High Renewable Penetration Research Articles

Enabling Inverter-based Resource Stability Control in Power Systems with High Renewable Penetration

Enabling Inverter-based Resource Stability Control in Power Systems with High Renewable Penetration

A High-Efficiency Low-Wearing Hybrid Voltage Regulator for Utility Applications

Step voltage regulator (SVR) has been utilized in power distribution systems for decades as the voltage regulation device. Due to the increasing integration of distributed energy resources, the conventional SVR is severely challenged by the modern power distribution pattern with high renewable energy penetration. The induced arc from the conventional SVR tap change and more frequent tap changes due to voltage instability from the renewable energy impose constraints on the conventional SVRs lifetime. Meanwhile, the conventional SVR device cannot regulate the voltage accurately since the SVR regulates the voltage step-by-step. This article proposed a hybrid voltage regulator with high-efficiency and low contact wearing, which can achieve arcless tap change and stepless voltage regulation by using a fractionally rated back-to-back power converter. The accurate load voltage regulation is guaranteed, while the tap changer mechanism remains in the system, which helps to promote the upgrade to the existing power distribution systems. The power converter capacity in the proposed topology is only 0.31% of the distribution transformer rating to achieve a stepless voltage regulation range of ±10%, significantly reducing the system cost compared with the full power electronics solutions and projects high total system efficiency. The proposed hybrid voltage regulator was simulated and experimentally validated. The experimental results demonstrate arcless tap change operation and stepless voltage regulation. Collaborative operation between the conventional mechanical tap change and the power converter operation is also demonstrated to acquire large voltage regulation with fast-acting voltage control.

Grid-Forming Control of Voltage Source Converters Based on the Virtual-Flux Orientation

The increasing penetration of renewable generation in power systems is causing growing concern about system stability. Grid-forming (GFM) control has been appointed as the technology required for achieving a high penetration of renewables in the grid, as it successfully contributes to the power system stability. This paper proposes a novel grid-forming control scheme for voltage source converters (VSC) achieving the operational characteristics of a virtual synchronous machine (VSM). The proposed scheme is based on the orientation of a defined virtual flux to a reference axis obtained from the emulation of the synchronous generator swing equation. The virtual flux is obtained by the integration of the VSC internal voltage and it is oriented to the reference axis by means of a flux controller that also controls the flux magnitude. In this way, the VSC synchronism is maintained, operating as a voltage source connected to the grid. Moreover, the flux orientation in turn allows to control the VSC active power, while the flux magnitude control allows to regulate the VSC reactive power or terminal voltage in isolated mode. The paper also demonstrates that the stability of GFM converters is negatively affected when emulating high inertia values. So, a stabilizer is also proposed for damping these modes. Finally, due to fact that GFM converters behave as voltage sources, their low voltage ride through capability becomes an issue, because they naturally respond to faults with high short-circuit currents, that cannot be withstand by power electronics converters. Therefore, a method for limiting fault currents is proposed as well in the paper. The proposed grid-forming control scheme has been implemented in a real-time control platform and validated using comprehensive simulation models in a real-time simulator for assessing its grid-forming capability.

Evaluation of Australia’s Generation-Storage Requirements in a Fully Renewable Grid With Intermittent and Flexible Generation

Energy storage is crucial for grids with high renewable penetration to ensure reliable power supply during low renewable generation periods and address the intermittency associated with weather-dependent resources. However, sizing grid-scale storage is challenging due to its interdependence on renewable generation and load profiles. This paper investigates the minimization of storage requirements for Australian grids as a case study in a fully renewable scenario and examines how inflexible generation (such as solar and wind) and flexible generation (such as hydro) affect the capacity requirements. We extend our analysis to the economic trade-off between investing in increased storage versus intentional excess renewable generation. Subsequently, the optimum generation-storage requirement is analyzed, and regional requirements with and without interconnectors are estimated. Finally, we analyze storage annual utilization and present a sensitivity analysis to variations in technology costs. The quantitative results suggest that optimal storage size is contingent upon the renewable mix, and while solar generation is cost-competitive, higher contributions from wind generation and strategic dispatch of hydro generation are required to achieve an optimum generation-storage solution. We show that storage with a power capacity slightly lower than the mean annual demand with a duration of one day is required for Australia’s National Electricity Market (NEM). These findings underscore the importance of carefully balancing the renewable mix to achieve an efficient and cost-effective grid. Based on estimated future costs for long-duration storage and generation technology, the optimum generation-storage solution will translate into an investment of approximately 9.8% of the country’s Gross Domestic Product (GDP)—this investment is achievable when amortized over 10–15 years for the transition to a near-100% renewable grid.

Research on Evaluation of Multi-Timescale Flexibility and Energy Storage Deployment for the High-Penetration Renewable Energy of Power Systems

With the rapid and wide deployment of renewable energy, the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance. The output power of renewable energy is uncertain, and thus flexible regulation for the power balance is highly demanded. Considering the multi-timescale output characteristics of renewable energy, a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper. Through the multi-timescale decomposition algorithm on the basis of mathematical morphology, the multi-timescale components are separated to determine the flexibility requirements on different timescales. Based on the obtained flexibility requirements, a multi-timescale energy resources deployment model based on bi-level optimization is established considering the economic performance and the flexibility of system operation. This optimization model can allocate corresponding flexibility resources according to the economy, flexibility and reliability requirements of the power system, and achieve the trade-off between them. Finally, case studies demonstrate the effectiveness of our model and method.

A modified controller scheme for frequency stability enhancement of hybrid two‐area power grid with renewable energy sources

AbstractThis paper proposes a modified optimal control strategy for enhancing the frequency stability of a power grid. The considered grid includes different generation sources and renewable energy distributed in two interconnected areas. This strategy is based on applying a modified control configuration based on two‐degree of freedom for an improved tilt‐integral‐derivative controller entitled () for load frequency control (LFC). This study considers the effect of the automatic voltage regulator (AVR) and its effect on the frequency stability. The modified 2DOF‐T controller is based on utilizing the merits of the two degree of freedom (2‐DOF) structure, and applying the fractional order. Also, an improved gradient‐based optimizer (GBO) is proposed to optimally adjust the gains of the developed control technique. For robust design of the proposed control strategy, the system constraints are considered besides the high renewable power penetration. The effectiveness of the proposed controller in LFC has been confirmed by comparing its efficiency with other control strategies' efficiency in previous studies such as modified TID (ITnD), and FO‐PID () controllers. Furthermore, in cases of high renewable penetration, the AVR with LFC is superior to conventional LFC in terms of decreasing the value of fluctuations while maintaining voltage and frequency stability.

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.

Towards reliability competition: Non-cooperative market mechanism under high variable renewable energy penetration

To encourage variable renewable energy (VRE) penetration, scholars put efforts in building cooperative market mechanisms. Under these mechanisms, VRE generators are treated as negative uncontrollable loads. The advantage of cooperative mechanism is that by cooperative aggregation of the uncertain sources (VREs and uncontrollable loads), some fluctuations cancel out. However, this study points out that the nature of cooperative mechanism will hinder further improvement for either the society-wise production efficiency or the VRE-wise economic efficiency. The key issue is that it is hard for the cooperative mechanisms to define positive marginal cost for VRE, thus blocking the value chain of carbon reduction. To solve the problem, this study proposes to consider reliability as a production characteristic of VRE generators. Based on these proposals, this study establishes a novel non-cooperative reliability competition mechanism for VRE market participation. Under this mechanism, the system is able to generated power at the lowest marginal cost considering both carbon cost and reliability cost. What’s more, the numerical simulation shows that: more VRE generators are able to achieve higher economic efficiency under non-cooperative mechanism compared to cooperative mechanism; the non-cooperative mechanism can provide clear signals for the internal and external marginal cost of generation reliability of VRE. It is shown that under the proposed mechanism, the reliability of VRE-included power generation system can reach the limit of technology in the long run.

Why we must move beyond LCOE for renewable energy design

• Wind and solar generation devaluation occurs for grids with high renewable shares • This effect, due to intermittency, dramatically reduces the value of generated energy • Cost of Valued Energy can be used to account for this intermittency penalty • Minimizing COVE can improve VRE system design to better meet demand The inherent intermittency of wind and solar energy challenges the relevance of Levelized Cost of Energy (LCOE) for their future design which neglects the time-varying price of electricity. The Cost of Valued Energy (COVE) is an improved valuation metric that takes into account time-dependent electricity prices. In particular, it integrates short-term (e.g., hourly) wind and solar energy “generation devaluation”, whereby high wind and/or solar energy generation can lead to low, and even negative, energy prices for grids with high renewable penetration. These aspects are demonstrated and quantified using examples of two large grids with high renewable shares with three approaches to model hourly price: 1) residual demand, 2) wind and solar generation, and 3) statistical price-generation correlation. All three approaches indicate significant generation devaluation. The residual demand approach provides the most accurate price information while statistical correlations show that generation devaluation is most pronounced for the Variable Renewable Energy (VRE) that dominates market share (e.g., solar for California and wind for Germany). In some cases, the cost of valued energy relative to levelized cost can be 43% higher for solar (CAISO) and 129% higher for wind (ERCOT). This indicates that COVE is a much more relevant metric than LCOE in such markets. In particular, COVE is based on the annualized system costs relative to the annualized spot market revenue, and thus considers economic effects of costs vs. revenue as well as those of supply vs. demand. As such, COVE (instead of LCOE) is recommended to design and value next-generation renewable energy systems, including storage integration tradeoffs. However, more work is needed to develop generation devaluation models for projected grids and markets and to better classify grid characteristics as we head to a carbon-neutral energy future.

A practical solution for excess energy management in a diesel-backed microgrid with high renewable penetration

One of the limiting factors in adding high levels of rooftop solar photovoltaic (PV) resources to isolated hybrid microgrids is the ability to maintain the minimum operating point of must-run diesel generators. This research investigates a proposed inexpensive and practical solution to mitigate excess energy from renewables (mainly PVs) while maintaining a diesel-backed grid's acceptable minimum down reserve. It includes the innovative use of a resistive dynamic load bank (DLB) during peak PV periods. A control algorithm was developed to monitor the grid's total generation and control the DLB such that conventional diesel generators are not pushed below a setpoint equal to their minimum reliable operating level defined by the local utility. The setpoint is adjustable to allow for changes in grid conditions over time, such as the addition of more renewable resources or grid upgrades. This DLB system, as a practical and low-cost PV excess energy mitigation solution, has been connected to the grid in coordination with the local utility on the island of Molokai in the Hawaiian Islands. The DLB system addition has enabled the utility to significantly increase the allowed customer-sited PV on the power system without sacrificing grid reliability.

Wind farm control for wake-loss compensation, thrust balancing and load-limiting of turbines

As renewable energy sources such as wind farms become dominant, new challenges emerge for operating and controlling them. Traditionally, wind farm control aims to dispatch power set-points to individual turbines to maximize energy extraction and, thus, their usage as assets. Yet, grid balance and frequency support are fundamental in presence of high renewable penetration and volatility of energy prices and demand. This requires a paradigm change, moving from power maximization to revenue maximization. In this paper, three active power control strategies pushing this shift of paradigm are investigated, namely: wake-loss compensation, thrust balancing, and load-limiting control.The findings of large eddy simulations of a reference wind farm show that wake-loss compensation indeed improves the power generation on waked wind farms, but at the price of increased structural loads on certain turbines. The addition of a thrust balancing can equalize the stresses of individual turbines and their wear in the long term, while still attaining the required power output at the farm level. Furthermore, load-limiting controllers could potentially aid by allowing maintenance to be scheduled in a single time window, thus reducing operation and maintenance costs.

Systematic Review on Deep Reinforcement Learning-Based Energy Management for Different Building Types

Owing to the high energy demand of buildings, which accounted for 36% of the global share in 2020, they are one of the core targets for energy-efficiency research and regulations. Hence, coupled with the increasing complexity of decentralized power grids and high renewable energy penetration, the inception of smart buildings is becoming increasingly urgent. Data-driven building energy management systems (BEMS) based on deep reinforcement learning (DRL) have attracted significant research interest, particularly in recent years, primarily owing to their ability to overcome many of the challenges faced by conventional control methods related to real-time building modelling, multi-objective optimization, and the generalization of BEMS for efficient wide deployment. A PRISMA-based systematic assessment of a large database of 470 papers was conducted to review recent advancements in DRL-based BEMS for different building types, their research directions, and knowledge gaps. Five building types were identified: residential, offices, educational, data centres, and other commercial buildings. Their comparative analysis was conducted based on the types of appliances and systems controlled by the BEMS, renewable energy integration, DR, and unique system objectives other than energy, such as cost, and comfort. Moreover, it is worth considering that only approximately 11% of the recent research considers real system implementations.

Sub Synchronous Oscillations under High Penetration of Renewables—A Review of Existing Monitoring and Damping Methods, Challenges, and Research Prospects

With the recent developments in renewable energy generation and addition of power electronic devices, power system dynamics have become extremely complex. One of the challenges faced due to this transition is the sub synchronous oscillations caused by the interaction of renewable energy sources and various components of the power grid. Recently reported incidents due to sub synchronous oscillations highlight the need of monitoring and suppression of these harmful oscillations in real time. This paper gives an overview of the phenomena of sub synchronous oscillations and discusses the existing monitoring and damping techniques along with their limitations. Further, it highlights the research trends along this path.

Solution of the emergency control of synchronous generator modes based on the local measurements to ensure the dynamic stability

Stochastic renewable sources of energy have been causing changes in the structure and operation of power systems. High penetration of this type of generation results in decreased inertia of a power system, increased active power fluctuations, and a higher probability of false tripping of emergency control devices. Traditional algorithms of emergency control are not adaptable and flexible enough for systems with high penetration of renewables and flexible alternating current transmission systems. Integration and development of phasor measurement units make it possible to create adaptable emergency control systems, which would require minimal pre-defined data. The purpose of this study is to develop an adaptable algorithm for turbine fast valving control synthesis and transient stability estimation for a generator. The suggested algorithm is based on the equal area criterion in the domain synchronous generator “torque–load angle”. The measurements of the generator operation under consideration are used as the input data for the steam turbine fast valving control synthesis. Thus, the algorithm becomes adaptable because no pre-defined parameters of a power system model are required. The suggested algorithm was tested on the power system model NE39bus using Matlab/Simulink. The efficiency of the suggested algorithm is verified and demonstrated.

Representative operating scenario selection with algebraic multi-grid clustering for integrated energy systems planning

Recent shifts towards higher renewable penetration in power systems, has resulted in increasing gas-fired generation capacity in systems without hydro or other fast responding alternatives, implying increased electricity and gas infrastructure interdependency. Furthermore, highly efficient combined heat and power (CHP) units lead to heat and electricity interdependency. It is crucial to consider these interdependencies in the expansion planning of energy systems for an effective and reliable investment planning and policy design. In this paper, the problem of integrated expansion planning of electricity, heat, and gas in presence of demand and wind uncertainty is addressed. Representative operating scenario selection with algebraic multi-grid clustering is used to model wind and demand uncertainties, and to address computational complexity of a central planning model. The simulation results on a modified IEEE-118 bus test system with a 14-node gas network shows that the algebraic multi-grid clustering outperforms the classical methods such as kmeans by following the benchmark case more closely.

Comparative study for four technologies on flexibility improvement and renewable energy accommodation of combined heat and power system

Insufficient flexibility of the combined heat and power (CHP) system brought by its inherent heat-electricity coupling limitation reduces its renewable energy consumption capacity. Accordingly, this paper integrates four technologies, including the electric boiler, heating energy storage, electrical energy storage and bypass compensation technology, into the CHP system for more flexibility. The flexibility improvement indicator and the operational model for the integrated CHP systems are developed from the feasible operation region perspectives. Besides, an operational optimization considering the punishment for renewable energy curtailment and load shedding is proposed to evaluate performance improvement quantitatively. Combined with the energy efficiency distribution within the feasible operation region, the operating performance promotion contributed by the technology integration is analyzed using a 350 MW CHP system. The results show that integrating the bypass compensation technology can increase the maximum heat-electricity ratio by 160.3% and the electricity adjustment capacity under the heating load of 375 MW by 90.95%in the same flexibility improvement rate. Besides, the electric boiler and bypass compassion technology effectively reduce total coal consumption due to their effectiveness in improving renewable energy consumption and the high energy efficiency distribution within the newly added feasible operation region. However, they hardly handle the load shedding. Inversely, the electrical and heating energy storage systems can address the load shedding but improve weakly renewable energy accommodation under a high renewable penetration rate.

An improved state machine-based energy management strategy for renewable energy microgrid with hydrogen storage system

Renewable energy (solar and wind) sources have evolved dramatically in recent years around the globe, primarily because they have the potential to generate environmentally friendly energy. However, operating systems with high renewable energy penetration remain challenging due to the stochastic nature of these energy sources. To tackle these problems, the authors propose a state machine-based energy management strategy combined with a hysteresis band control strategy for renewable energy hybrid microgrids that integrates hydrogen storage systems. By considering the power difference between the renewable energy source, and the demand, the battery’s state of charge, and the hydrogen storage level, the proposed energy management strategy can control the power of fuel cells, electrolyzers, and batteries in a microgrid and the power imported into/exported from the main grid. The results showed that the energy management strategy provides the following advantages: (1) the power supply and demand balance in the microgrid was balanced, (2) the lifespans of the electrolyzer and fuel cell were extended, and (3) the state of charge of the battery and the stored level of the hydrogen were appropriately ensured.

Power system preventive control aided by a graph neural network-based transient security assessment surrogate

In the context of the clean energy revolution and the high penetration of renewables and power electronics, the uncertainty level of operating states significantly increases, which brings new challenges to the safe and stable operation of power grids. Power system preventive control is an important measure to ensure the safe and stable operation of power systems by adjusting the active generation and nodal voltage of generators. In this paper, a power system preventive control algorithm aided by a Graph Neural Network (GNN)-based Transient Security Assessment (TSA) surrogate is proposed. A GNN-based fast contingency scanning model is constructed based on power network topology, which can predict the contingency scanning results rapidly only based on the power flow by transforming the original contingency scanning problem into the node classification problem on the GNN. The obtained GNN is then used as a surrogate model for TSA to speed up the solution of particle swarm optimization-based transient security-constrained optimal power flow. Numerical Tests are carried out in the IEEE-39 system and the test results indicate that the proposed method can significantly improve the efficiency without affecting the solution accuracy.

Oscillation Propagation Analysis of Hybrid AC/DC Grids With High Penetration Renewables

The high penetration of renewables has sparked new oscillatory concerns in hybrid AC/DC grids. Knowledge of the oscillation regarding its source and propagation mechanism, is crucial to system operation. In this respect, the frequency-domain modal analysis (FMA) provides a way (e.g., participation factor) to extract these oscillation properties, and has been widely applied in converter-based AC grids. Compared to AC grids, oscillation properties of hybrid AC/DC grids are much more complex. Such complexity mainly originates from the diversity of oscillation propagation behaviors in hybrid AC/DC grids, where a distinctive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">local-area</i> oscillation will emerge. Therefore, a dedicated oscillation propagation analysis for hybrid AC/DC grids is desired, which is the main focus of this paper. First, the mechanism of the distinctive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">local-area</i> oscillation is analyzed considering AC/DC coupled dynamics of converters. Then, a systematic method for the oscillation propagation analysis is presented, where indices for characterizing the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">local-area</i> oscillation and its impact area are established. Finally, some propagation properties are discussed, by which a strategy for the online oscillation source locating is designed. Case studies are carried out in a typical hybrid AC/DC grid to validate the propagation analysis in this paper.

An Efficient Power System Planning Model Considering Year-Round Hourly Operation Simulation

High renewable energy penetration increases the electricity seasonal imbalance in the long-term timescale. Power system planning needs to consider the optimal configuration of various flexibility resources and electricity balance in different timescales. The coupling of multiple timescales largely increases the computation complexity of the power system planning problem. Thus, this paper presents an efficient source-grid-storage co-planning model which incorporates a year-round hourly operation simulation. To improve the computation efficiency of the planning model, from the temporal scale, a self-adaptive compact panorama time series (CPTS) model is applied, which greatly reduces the number of variables related to short-term decisions. From the spatial scale, a network-constrained relaxed clustered unit commitment (NC-RCUC) model is introduced, which significantly reduces the number of variables related to unit commitment decisions. Case studies on the modified Garver’s 6-node system and HRP-38 system prove the validation and efficiency of the proposed model (“HRP” stands for high renewable penetration). The studies on the China power grid in 2035 demonstrate the future planning results of generation, transmission and storage in China power systems based on the proposed model.