Penetration Of Generation Research Articles

Bayesian Belief Networks: Redefining wholesale electricity price modelling in high penetration non-firm renewable generation power systems

The transition of electricity generation from firm to non-firm renewable generation is driving changes in wholesale electricity price dynamics that are increasingly challenging to model due to the stochastic nature of wind and solar as the primary energy source. Robust pricing models are essential for optimising financial performance in liberalised electricity markets. The novelty of this paper is the application of Bayesian Belief Networks in the modelling of wholesale electricity price formation, specifically in power systems with a high penetration of non-firm renewable generation. This paper links the mathematical Bayesian representation to established statistical and computational approaches using a functional supply-side wholesale electricity market pricing model. In addition, the paper introduces a novel validation method employing volatility analysis to assess the case study's performance.The case study revealed that when the proportion of stochastic generation was ≥40 % penetration in a trading interval, the Bayesian Belief Network model's accuracy considerably outperformed the benchmark model with a Mean Absolute Scale Error of 1.43 compared to 1.63 in those intervals. Finally, the volatility analysis results challenged the prevailing notion of a positive causal relationship between non-firm renewable penetration and price volatility.

Two-stage optimization strategy for the active distribution network considering source-load uncertainty

This study aims to advance the development of the active distribution network (ADN) by optimizing resource allocation across different stages to enhance overall system performance and economic benefits. First, an ADN optimization model is constructed based on a two-stage robust optimization approach. The first stage focuses on determining optimal decision variables within the uncertainty set, while the second stage adjusts control variables based on the initial stage decisions. This model effectively addresses source-load uncertainties while preserving the flexibility and adaptability of decision-making solutions. Additionally, this study explores uncertainty models that incorporate correlation factors. The IEEE33-node model is employed to validate the effectiveness and superiority of the proposed optimization strategy through numerical simulations. Simulation results demonstrate that Model 3 comprehensively accounts for photovoltaic and wind turbine generator planning by optimizing their capacity configurations, leading to a 23% increase in distributed generation (DG) penetration. During high-load periods (e.g., 13:00 and 16:00), DG output reaches 47% and 50% of the demand load, underscoring the critical role of DG in supporting the power grid during peak hours. Overall, the proposed two-stage optimization strategy considers source-load uncertainties, significantly reducing economic costs, enhancing DG output, and improving overall system performance. In scenarios with correlated uncertainties, the optimized results exhibit greater accuracy and reliability, providing robust support for the planning and operation of practical distribution networks.

Energy management strategy and operation strategy of hybrid energy storage system to improve AGC performance of thermal power units

With the continuous increase of the renewable energy power generation penetration, the intermittency and fluctuation of renewable energy power generation make the traditional thermal power units (TPU) which play the main role of regulation need to undertake more frequent and more severe regulation tasks. In order to improve the automatic generation control (AGC) command response capability of TPU, an operation strategy of hybrid energy storage system (HESS) is proposed in this paper. While assisting TPU to complete the regulation tasks, it gives full play to the advantages of power-type and energy-type energy storage. Moreover, an energy management strategy of energy storage array (ESA) is proposed to improve the overall operation efficiency of ESA while making the state of charge (SOC) of all energy storage subunits consistent. Finally, the effectiveness of the proposed strategy is verified by simulation experiments. The results show that after using HESS to assist TPU operation, the comprehensive regulation performance index of TPU increased from 4.0198 to 7.8112, which significantly improved the operational flexibility of TPU. Meanwhile, the strategy proposed in this paper makes different types of energy storage systems in HESS operate in a relatively healthy SOC range, and the SOC of the flywheel energy storage system (FESS) reaches the limitation value decrease from 6 times to once, ensuring the overall charge and discharge capacity of HESS.

Reactive compensation in distribution systems and volt/var control analysis: Mutual performance of inverters and curve slope effects

The high penetration of photovoltaic distributed generation is causing overvoltage in distribution networks due to the reverse active power flow. Proposals to mitigate this problem through Volt/Var control (VVC) by photovoltaic inverters are being discussed. However, the configuration of the appropriate Volt/Var curve depends on the topological factors of each system. In this context, this paper presents a practical methodology for calculating the reactive compensation of the local VVC. In addition, the impact of the slope of the curve on power quality and the problems of mutual actuation of inverters in the VVC are analyzed. The studies were conducted in quasistatic time series (QSTS) mode on the IEEE 33 bus system. The slope of the curve affects grid losses and the substation power factor, and can mitigate the negative effects of the mutual actuation of the inverters in the VVC. Based on this, guidelines were established to adapt the definition of the slope to the characteristics of each system.

Is the clean energy transition making fixed-rate electricity tariffs regressive?

Wholesale electricity prices can rapidly change in real-time, yet households usually face fixed-price electricity tariffs. In markets with large amounts of solar electricity generation, households that predominantly import energy in the daytime when wholesale prices are low implicitly cross-subsidize households with energy use that is more weighted to the higher-priced evening. We map substation data on electricity use to demographic data, to identify the household characteristics associated with this cross-subsidization in a high-solar setting. We find that households in areas with low house prices and high levels of renters are the net funders of this implicit subsidy. These households currently have the lowest average energy cost for retailers to service, and could be the greatest immediate beneficiaries if real-time retail tariffs are made available, before accounting for price-responsiveness. Finally, we present evidence that cross-subsidy magnitudes have grown significantly in recent years, coincident with rapid solar generator penetration.

A unified approach to modeling and stability equivalence analysis for grid-forming and grid-following converters

With the increasing penetration of renewable energy generation, the large-scale integration of grid-connected converters, serving as interfaces, has led to the characteristics of a weak grid with low strength and low inertia, resulting in insufficient stability of existing grid-following (GFL) converters. Grid-forming (GFM) converters, by emulating the characteristics of traditional synchronous machines, can operate stably in weak grids, but their introduction creates a complex operational state with mixed modes, presenting unprecedented challenges to the system. To address this, this paper first analyzes the structure and GFM/GFL control strategies of grid-connected converters; based on this, a comprehensive model framework for GFM/GFL converters is established, and the control of the converters is divided into three parts: LCL with the grid, output control, and power control, each modeled with a small-signal approach; using the established small-signal models, the stability of GFM/GFL converters under different grid short circuit ratios (SCR) is analyzed. Finally, a 20 kW test platform was constructed, and the correctness of the modeling and analysis was jointly verified using simulation frequency sweep methods and experimental time-domain stability analysis techniques.

Study of rooftop PV hosting capacity in 20 kV systems in facing distributed generation penetration

---With the increasing request for integrating rooftop photovoltaic (PV) systems into the distribution grid, it is crucial to prevent the potential negative impacts of high PV penetration. Considering the uncertainty and variability characteristics of high rooftop PV penetration, a stochastic approach for determining PV hosting capacity (HC)—the maximum capacity of a PV system to receive electricity from the power distribution network before the network reaches an operating limit violation—is necessary. Therefore, this study proposes calculating PV hosting capacity using the Monte Carlo simulation. Unlike previous works, this paper uses real feeders as case studies, representing both urban and rural areas. The feeder representing an urban area with many industrial and business customers has a higher hosting capacity, 31 % of full load, compared to the feeder representing rural areas, which has 18 % of full load. By using actual feeders that represent urban and rural areas, more representative results for specific problems can be achieved without assuming urban and rural feeders have the same specific problems.

Optimal retail contracts with contractible uncertainty

Around the world policymakers and regulators are struggling with the question of how to design retail electricity tariffs in the face of increasing penetration of local generation (e.g., solar PV), smart appliances, local storage, and electric vehicles. There is a widespread recognition that retail tariffs should vary dynamically across time and space, reflecting the changing conditions (congestion and losses) on the underlying networks. But, at the same time, there is recognition that such tariffs potentially expose retail customers to substantial risk. Risk averse retail customers desire protection against price spikes and volatile wholesale spot prices. This paper seeks to derive the optimal retail contract in the special case in which the uncertainty in the market is contractible (in the sense defined here). We show that the optimal retail contract exposes the prosumer to the wholesale spot price at the margin, but also perfectly insulates the customer from risk, achieving the first-best outcome. We show how the hedge component of this retail contract can be constructed from standard-form hedge contracts. We draw out several lessons for policymakers.

Hydropower Enhancing the Future of Variable Renewable Energy Integration: A Regional Analysis of Capacity Availability in Brazil

As the share of variable renewables in the power system generation mix increases, meeting capacity requirements becomes challenging. In this context, hydropower reservoirs can play a vital role in integrating renewable energy due to their storage potential, contributing to meeting power supply criteria. However, given that reservoirs serve multiple purposes, various constraints can limit their capacity potential. This article introduces an analytical methodology that is designed to evaluate the maximum available power of hydro plants in critical scenarios. By applying concepts related to hydropower production calculations for the peak power demand and metrics evaluating the compliance with supply criteria, this study distinguishes itself from region-specific investigations. It conducts a generalized analysis of power availability across all regions of Brazil, with a focus on identifying the reasons for the most significant power losses and their specific locations. The results of this analysis demonstrate the feasibility of enhancing the available power of reservoirs, effectively addressing demand fluctuations, and sustainably improving energy security. This is particularly crucial in countries that are heavily reliant on renewables, including hydropower, for a huge portion of their electricity. The findings underscore the feasibility of increasing the penetration of variable renewable generation by optimizing the operation of existing hydropower plants. This optimization not only enhances energy security but also contributes to a more resilient and sustainable future, benefiting policy makers, energy planners, and stakeholders in the field of hydropower with reservoirs.

The effect of PV generation's hourly variations on Israel's solar investment

Limited by sunniness and conversion efficiency, one installed MW of photovoltaic (PV) capacity can only produce ωt MWh of electricity in daytime hour t, where ωt = positive fraction that we call PV's hourly effective capacity (HEC). Based on a sample of commercially operating PV plants in Israel, HEC rises throughout the 08:00–11:00 period, peaks in the 11:00–14:00 period and then declines in the 14:00–18:00 period. Further, HEC values in spring and summer exceed those in autumn and winter, thus motivating our research question: do HEC variations by hour and season adversely affect the plans for and assessment of PV investment in Israel? An affirmative answer would cause concerns regarding Israel's announced policy of relying on increasing market penetration of PV generation transitionally supported by merchant natural-gas-fired generation (NG) to achieve a low-carbon electricity future. Hence, we propose a two-stage model of Israel's forthcoming Cournot wholesale electricity market with independent power producers (IPPs) operating PV and NG power plants. By comparing the model's solutions under alternative HEC scenarios, we find that the level of detail in modelling the HEC variations by hour and season does not materially affect the optimal PV and NG investments, thus lending support to the use of relatively simple models with only two daily non-seasonal HEC values to assess Israel's announced policy of deep decarbonization. Our methodology is general and real-world relevant because it can be readily adapted for applications in other regions with ample sunshine and wholesale electricity market competition (e.g., California, Texas and Australia).

تأثير مولدات التوزيع (DG) على شبكة التوزيع الكهربائية الزهراء-ليبيا 30 كيلو فولت

Libyan electric distribution networks are suffering many problems of voltage limits violation, high system losses and low system performance. In this paper, a load flow study will be performed for a large power distribution of Alzahra area in Libya that include Alzahra power station. Considering distribution generation (DG) penetration method instead of conventional replanning methods, such as the expanding and adding methods that needs efforts and time. Alzahra 30KV electric system is taken as the case study including Alzahra power plant, different operation cases are considered includes the operation of the considering DG penetration during peak loads. The availability of high-performance software's such as NIPLAN helps in redesigning and replanning of electric power system for enhancing performance and solving system problems. The loss in the general phase was 8MW, and after increasing the loads by 8%, the loss ratio increased to 10MW. When adding the distribution generation in the right place, we note that the loss has been saved to approximately 4.5MW. KEYWORDS: DG, Penetration, Load flow, NIPLAN software, Voltage drop, Power system planning.

Analysis of protection blinding in active distribution grids

AbstractProtection blinding is a challenging issue in renewables‐penetrated distribution grids and refers to a situation where a circuit breaker may not trip due to fault current contribution from distributed generation. This research addresses how the distributed generation location and capacity impact the operation of the circuit breaker in terms of the response time of the circuit breakers. The relative electrical distances of the faults and distributed generation to the circuit breakers are considered. The impact of distributed generation capacity considering the fault location is characterized using a new index called the heterogeneity index. The electrical distance between distributed generations and circuit breakers and the electrical distance between fault and circuit breaker is considered by a second new index called the electrical distance ratio. Data analysis on simulation results shows that these indices capture the phenomena of protection blinding caused by distributed generation. Results show that a higher distributed generation penetration and faults that are electrically further away from a circuit breaker show severe cases of protection blinding captured by the indices. Furthermore, it is demonstrated how these indices can identify the worst impacted locations in the distribution grid. A key result is that protection blinding does not necessarily occur solely due to the presence of distributed generation between a circuit breaker and a fault, but is dependent on factors such as distributed generation location in the distribution grid, fault level, fault level distribution across the generation units and fault location.

Energy Storage Improves Power Plant Flexibility and Economic Performance

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation, such as wind and solar, is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and a lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that the flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on the flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that energy storage systems integrated with a thermal power plant improve plant flexibility and participation in the energy and ancillary services markets, which improves plant financial performance. The study was funded by the U.S. Department Office of Fossil Energy FE-1 under award number DE-FE0031903.

Optimal sizing and placement of battery energy storage system for maximum variable renewable energy penetration considering demand response flexibility: A case in Lombok power system, Indonesia

Indonesia is a tropical climate country with considerable renewable electrical energy source prospects, including photovoltaic (PV) and wind energies. Nevertheless, several variable renewable energy sources (VREs) have exhibited uncertain attributes and substantial reliance on natural conditions, leading to unstable load-related power supply risks. Hence, integrating battery energy storage systems (BESSs) with VRE generators is a dependable approach to bolster renewable energy generator applications on a large-scale grid while providing load demand flexibility. This study determined adequate sizing and placement of the BESS to achieve maximum VRE generator penetration while considering the demand response flexibility. Key indicators, including technical minimum load and system ramp capacity, were identified to achieve maximum penetration of thermal generators. This study also combined a unit commitment procedure with direct current optimal power flow (DC-OPF) as a novel approach to determine the maximum VRE penetration level. An optimization problem model concerning mixed integer linear programming (MILP) was subsequently employed in this study using the CPLEX solver in the general algebraic modeling system (GAMS). The study is based on the IEEE RTS-24 system modified and a real-life case study of the Lombok energy system in Indonesia. Results from the simulated Lombok power system highlighted that optimal sizing and placement of the BESS could lower system costs by 37.66%, 33.63%, and 22.26% compared to the current system conditions during the weekday, weekend, and the lowest day scenarios, respectively. The VRE penetrations of the generators were also higher than the current system conditions by 83%, 51%, and 39% during the weekday, weekend, and the lowest day scenarios, respectively.

A Novel Approach for Dynamic Analysis of Wind-Integrated Multi-Machine Power Systems

Indeed, the rapid expansion of Renewable Energy Sources (RES) in recent years has brought about numerous benefits, including reduced carbon emissions, increased energy independence, and the creation of new economic opportunities. However, integrating these variable and intermittent sources into existing power systems poses several challenges for power system management. Faults in electrical networks are among the key factors and sources of network disturbances. Control and automation strategies are among the key fault clearing techniques responsible for the safe operation of the system. In recent years, the increasing penetration of wind energy in multi-machine power systems has posed unique challenges to power grid stability and reliability. Accurate assessment methodologies are required to ensure the effective integration of wind energy sources while maintaining grid stability. Several researchers have revealed various constraints of control and automation strategies such as a slow dynamic response, the inability to switch the network on and off remotely, a high fault clearing time and loss minimization. It's important to note that the impact of wind energy on system inertia is a complex and dynamic aspect of power system operation. Ongoing research and technological advancements aim to improve the integration of wind and other renewable energy sources while ensuring grid stability and reliability. As the energy transition continues, addressing these technical challenges is crucial for building a sustainable and resilient power system. In this paper, the influence of doubly-fed induction generator (DFIG) penetration is analyzed to examine the transient stability of power system networks. The concept of a Coupling Strength Index (CSI) derived from Network Structural Characteristics Theory sounds intriguing, especially in the context of identifying critical elements susceptible to the impact of a three-phase fault in a network. The investigation involves studying the transient stability of a power system under different conditions, specifically with and without doubly-fed induction generators (DFIGs) connected to a weak bus. Additionally, a three-phase fault is applied at the middle of the identified weakest line for both the IEEE 9 and 39 bus systems. The investigation of generator speed, rotor angle, and electric power during transient stability analysis provides a holistic view of how a power system responds to disturbances. This information is crucial for ensuring the reliability and stability of the system, especially when studying the integration of renewable energy sources and addressing potential challenges associated with faults and weak buses. This paper presents a pioneering non-iterative framework for dynamically assessing wind energy dominated multi-machine power systems. The proposed framework aims to address the shortcomings of traditional iterative methods, providing a more efficient and reliable approach to power system analysis.

Data-driven distributionally robust day-ahead dispatch for active distribution networks based on improved conditional generative adversarial network

With the increasing penetration of renewable energy generation (REG), strong uncertainty poses a significant challenge to the rationality of day-ahead dispatch plans in distribution systems. We propose a data-driven, distributionally robust day-ahead dispatch method for active distribution networks (ADNs) based on an improved conditional generative adversarial network (CGAN). First, an improved CWGAN-GP model is constructed based on three-dimensional convolution (Conv3D) and the Wasserstein distance to obtain the day-ahead REG scenarios, considering the correlation features of photovoltaic (PV) and wind turbines (WTs), which reduces the conservatism of scenario generation. Accordingly, the Gaussian mixture model (GMM) clustering method based on moment information was used to construct an ambiguity set. Moreover, a two-stage distributionally robust day-ahead dispatch model for an ADN is established, which realizes the fusion of the data-driven method and distributionally robust optimization (DRO) mechanism model. Finally, the validity of the data-driven DRO (DDRO) method is verified through a case analysis.

Interactive demand response and dynamic thermal line rating for minimizing the wind power spillage and carbon emissions

Spilling has already occurred as a result of rising the penetration of intermittent renewable generation, and it is anticipated that the level of renewable energy curtailment will continue to soar. This leads to an increase in operating costs, CO2 emissions, and not good utilization of renewable energy resources. A bi-level multi-objective optimization model is proposed in this paper to reduce wind power spillage (WPS) based on demand response (DR) and dynamic thermal line rating (DTLR). In the upper level, multiple objectives will be satisfied based on the optimal allocation and time of DR programs considering DTLR obtained in the lower level. The minimization of WPS, load shedding, power losses, and CO2 emissions are the objectives of this level. While the lower-level aims to maximize social welfare under different scenarios and overall system constraints. Under the uncertainty of the wind power and load demand, a collection of lower-level problems that represent the market clearing conditions is used to constrain the upper-level. The effectiveness of the proposed algorithm is examined on a modified two-area IEEE 24-bus test system. Results depict that the suggested bi-level model enables considerable reductions in the WPS by up to 32.7 %. Also, there is an enhancement in load shedding, power losses, and CO2 emissions by 28.93 %, 23.07 %, and 13.9 % respectively. Finally, the social welfare increased by up to 36.6 %.

Dynamic Patterns in the Small-Signal Behavior of Power Systems with Wind Power Generation

This paper investigates the dynamic patterns in the small-signal behavior of power systems with wind power generation. The interactions between synchronous generators and wind generators are investigated. In addition, the impact of increased wind generation penetration on the damping and frequency of the synchronous generator’s electromechanical oscillations is addressed. Wind generators of three different technologies are considered throughout this study. Very detailed dynamic models of wind generators are used and detailed.

Relay protection sensitivity integrated optimal placement and capacity of inverter interfaced distributed generators in distribution networks

The relay protection sensitivity is one of the determined factors in the power system, however, it is often overlooked in current distribution network (DN) planning. The relay protection sensitivity can be decreased to below the minimum values, failing to meet the requirements for electrical installations. To address this challenge, a new optimization model integrated with the relay protection sensitivity to maximize the inverter interfaced distributed generator (IIDG) penetration level while minimizing IIDG investment was proposed in this paper. The IIDG effect on the relay protection sensitivity was analysed and the relay protection sensitivity re-evaluation method was developed. The relay protection sensitivity evaluation was integrated into the proposed model and the particle swarm optimization (PSO) algorithm was developed to solve the nonlinear issue. The proposed optimization method was tested on different cases, and results confirmed the effectiveness of the method. Furthermore, the relay sensitivity profiles obtained through the proposed method and the optimization without considering the relay sensitivity limits were compared. The proposed method improves the average and minimum sensitivity factors by 28.77 % and 51.76 %, respectively, when the DTO protection functions as the backup for the protected line in the thirty-three-node system. When DTO acts as the backup for the adjacent line, the average and minimum values increase by 29.91 % and 50.95 %, respectively. Comparative analysis confirms the efficacy of the proposed method. The new method extends the power system panning approaches and can be integrated into the DN planning tools to support the low-carbon initiatives.

Coordination of aluminium crusher and battery energy storage system to provide multistage power system services

AbstractAncillary service provision and peak shaving (PS) play essential roles in the current day‐to‐day power system operation, which is challenged by the increasing renewable generation penetration. Providing these critical services using classical approaches such as peak load generators has been limited due to high operational costs and environmental impacts. The use of battery energy storage systems (BESS) is another popular method that is limited by high initial investment costs and high degradation rates. In this work, a novel approach to utilize industrial loads and BESS to provide multiple power system services in different stages is proposed. Industrial loads such as aluminium crushers are known for their intensive electricity consumption. Nevertheless, when applied in frequency regulation (FR), they perform poorly due to their discrete nature in operation. This drawback and the aforementioned BESS shortcomings are addressed by combining on‐site BESS with plant machinery to provide FR services and recover BESS related costs. Later, depending on the optimal capacity distribution, BESS usage is extended into the energy arbitrage market to provide PS services. This approach resulted in higher earnings for participating customers and network operators, as well as in less emissions, and minimal BESS degradations. An Australian case study of the South West Interconnected System, along with Worsley Alumina refinery data of Western Australia has been used to showcase the model performances.