (SSCB) and partially rated power flow control converter (PFCC) capable of achieving the given control objectives with extremely high system efficiency and full short circuit protection.

Two-Stage Optimal Active-Reactive Power Coordination for Microgrids with High Renewable Sources Penetration and Electrical Vehicles Based on Improved Sine−Cosine Algorithm

As current global trends aim at the large-scale insertion of electric vehicles as a replacement for conventional vehicles, new challenges occur in terms of the stable operation of electric distribution networks. Microgrids have become reliable solutions for integrating renewable energy sources, such as solar and wind, and are considered a suitable alternative for accommodating the growing fleet of electrical vehicles. However, efficient management of all equipment within a microgrid requires complex solving algorithms. In this article, a novel two-stage scheme is proposed for the optimal coordination of both active and reactive power flows in a microgrid, considering the high penetration of renewable energy sources, energy storage systems, and electric mobility. An improved sine-cosine algorithm is introduced to ensure the day-ahead optimal planning of the microgrid’s components aiming at minimizing the total active energy losses of the system. In this regard, both local and centralized control strategies are investigated for multiple generations and consumption scenarios. The latter proved itself a promising control scheme for the microgrid operation, as important energy loss reduction is encountered when applied.

Advanced energy management strategy for microgrid using real-time monitoring interface

Recently, the integration of renewable energy sources in microgrids has seen a significant rise due to their attractive prices, reliability etc. However, besides the techno-economic benefits, the renewable energy sources are intermittent, and the high penetration of renewable sources into the microgrid poses design and operation challenges. Indeed, an efficient energy management strategy (EMS) is required to govern power flows across the entire microgrid. This paper introduces an advanced EMS design with a real-time monitoring interface for the effective operation of the hybrid microgrid and data analysis. The proposed advanced EMS model uses a real-time monitoring interface, and it provides the optimum operation and control in terms of balanced power supply and voltage profile with stable frequency. We designed the microgrid, which comprises hybrid sources such as solar and wind power sources, Li-ion battery storage system, backup electrical grids, and AC/DC loads, considering the functional constraints of a microgrid energy management and stability. In addition, the battery energy storage is effectively managed through the performance control of battery charging and discharging using an efficiency controller. The proposed system control is based on the optimum power supply of loads through the available renewable sources and the battery State of Charge (SOC). The microgrid measurement data is transmitted through the Python platform and a graphical user interface (GUI) software developed for data analysis. The simulation results using Matlab Simulink and Python platforms demonstrate the relevance and effectiveness of the proposed EMS and monitoring interface for the stable and reliable operation of the developed hybrid microgrid.

Design and Optimization of Fractional Order PID Controller to Enhance Energy Storage System Contribution for Damping Low-Frequency Oscillation in Power Systems Integrated with High Penetration of Renewable Sources

This paper proposes adding a controller to the energy storage system (ESS) to enhance their contribution for damping low-frequency oscillation (LFO) in power systems integrated with high penetration of different types of renewable energy sources (RES). For instance, wind turbines and photovoltaic (PV) solar systems. This work proposes superconducting magnetic energy storage (SMES) as an ESS. The proportional–integral–derivative (PID) and fractional-order PID (FOPID) are suggested as supporter controllers with SMES. The PID and FOPID controller’s optimal values will be obtained using particle swarm optimization (PSO) is used as the optimization method. Both local area and inter-area oscillation is considered in this work as a LFO. To investigate the impact of adding the SMES with the proposed controller, a multimachine power system with different integration scenarios and cases is carried out with a PV system and wind turbine. The system responses are presented and discussed to show the superiority of the proposed controller both in the time domain and by eigenvalues analysis.

On the Importance of using an AC or DC Network Model in the Multi-Period Secure Stochastic Optimal Power Flow for Settling a Multidimensional Day-Ahead Market

As the penetration of renewable energy sources increases, their variability and uncertainty have pushed the development of secure stochastic approaches to solving the secure day-ahead and intra-day multi-period optimal power flow. Some of these approaches, in addition to settling the energy market, also procure other products that generators can offer such as spinning reserves and ramping capability, the latter of which becomes even more important under high penetration of renewable sources. The resulting large scale nonlinear minimization problem makes using the more simple DC flow model of the network appealing, at least in the day-ahead stage. This work focuses on the impact of using an AC vs. a DC model of the network in the results of these multi-dimensional markets, using the Colombian system as a test case. The study implies that although the overall energy allocations may not change much from one model to another, other products may exhibit very different allocations under different network models.

Effective damping of local low frequency oscillations in power systems integrated with bulk PV generation

High penetration of renewable sources into conventional power systems results in reduction of system inertia and noticeable low-frequency oscillations (LFOs) in the rotor speed of synchronous generators. In this paper, we propose effective damping of LFOs by incorporating a supplementary damping controller with a photovoltaic (PV) generating station, where the parameters of this controller are coordinated optimally with those of a power system stabilizer (PSS). The proposed method is applied to damp local electromechanical modes by studying a system comprising a synchronous generator and a PV station connected to an infinite bus. The PV station is modeled following the instructions of the Western Electricity Coordinating Council. The problem is modeled as an optimization problem, where the damping ratio of the electromechanical modes is designed as the objective function. Constraints including upper and lower limits of decision parameters and damping ratio of other modes are considered by imposing penalties on the objective function. Different optimization algorithms are used to pursue the optimal design, such as political, improved gray wolves and equilibrium optimizers. The results validate the effectiveness of the proposed controller with PSS in damping local modes of oscillations.

Frequency stability of the Israeli power grid with high penetration of renewable sources and energy storage systems

As countries worldwide are integrating more energy storage systems and renewable energy sources, it is important to examine how these impact the frequency stability of the grid. In this study we explore this question by focusing on Israel in 2025. Based on the Israeli power grid model in 2025, which includes detailed information on the entire transmission network, generation units, and loads, we examine hundreds of different locations and sizes of renewable energy sources and energy storage systems, focusing on the frequency behavior in each scenario following the loss of a large generator. This is done using the industry-standard PSS/E simulator. The results lead to several design-level recommendations. One main conclusion is that the Israeli power system already has the required resources to maintain frequency stability in case a large generation unit is lost. However, to maintain a reliable system, policy makers should encourage that the existing and additional storage will contribute to frequency regulation when there is a risk of instability. We also find that the location of renewable energy sources and energy storage systems has an impact on the frequency stability, and that it is better to place storage systems in the south, and renewable energy sources in the north. However, at least until 2025 this impact is not yet strong enough to be a leading factor in determining the location of these sources.

Combination of compressed air energy storage and Kalina 11 cycles for sustainable energy provision; energy, exergy, and economic analysis

A novel efficient and entirely green hybrid energy conversion system comprising compressed air energy storage and Kalina KCS11 is proposed for peak shaving application and grid stability. The use of high-temperature thermal energy storage as a replacement for the traditional combustion chamber and a Kalina KCS11 with clean working fluid aims to minimize greenhouse gas emissions while adequately addressing intermittency and electricity curtailment of power grids with high penetration of renewable sources. The proposed system is comprehensively analyzed from the energy, exergy, and economic viewpoints. The thermodynamic simulation results indicate that the air turbine and pressure regulating valve have, respectively, 595.5 and 477.5 kW exergy destruction, accounting for around 40% of total exergy destruction. In addition, employing a KCS11 cycle recovers 57.95% of the heat dissipated in the CAES outlet. Accordingly, the proposed hybrid CAES-KCS11 system has round trip energetic and exergetic efficiencies of 52.97% and 46.28%, respectively. The economic analysis reveals that along with environmental benefits, it has a reasonable payback time of around 3.69 years. Moreover, a total benefit of 740 000 $ is gained during the service year of the system. The hybrid system is found to be more efficient compared to a stand-alone high-temperature hybrid CAES system.

Evaluating ammonia as green fuel for power generation: A thermo-chemical perspective

Energy storage will be necessary for a future power system with high penetration of renewable sources, mainly, wind and solar, to ensure the stability of the grid. In this context, power-to-chemicals is a promising concept for a medium/long-term storage horizon and a wide range of capacities. Within this alternative, ammonia rises as one of the fuels with the highest potential in a scenario targeting decarbonization. The first step is the production of ammonia using renewable energy sources, followed by its transformation into energy. This second area requires a deeper analysis at process scale in order to introduce this technology into the future power system. In this work, an assessment of an ammonia-based power plant is presented, focusing on the thermo-chemical route. A combined cycle is evaluated, considering different gas clean-up technologies to recover valuable components and comply with environmental restrictions. As a result, the total efficiency of the power facility reaches about 40%, limited by the maximum temperature allowed in the gas turbine. The influence of the price of ammonia is also evaluated due to the paramount importance of this parameter. The production cost ranges from 0.2 to 0.6€/kWh, with the lowest level corresponding to a scenario in which there is a significant reduction in the cost of renewable power generation and electrolysis technology. Therefore, the feasibility of the use of ammonia as an energy storage alternative is demonstrated, providing a powerful platform for the implementation of a power grid with high penetration of fluctuating sources.

Comprehensive assessment and multi-objective optimization of a green concept based on a combination of hydrogen and compressed air energy storage (CAES) systems

In this paper, a novel efficient and environmentally-friendly hybrid energy production/storage system comprising a compressed air energy storage, a heliostat-driven Brayton cycle, and a hydrogen production unit is proposed and thoroughly investigated. The aim is to minimize the pollutant emission of compressed air energy storage technology while adequately addressing intermittency and electricity curtailment of power grids with high penetration of renewable sources. The proposed system uses the surplus power and wasted heat of the solar-powered Brayton cycle to store pressurized air and hydrogen during off-peak periods, and releases them for extra power generation during peak demand periods. For the performance analysis of this hybrid solution, the reference system is precisely analyzed from thermodynamic and economic points of view. Then, training the results of the developed model employing an artificial neural network, four multi-objective optimization programs based on MOPSO, NSGA-II, PESA-II, and SPEA2 algorithms are performed to find an optimal trade-off between thermodynamic performance and economic attractiveness of the system. It is concluded that the system has an exergy round trip efficiency of 60.4% and a total cost rate of 117.5 $/GJ at the optimum solution. Applying the proposed method for the case study of Los Angeles with real historical data, 3313 ton/year Carbone-Dioxide emission is prevented, resulting in around 80,000 $/year environmental cost reduction. Also, the economic analysis indicates a payback period of shorter than 4.6 years for the system.

Resilient Power Converter: A Grid-Connected Converter With Disturbance/Attack Resiliency via Multi-Timescale Current Limiting Scheme

With the high penetration of renewable sources and flexible DC transmission systems, the power electronics converters are playing an important role in the modern power system. However, the grid-connected power converters may suffer from disturbances or cyberattacks from grid faults and communication networks. In this paper, we propose a control framework with multi-timescale constraints for the grid-connected converters. Firstly, the response sequence of different control layers is analyzed for a high power modular multi-level converter (MMC). Then, the operation boundaries of different control layers are derived considering the system stability and the protection requirement. Based on the operation boundaries at various timescales, a current limitation strategy is embedded in the controller to achieve the disturbance/attack resiliency for the grid-connected converter. Finally, simulations of a three-phase 40 MW 21-level MMC connected to a weak grid are performed to verify the resilient operation of the system.

Energy drive and management of smart grids with high penetration of renewable sources of wind unit and solar panel

This paper proposes a novel reinforcement learning based energy drive and management in smart grids incorporating the uncertain behavior of the electric vehicles and renewable energy sources. To this end, a novel stochastic framework based on evolving point approximation is devised to provide the most optimal power dispatch and minimize the total operation costs. In order to predict the output power of the renewable energy sources of wind unit and solar panel, the proposed approach uses Q-learning technique. This method enhances the prediction of conventional models such as neural networks. Due to the high complexity and nonlinearity of the final optimization framework, a new optimization approach based on dragonfly is devised. Moreover, a novel three-phase correction is introduced to help improving the quality of the final solutions and escape from the optima. The effect of charging/discharging of electric vehicles on the optimal energy management of the smart grid is assessed in two different scenarios. The performance of the proposed model is examined on an IEEE smart grid system.

Forecast‐based modeling and robust frequency control of standalone microgrids considering high penetration of renewable sources

Forecast‐based modeling and robust frequency control of standalone microgrids considering high penetration of renewable sources

Marginal Uncertainty Cost Functions for Solar Photovoltaic, Wind Energy, Hydro Generators, and Plug-In Electric Vehicles

The high penetration of renewable sources of energy in electrical power systems implies an increase in the uncertainty variables of the economic dispatch (ED). Uncertainty costs are a metric to quantify the variability introduced from renewable energy generation, that is to say: wind energy generation (WEG), run-of-the-river hydro generators (RHG), and solar photovoltaic generation (PVG). On other side, there are associated uncertainties to the charge/uncharge of plug-in electric vehicles (PEV). Thus, in this paper, the uncertainty cost functions (UCF) and their marginal expressions as a way of modeling and assessment of stochasticity in power systems with high penetration of smart grids elements is presented. In this work, a mathematical analysis is presented using the first and second derivatives of the UCF, where the marginal uncertainty cost functions (MUCF) and the UCF’s minimums for PVG, WEG, PEV, and RHG are derived. Further, a model validation is presented, considering comparative test results from the state of the art of the UCF minimum, developed in a previous study, to the minimum reached with the presented (MUCF) solution.

Power Balance Management of an Autonomous Hybrid Energy System Based on the Dual-Energy Storage

The urgent task of modern energy is to ensure reliable and efficient power supply to consumers, even those located in remote, far end places. A hybrid energy system with renewable energy sources is a promising way to ensure such a process. A characteristic feature of the modes of such systems, especially with high penetration levels of renewable energy sources, is the presence of ripples in the charge–discharge currents of the batteries used as energy storage devices. Batteries operation with such current fluctuations leads to rapid degradation of its characteristics as well as a reduction in its lifetime. Furthermore, it leads to a decrease in the reliability of the power supply system and an increase in the cost of generated electricity. A significant drawback of hybrid systems built according to well-known standard schemes is the inefficient use of the primary renewable energy, which is especially critical for energy systems located geographically in areas with severe climatic conditions. This article proposes a new construction method and an algorithm for controlling the modes of hybrid energy systems based on a dual-circuit energy storage device, which increases their reliability and energy efficiency. The prominent outcomes of operating modes of a hybrid power plant with a high penetration of renewable sources are presented, which proves that the proposed method of construction and the proposed control algorithm provide reliable and efficient control of the power balance of the hybrid power system in all possible operating conditions. In addition, the overall efficiency of the proposed renewable energy system is increased from 28% to 60% compared to standard hybrid power plants.