Penetration Of Renewable Generation Research Articles

Load-driven interactions between energy efficiency and demand response on regional grid scales

• We simulate bottom-up energy efficiency load impacts at building and grid scales. • Efficiency can interact differently with demand response on different scales. • We see no fixed relationship between efficiency and demand response; details matter. • Most often, there is competition between efficiency and demand response. • Strong complementarity is also possible, especially with controls-based efficiency. Energy efficiency (EE) has long been recognized as a source of value to the electricity grid. Especially with increasing penetration of variable renewable generation, demand response (DR) can also provide system value and support the evolving needs of the grid. Yet there has been little study to date of interactions between EE and DR that may complicate their grid impacts. In this study we perform bottom-up modelling of the interactive effects between EE and DR in buildings for three representative regions of the United States electricity grid. Leveraging new simulation tools that enable detailed modelling of the building stock, we synthesize system-level demand profiles for several scenarios representing different portfolios of EE measures. In each scenario, we couple the underlying building models with a database of DR-enabling technologies to estimate building-level DR capabilities and compute a system-level supply curve for DR. We assess the resulting EE and DR interactive effects based on an existing conceptual framework. The results show a complex relationship between EE and DR, with interactive effects whose size and direction can vary widely depending on the grid system, type of DR, and the framework level being considered. Most often, the overall effect is competition between EE and DR, but significant complementarity can also occur, especially when the EE portfolio includes controls measures. Our results suggest that EE and DR programs developed without considering interactive effects may erode the benefits of both resources, whereas a more integrated approach may yield increased benefits.

Optimal Power Flow in DC Networks With Robust Feasibility and Stability Guarantees

With high penetrations of renewable generation and variable loads, there is significant uncertainty associated with power flows in dc networks such that stability and operational constraint satisfaction are of concern. Most existing dc network optimal power flow (DN-OPF) formulations assume exact knowledge of loading conditions and do not provide stability guarantees. In contrast, this article studies a DN-OPF formulation, which considers both stability and operational constraint satisfaction under uncertainty. The need to account for a range of uncertainty realizations in this article’s robust optimization formulation results in a challenging semi-infinite program (SIP). The proposed solution algorithm reformulates this SIP into a computationally tractable problem by constructing a tight convex inner approximation of the feasible region using sufficient conditions for the existence of a feasible and stable power flow solution. Optimal generator setpoints are obtained by optimizing over the proposed convex stability set. The validity and value of the proposed algorithm are demonstrated through various dc networks adapted from IEEE test cases.

Fault current and fault voltage analysis of power transmission systems with high penetration of inverter-based wind generators

This paper highlights the evolution of wind power sources in the modern energy scenario, emphasizing the impacts of inverter-based generators, namely Full-Converter and DFIG (Doubly-Fed Induction Generator), on fault currents and fault voltages in transmission systems. The studies were carried out through computer simulations, with an EMTP (Electromagnetic Transients Program) type software. A power system with high penetration of such renewable generations was modeled and several contingency scenarios were simulated in a transmission line that performs the connection of the wind power plant to the grid. The scenarios included the variation of parameters such as fault type, inception instant angles, resistance, and distance, to explore the main differences between the contributions to the fault of a wind power plant and conventional generation. Among the atypical analyzed characteristics, the following can be highlighted: the absence of the DC (Direct Current) component for Full-Converter generation, independent of fault inception instant angle and distance variation; low levels of the fault contributions at the wind power plant terminal; low levels of voltages at the wind power plant terminal, evidencing the high SIR (Source Impedance Ratio) characteristic of these generations; atypical relations between the fault resistance and measured currents; and others. The obtained results show the importance of further studies on the impacts of inverter-based generations on fault currents and voltages, allowing developments that are able to improve control and protection systems for grids with high penetration of this wind generation topologies

Efficient Operations of Micro-Grids with Meshed Topology and Under Uncertainty through Exact Satisfaction of AC-PF, Droop Control and Tap-Changer Constraints

Micro-grids’ operations offer local reliability; in the event of faults or low voltage/frequency events on the utility side, micro-grids can disconnect from the main grid and operate autonomously while providing a continued supply of power to local customers. With the ever-increasing penetration of renewable generation, however, operations of micro-grids become increasingly complicated because of the associated fluctuations of voltages. As a result, transformer taps are adjusted frequently, thereby leading to fast degradation of expensive tap-changer transformers. In the islanding mode, the difficulties also come from the drop in voltage and frequency upon disconnecting from the main grid. To appropriately model the above, non-linear AC power flow constraints are necessary. Computationally, the discrete nature of tap-changer operations and the stochasticity caused by renewables add two layers of difficulty on top of a complicated AC-OPF problem. To resolve the above computational difficulties, the main principles of the recently developed “l1-proximal” Surrogate Lagrangian Relaxation are extended. Testing results based on the nine-bus system demonstrate the efficiency of the method to obtain the exact feasible solutions for micro-grid operations, thereby avoiding approximations inherent to existing methods; in particular, fast convergence of the method to feasible solutions is demonstrated. It is also demonstrated that through the optimization, the number of tap changes is drastically reduced, and the method is capable of efficiently handling networks with meshed topologies.

Power System Stability Analysis of the Sicilian Network in the 2050 OSMOSE Project Scenario

This paper summarizes the results of a power system stability analysis realized for the EU project OSMOSE. The case study is the electrical network of Sicily, one of the two main islands of Italy, in a scenario forecasted for 2050, with a large penetration of renewable generation. The objective is to establish if angle and voltage stabilities can be guaranteed despite the loss of the inertia and the regulation services provided today by traditional thermal power plants. To replace these resources, new flexibility services, potentially provided by renewable energy power plants, battery energy storage systems, and flexible loads, are taken into account. A highly detailed dynamical model of the electrical grid, provided by the same transmission system operator who manages the system, is modified to fit with the 2050 scenario and integrated with the models of the mentioned flexibility services. Thanks to this dynamic model, an extensive simulation analysis on large and small perturbation angle stability and voltage stability is carried out. Results show that stability can be guaranteed, but the use of a suitable combination of the new flexibility services is mandatory.

Distributionally Robust Optimization for Generation Expansion Planning Considering Virtual Inertia from Wind Farms

• The stability and reliability requirements in generation expansion planning are jointly considered. • A distributionally-robust-optimization-based generation expansion planning model considering the virtual inertia support from wind farms is proposed. • Frequency stability is guaranteed by inertia-based frequency requirements. • Balance between reliability and investment cost is achieved. High penetration of renewable energy generation imposes two significant challenges to power systems: the stability problem caused by low inertia and the reliability problem caused by generation uncertainties. Although these challenges have been widely recognized, their impacts on the optimal generation capacity mix have not been explicitly revealed and quantified. Luckily, with advanced converter control strategies, renewable generators may also provide the so-called virtual inertia similar to conventional inertia provided by thermal generators. This paper proposes a novel distributionally-robust-optimization-based generation expansion planning model considering the virtual inertia support from wind farms. The proposed model minimizes the generation expansion cost under uncertainty while maximizing the probability with which the system can fully absorb renewable energy generation. The constraints include expansion limits, unit commitment constraints, frequency requirements, virtual inertia provision, and distributionally robust joint chance constraints. The proposed formulation is recast into a mixed-integer second-order conic model and solved efficiently via commercial solvers. Case studies are carried on a 9-bus system and the IEEE 118-bus system to demonstrate the validity and scalability of the proposed method and highlight the importance of incorporating inertia response services

Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant

As wind and solar technologies improve and their costs decrease, the share of power produced by these sources will increase. As the market penetration increases, these power sources will need to provide grid services, such as dispatchability, in addition to providing energy. One way to reduce variability, provide higher quality power to the grid, and address local grid stability issues is through colocating wind and solar power plants. In addition to operating reliably during normal operating conditions, in scenarios with high penetrations of renewable generation, it is important that these hybrid plants can withstand production disruptions and continue to supply power despite prolonged resource reduction, extreme weather events, or other disruptions. In this paper, we present a methodology to optimize a wind–solar-battery hybrid power plant down to the component level that is resilient against production disruptions and that can continually produce some minimum required power. We introduce the models and assumptions we used to simulate a hybrid power plant as well as the design variable parameterization and specific methods we used to optimize the plant. We demonstrate the performance of our method by comparing a plant optimized for different objectives, generation outage durations, minimum power requirements, and power purchase agreements. Although the plant design is sensitive to model parameters and various other assumptions, our results demonstrate some of the optimal designs that occur in different scenarios and what one should expect when designing a hybrid wind–solar-storage power plant.

Multi-Period AC/DC Transmission Expansion Planning Including Shunt Compensation

Due to the increasing penetration of large-scale renewable energy generation at transmission level, hybrid AC/DC transmission expansion is becoming more relevant by the day, especially if the considered renewable generation is far away from existing AC grid infrastructure. This paper presents a multi-period hybrid AC/DC network expansion planning model that incorporates node voltages, reactive power and network losses. Since the operation of a high voltage DC link is influenced considerably by the converter stations, converter transformer, filter, and phase reactor are modeled in each converter station. Since the AC power flow equations render a non-convex problem whose solution algorithms do not always guarantee convergence or optimality, a second-order conic relaxation is utilized. The resulting model is a mixed-integer convex problem with a convergence guarantee that embodies a better approximation of system operation than its DC linear counterpart. Three case studies are considered to illustrate the proposed model.

Co-optimization of Energy and Reserve With Incentives to Wind Generation

Transitioning from fossil fuel dominated power systems to high penetrations of intermittent renewable generation is affecting classical electricity market designs. Here, a method is proposed to model and assess the absence of co-optimization of energy and reserve that prevails in the European system. Co-optimization is formulated through an optimization problem (COM), and its absence as an equilibrium problem (EQM) built on Karush-Kuhn-Tucker conditions of agents’ optimization and market clearing equations. EQM cannot be reformulated as a single optimization problem. Market distortions are identified by comparing the complementarity conditions of both models. These are then discussed on system with Feed in Premium to wind generation. Parameters in the models allow to represent different market configurations regarding: available wind generation, Feed in Premium to wind, generators’ risk aversion, and required reserve from wind generation.

Data-Driven Power Flow Calculation Method: A Lifting Dimension Linear Regression Approach

The high-precision parameters in distribution networks are difficult to obtain, which brings difficulties to the model-based methods and analysis. With the widespread deployment of high-precision measurement units, data-driven methods have greater advantages in practice. In addition, with massive integration of distributed renewable generation and fast electric vehicle chargers, the fluctuations of net load increase significantly. The data-driven power flow calculation method based on the linear model becomes difficult to obtain accurate results for the low nonlinear adaptability. To improve the data-driven power flow calculation accuracy under high penetration of renewable distribution generation, this paper proposed an approach with high adaptability to the nonlinearity of power flow. Based on the thought of Koopman operator theory, the nonlinear relationship in power flow calculation is converted into a linear mapping in a higher dimension state space, which can significantly improve the calculation accuracy. Case studies on different IEEE cases have demonstrated that the proposed method can realize higher accuracy in power flow calculation with large-scale power fluctuations, compared to the existing data-driven method, in both mesh and radial networks. Finally, measurement data of a practical 10kV distribution network has been further used to verify the effectiveness of the proposed method in practical applications.

Impedance Modeling and Stability Analysis of Three-Phase Four-Wire Inverter with Grid-Connected Operation

With the continuous penetration and development of renewable energy power generation, distributed grids and microgrids are becoming increasingly important in power systems. In the distribution networks and microgrids, the grid impedance is comparatively large and cannot be ignored. Usually, the parallel compensation is used to improve the grid quality. In these three-phase four-wire power systems, analyzing the impedance characteristics of the grid-connected inverter is vital to carry out the small-signal stability analysis. Thus, it is vital to consider the influence of the zero-sequence component in addition to the positive-sequence component and the negative-sequence component when it comes to analyzing system stability. In this paper, the impedances of three-phase four-wire split capacitor inverter and three-phase four-leg inverter are established. Based on the achieved impedance, the similarities and differences between the impedances of three-phase four-wire split capacitor inverter and impedance of three-phase four-leg inverter are studied. The main difference is reflected in zero-sequence impedance. Additionally, the zero-sequence impedance characteristics and the dominating factors deciding the zero-sequence impedance are analyzed. Then, the stability of the system considering the grid impedance and impedance of three-phase four-wire inverter is investigated by separately considering the stability of the positive–negative-sequence component and the stability of the zero-sequence component. Several cases of small-signal instability caused by the positive–negative-sequence component or zero-sequence component are revealed. The experimental results validate the theoretical analysis.

Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China

The development of renewable energy (RE) is a critical path to achieve global climate goals and energy conversion. The understanding of Demand-side response (DR) is crucial for the stability and efficiency of renewable energy system (RES). The DR strategies are performed by coordinating various energy sources and electricity demand optimally in the operation of high penetration of renewable generations across different seasons from 2015 to 2050 using Qinghai, China as an example. The results show the reduced peak demand by DR is various in different seasons, and the shifted peak demand will be 56.8 GWh-596.5 GWh in 2050. In general, DR could cause a significant reduction of the total costs by avoiding unnecessary installed capacity from ￥2.19 billion to ￥28.62 billion in 2050. In the short-term, the structure of high-proportion RES cannot rapidly adjust to a new form. However, in the long-term, hydropower will have a large share in RES due to the ability of improving the synergistic stability of the high-proportion RES. In addition, the adoption of DR demonstrates a great potential on reducing PV curtailment and wind curtailment.

Modeling the Energy Cooperation between Regionally Interconnected Aggregators using Bilateral Agreements

Traditional centralized power dispatching systems have inherent limitations in dealing with the increasing penetration of variable renewable energy generation in distribution networks. This study presents a flexible energy exchange mechanism for regionally interconnected aggregators in regards to VRE penetration. Direct energy exchange between neighboring aggregators is proposed as a promising method of maximizing social welfare (i.e. maximization of end-users benefits and minimization of energy costs). The main idea of the proposed mechanism is to develop a parallel energy exchange cooperation between physically connected aggregators ensuring operational efficiency of the power systems at a local level. Given that neighboring aggregators may have differences in their energy generation and usage patterns these differences can be utilized to bridge the mismatch of each other’s supply shortage. An operational scenario of regionally interconnected aggregators is presented and investigated. The initial simulation results have illustrated the effectiveness and reliability of the proposed model and method.

Online Ensemble Approach for Probabilistic Wind Power Forecasting

Probabilistic wind power forecasting is an important input in the decision-making process in future electric power grids with large penetrations of renewable generation. Traditional probabilistic wind power forecasting models are trained offline and are then used to make predictions online. However, this strategy cannot make full use of the most recent information during the prediction process. In addition, ensemble learning is recognized as an effective approach for further improving forecasting performance by combining multiple forecasting models. This paper studies an online ensemble approach for probabilistic wind power forecasting by taking full advantage of the most recent information and leveraging the strengths of multiple forecasting models. The online ensemble approach is first formulated as an online convex optimization problem. On this basis, a quantile passive-aggressive regression model is proposed to solve the online convex optimization problem. Case studies and comparisons with other online learning methods are conducted on an open wind power data set from Belgium. Results show that the proposed method outperforms competing methods in terms of pinball loss and Winkler score with high reliability.

Robust transmission expansion planning using pair-based convex hull uncertainty sets under high penetration of renewable energy generation

Robust optimization is a practical and effective mathematical framework for coping with uncertainty in the transmission expansion planning (TEP) process, while computing the full convex hull is an outstanding data-driven means of searching for robust boundaries in the uncertainty sets employed in robust TEP processes. However, computing the full convex hull becomes intractable as the number of uncertain factors increases. This study addresses this issue by proposing a two-stage, four-level robust TEP model with uncertainty sets constructed using pair-based convex hulls. Employing a pair-based convex hull enables high-dimensional uncertainty to be characterized by constructing multiple low-dimensional uncertainty sets, and thereby decreases the computational burden associated with solving the robust TEP model while reducing the conservativeness of planning solutions. The model is then solved by means of a parallel column and constraint generation method. The proposed model is demonstrated to characterize the high-dimensional uncertainty efficiently and provide TEP solutions with relatively low conservativeness and high robustness based on numerical simulations of Garver’s 6-bus and IEEE 118-bus test systems.

A new power system active rescheduling method considering the dispatchable plug-in electric vehicles and intermittent renewable energies

The significant penetration of renewable power generations (RGs) and the large-scale use of plug-in electric vehicles (PEVs) have brought tangible impacts in tackling the climate change challenge the mankind has been facing due to substantive green-house gas and pollutant emissions from fossil-fuel based thermal power generation plants. However, the uncertainty of RGs has also exerted significant challenges to the grid operation and control. Therefore, dynamic power system scheduling to accommodate the intermittent RGs and mass roll-out of PEVs has become extremely important. In this paper, a novel power system rescheduling strategy is proposed to tackle this problem. Considering the uncertainty of the wind energy, a set of indices according to different wind power application scenarios is proposed to initiate a rescheduling scheme for power generations. In addition, a social learning particle swarm optimization algorithm based on real-value and binary parallel is proposed to schedule the output of generator units and the charging and discharging of the PEV. The effectiveness of the proposed active rescheduling framework and solving algorithm has been verified by extensive experiments considering different number of generating units and scenarios, achieving up to over 5.3% cost reduction. The experimental results have also shown that through expropriate management of the charging and discharging of PEVs would be significantly alleviate the negative impact on the grid stability caused by the intermittent wind power generations.

Transmission System Electromechanical Stability Analysis with High Penetration of Renewable Generation and Battery Energy Storage System Application

Despite the benefits of wind and solar photovoltaic generation, its stochastic characteristic imposes uncertainties on the electric power system’s transient stability. The dynamics considering large synchronous generators has been studied for many decades, and its behavior is well known. On the other hand, the penetration of renewable sources has reached records, showing that it is still vital to study their impact. The present work proposes computer modeling and simulations for the dynamic analysis of electromechanical stability in a transmission system with significant renewable generation. In general, the literature does not propose solutions to the electromechanical stability analysis, proving that there are gaps to be filled. Therefore, the main work contribution consists of designing and coupling a battery energy storage system to a solar plant to smooth power variations. A significant innovation is the proposition of different scenarios that replicate disturbance situations, where the analyses were carried out using the Brazilian grid code. It was possible to evaluate the robustness of the proposed system and the efficiency of the storage system in mitigating the impacts of renewable generation. Thus, it is possible to achieve high levels of renewable penetration if extensive and rigorous studies are carried out.

Primary frequency regulation scheme applicable to LCC – VSC series hybrid HVDC considering AC voltage stability at receiving end

The penetration of high proportion renewable energy generation in the load center reduces the inertia of the power system and causes frequency stability problems. Series hybrid HVDC (e.g., BaiHeTan-JiangSu) with landing point at load center should play an important role in primary frequency regulation. Thus, this paper proposes a control scheme that coordinates line-commutated converter (LCC) and voltage-source converter (VSC) operation of the series hybrid HVDC (SHHVDC) and couples inertia emulation control with droop control (CIEDC). The CIEDC absorbs or releases the energy stored in the augmented capacitor of VSC for inertia emulation through regulating DC voltage. Then the DC voltage of LCC is coupled with the DC voltage of VSC through the voltage distribution coefficient. Meanwhile, the DC voltage of the inverter side is used to transmit the frequency information to the rectifier side to change the DC current order value without communication-based. Next, The equivalent DC input resistance based on communication-free is introduced to obtain the reactive power variation caused by LCC, which is transmitted to the reactive power control link in VSC to suppress the AC side converter bus voltage fluctuation. Finally, The CIEDC control scheme is verified by case studies in the event of slight AC fault and step load variation compared with the Fixed-Inertia Emulation Control Scheme (FIEC) and conventional droop control (CDC) in AC bus voltage stability, frequency deviation, rate of change of frequency (RoCoF).

High Frequency Resonance Suppression Strategy of Three-Phase Four-Wire Split Capacitor Inverter Connected to Parallel Compensation Grid

With the continuous penetration and development of renewable energy power generation, the distributed grid and the microgrid are becoming increasingly important in modern power systems. In distribution networks and the microgrid, the grid impedance is comparatively large and cannot be ignored. Usually, the parallel compensation is used to improve the grid quality. In the grid with parallel compensation, the large phase angle difference between the impedance of the grid-connected inverter and the impedance of the grid at amplitude intersection will result in high frequency resonance (HFR). Because the inverter shows filter characteristics due to limited bandwidth of the controller, the parallel compensation grid, respectively, performs as the capacitance characteristic and inductance characteristic in different high frequency range. Compared with the three-phase, three-wire system, an additional zero-sequence path exists in the three-phase four-wire split capacitor inverter (TFSCI) system, so that the existing high frequency resonance suppression methods will be not effective. Since the zero-sequence component is neglected, HFR will also occur, in addition to the positive-sequence component and the negative-sequence component. Therefore, in order to suppress the high frequency resonance caused by positive-sequence, negative-sequence and zero-sequence components, an impedance reshaping strategy based on current feedback is proposed in this paper. This proposed method can reshape the amplitude and phase of the inverter impedance in a high frequency range without affecting the performance of the fundamental frequency control and ensure that the inverter contains a sufficient phase margin. Additionally, the proposed method can reshape the impedance of TFSCI within a wide frequency range, which makes it able to cope with the challenge of the parallel compensation degree change. Theoretical analysis and experiments verify the availability of the proposed control strategy.

Solid-State Transformer-Based DC Power Distribution Network for Shipboard Applications

Due to simplicity, efficiency, and the ability to accommodate energy storage devices, DC distribution networks have been seen as an optimal alternative to AC distribution networks, especially aboard future electric ships. The emerging distribution DC system entails new control and management techniques. Therefore, an integrated DC power distribution network aboard an electric ship is selected as the case study in this paper. To meet the requirements of such a large-scale mobile power system, a multiport solid-state transformer (SST) based on silicon carbide (SiC) switches/MOSFETs is proposed. Thus, the system embodiment can significantly be reduced. Moreover, at the DC distribution level, a high penetration of renewable generation with energy storage is allowed and a six-phase asymmetrical induction machine (IM) can directly be integrated. Simulations have been conducted based on a 2 MW shipboard distribution network. The effects of the propulsion system dynamics on the SST are highlighted as well. Finally, a 2 kW lab-scale prototype has been implemented to validate the theoretical findings.