Renewable Energy Penetration Level Research Articles

Integrated distribution system and urban district planning with high renewable penetrations

Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi‐energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building‐to‐grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions.This article is categorized under: Wind Power > Systems and Infrastructure Energy Policy and Planning > Systems and Infrastructure Energy Efficiency > Systems and Infrastructure

Adaptive state-observer for monitoring flexible nuclear reactors

Since nuclear power still fulfills nearly 11% of world electricity demand nowadays, the flexible operation of nuclear reactors can be positive to improve the penetration level of intermittent renewable energy (IRE) sources. Meanwhile, the operational flexibility of nuclear reactors results in the frequent variation of reactor process variables such as the neutron flux, fuel temperature and primary coolant pressure and temperature, which may fasten the degradation of equipment, and further leads to the necessity of developing performance monitoring methods for nuclear reactors in the context of fast and deep IRE penetration. Motivated by the importance of performance monitoring, an adaptive state observer (ASO) for nuclear reactors is newly proposed, which only needs the measurements of neutron flux and coolant temperature at reactor inlet and can provide globally asymptotic estimation for the normalized concentrations of delayed neutron precursors, 135Xe and 135I, the average temperatures of fuel elements and primary coolant as well as the total reactivity disturbance. The ASO is then applied for reconstructing the unmeasurable state variables and total reactivity disturbance of a nuclear heating reactor (NHR). Numerical simulation results verify the theoretical analysis, and show the satisfactory observation performance with its influence given by the ASO parameters. Furthermore, a hardware-in-loop (HIL) verification experiment is performed, and the corresponding results show that this newly-built ASO is not sensitive to the measurement noises, which leads to the feasibility of deploying the ASO on those digital control system platforms.

Investigation of Energy Storage Batteries in Stability Enforcement of Low Inertia Active Distribution Network

The inherent intermittency of renewable power generation poses one of the great challenges to the future smart grid. With incentives and subsidies, the penetration level of small-scale renewable energy into power grids is sharply increasing worldwide. Battery energy storage systems (BESS) are used to curtail the extra power during low demand times. These energy storage systems are capable of absorbing and delivering real power to the grid. The increased penetration level of inverter-based distributed generation (DG) reduces the inertia of the grid and thus affects the transient stability of the network. This paper discusses and investigates the impact of BESS on distribution networks’ stability with high penetration levels of inverter based DG. The obtained results show that proper charging and discharging schemes of the BESS can enhance the transient stability of the network. Fast switching between charging and discharging mode would be helpful during transient fault disturbance to keep the system in a balanced condition.

Power system inertia in an inverter-dominated network

Erosion of power system inertial energy due to high penetration levels of renewable energy (RE) sources in a power system is a current teething issue with most system operators everywhere. The main issue is displacement of synchronous generators with inverter-based based generators, as the latter do not provide any inertial energy to the power system. The power system thereby becomes vulnerable to large system events (like sudden loss of a big generator or load) and in an inverter-based system this could result in catastrophes such as total collapse of the whole power system due to rapid rate of change of frequency. This paper focuses on power system inertia as RE penetration levels increase and also explores possible mitigation measures such as demand response techniques.

Optimistic use of battery energy storage system to mitigate grid disturbances in the hybrid power system

Renewable energy (RE) is being continuously penetrated in to the utility grid and RE penetration level has become comparable to the conventional energy. For balancing of energy generation, solar and wind generators are being integrated to the utility grid at same location to form the hybrid power system. This has been achieved by the use of power electronic converters which are non-linear in nature. Further, variability of solar and wind energy generation also deteriorates quality of power in the hybrid grid. Any disturbance developed in the hybrid grid affects system parameters and power flow due to non-linearity of system and variability of RE generation. This has motivated the academicians and researchers to investigate efficient devices to minimize effects of disturbances on the performance of hybrid grid parameters in the presence of RE. A design of hybrid power system incorporating the wind energy, solar energy, loads, battery energy storage system (BESS) and conventional generator is proposed. This will help to minimize effects of grid disturbances on hybrid power system and improve the performance of utility grid with high RE penetration. Minimization of variability in power generation due to variations of wind speed and solar insolation will be achieved. This is achieved by application of battery energy storage system supported by distribution static compensator (DSTATCOM) controlled by the use of synchronous reference frame theory (SRFT). Test network consisting of five buses, conventional generator, loads, wind generator and solar photovoltaic (PV) generator is realized in MATLAB to establish effectiveness of proposed scheme.

Probabilistic Power Flow Analysis of Bulk Power System for Practical Grid Planning Application

The sizes of PV power plants have grown in such a way that their effects on the power system can no longer be neglected. In order to address these issues, grid operators are forced to expand grid connection points, and a power flow analysis considering uncertain renewable generation is required. Thus, a modified probabilistic power flow (PPF) analysis for practical grid planning is suggested in this paper. The regularity and randomness of PV power are modeled by a Monte Carlo-based probabilistic model combining both k-means clustering and the kernel density estimation method. The certain cluster group is selected so as to reflect the severe PV generation scenario, and the chi-square test to represent the $n$ th conservative network planning was suggested. In order to provide the power flow result more effectively, a mapping function of graphic representation based on a significant grid code violation is provided in an automatic PPF tool written by Python scripts. Following this procedure yields a reasonable network design for various renewable energy penetration levels.

Impact of Smart Inverters on Feeder Hosting Capacity of Distribution Networks

Penetration of renewable energy based distributed generators into power networks is limited. This is due to several reasons such as intermittency of the generation, low-inertia during disturbances and high variation of local voltage and frequency. Traditionally, distribution networks are designed for a finite voltage drop with distance from feeder connection. When PV panels are deployed at households, their impact on the local voltage profile becomes very substantial. Especially, when there is high solar radiation, generated power increases and the local voltage exceeds the permittable limits. Smart inverters are introduced to tackle this problem. Unlike other inverters, they can follow the local network measurements and provide auxiliary voltage and frequency support. With these features, smart inverters have the ability to push the renewable energy penetration level further. To investigate this phenomenon, custom smart inverter models are developed. Power flow calculation steps are modified to include smart inverter's active inputs. Then, feeder hosting capacity studies were run with conventional and smart inverters to investigate the improvement. Developed models, modified power flow algorithm and results of simulations are reported. Findings show renewable energy share can be increased in networks with smart inverter deployments only, without making substantial changes to rest of the network.

Techno-Economic Analysis of Intermittent Renewable Energy Penetration with the Proposed India-Sri Lanka HVDC Interconnection

This paper presents a techno-economic analysis to identify the level of intermittent renewable energy (RE) such as wind & solar penetration in to the Sri Lankan power system with the proposed India-Sri Lanka HVDC interconnection. This research adopts a methodology to identify the level of RE penetration with the HVDC link and compares with original power system planned with a pumped storage power plant. Future power plant additions based on least cost principles were derived using WASP software considering a staged development of the interconnection; 500MW in 2025 and 1000MW in 2028. This power plant schedule was input to long term dispatch simulation software SDDP and short term dispatch simulation software NCP to simulate the dispatch and obtain excess generation from renewable to calculate the RE penetration level. The economic analysis was carried out to identify the cost impact and it was observed that the interconnection is economical for the initial RE capacities. RE penetration can be increased with the interconnection at an additional cost to the system. Therefore, sensitivity analyse were carried out to identify at what variable cost would the interconnection bring economic benefits to the country.

The Role of Concentrating Solar Power Toward High Renewable Energy Penetrated Power Systems

Achieving high renewable energy penetrated power systems requires considerable operational flexibility to hedge the variability and uncertainty of variable renewable energy (VRE) generation. Compared with VRE sources, concentrating solar power (CSP) is an emerging controllable renewable generation technique that utilizes solar thermal power to generate electricity. The operational dispatchability of CSP would contribute to the power system transition toward high renewable penetration. In this paper, we explore how the generation portfolio will change toward high renewable energy penetrations, how much cost is involved, and what role CSP will play in realizing a high renewable energy penetrated power system. This study relies on a stochastic two-stage generation and transmission expansion planning model with CSP plants. The model captures the uncertainty and variability of renewable generation and the flexibility limits of thermal plants. With the target of achieving a renewable-dominated minimum-cost system with an expected renewable energy penetration level, the investments of both generation and transmission facilities are optimized. A case study on IEEE test systems with renewable technology cost data in 2050 is performed to analyze the value of CSP toward high renewable energy penetrated power systems.

Active distribution network with efficient utilisation of distributed generation ancillaryservices

This study introduces an active distribution network with high penetration of inverter-based distributed generations (IBDGs) to improve the steady state, dynamic and transient performance of the distribution network. The size and location of the IBDGs, capacitor bank, on-load tap changers position and voltage regulator set points have been optimised to minimise the system losses, improve voltage profile and maximise the dynamic reactive power reserve. In addition to that, the adaptive master/slave roles are deployed in planning the active distribution network to achieve the best utilisation of each device based on its capability and response time in steady state, dynamic and transient operation. Indeed, the optimisation algorithm allows the IBDGs to operate in an inductive mode of operation during steady state resulted in maximising the dynamic reactive power reserve. Consequently, the IBDGs react with large dynamic margin in response to grid fault leading to enhanced voltage recovery and improved transient response. A comprehensive system optimisation and transient analysis are carried out to demonstrate the performance of the distribution network for enhancing the voltage profile, increasing the penetration level of renewable energy distributed generation, IBDGs, and improving the transient recovery in response to severe grid fault.

Energy Flexibility through the Integrated Energy Supply System in Buildings: A Case Study in Sweden

The increasing penetration level of renewable energies requires more flexibility measures at the consumption side. Flexible energy prices have been placed by energy providers to promote flexibility measures from energy users. However, because of the current energy supply system in buildings, these flexible energy prices haven’t been fully taken advantage of. This study focuses on the integrated energy supply system in buildings. A Swedish office building is used as the case study. The integrated energy supply system is built by installing new components, including battery, heat pump and electrical heater, and hot water tank. Mixed Integer Linear Programming (MILP) problems are solved to determine the optimal component capacities and operation profiles. The results indicate that all the studied system configurations achieve lower net present cost (NPC) than the current system. It suggests that the integrated energy supply system can take advantage of the flexible energy prices and lower the overall energy cost in the building. Among the studied configurations, the combination of air source heat pump (ASHP) and electrical heater (EH) has the lowest investment cost. This combination also has the lowest NPC except in the scenario with low borehole cost.

Energy flexibility from the consumer: Integrating local electricity and heat supplies in a building

The increasing penetration level of renewable energy requires more flexibility measures to be implemented in future energy systems. Integrating an energy consumer’s local energy supplies connects multiple energy networks (i.e., the electrical grid, the district heating network, and gas network) in a decentralized way. Such integration enhances the flexibility of energy systems. In this work, a Swedish office building is investigated as a case study. Different components, including heat pump, electrical heater, battery and hot water storage tank are integrated into the electricity and heat supply system of the building. Special focus is placed on the flexibility that the studied building can provide to the electrical grid (i.e., the building modulates the electricity consumption in response to the grid operator’s requirements). The flexibility is described by two metrics including the flexibility hours and the flexibility energy. Optimization of the component capacities and the operation profiles is carried out by using Mixed Integer Linear Programming (MILP).The results show that the system fully relies on electricity for the heat demand when not considering the flexibility requirements of the electrical grid. This suggests that district heating is economically unfavorable compared with using electricity for the heat demand in the studied case. However, when flexibility requirements are added, the system turns to the district heating network for part of the heat demand. The system provides great flexibility to the electrical grid through such integration. The flexibility hours can be over 5200 h in a year, and the flexibility energy reaches more than 15.7 MWh (36% of the yearly electricity consumption). The yearly operation cost of the system slightly increases from 62,273 to 65,178 SEK when the flexibility hours increase from 304 to 5209 h. The results revealed that flexibility can be provided from the district heating network to the electrical grid via the building.

Economics of Renewable Energy Integration and Energy Storage via Low Load Diesel Application

One-quarter of the world’s population lives without access to electricity. Unfortunately, the generation technology most commonly employed to advance rural electrification, diesel generation, carries considerable commercial and ecological risks. One approach used to address both the cost and pollution of diesel generation is renewable energy (RE) integration. However, to successfully integrate RE, both the stochastic nature of the RE resource and the operating characteristics of diesel generation require careful consideration. Typically, diesel generation is configured to run heavily loaded, achieving peak efficiencies within 70–80% of rated capacity. Diesel generation is also commonly sized to peak demand. These characteristics serve to constrain the possible RE penetration. While energy storage can relieve the constraint, this adds cost and complexity to the system. This paper identifies an alternative approach, redefining the low load capability of diesel generation. Low load diesel (LLD) allows a diesel engine to operate across its full capacity in support of improved RE utilization. LLD uses existing diesel assets, resulting in a reduced-cost, low-complexity substitute. This paper presents an economic analysis of LLD, with results compared to conventional energy storage applications. The results identify a novel pathway for consumers to transition from low to medium levels of RE penetration, without additional cost or system complexity.

Economic justification of concentrating solar power in high renewable energy penetrated power systems

Concentrating solar power (CSP) plants are able to provide both renewable energy and operational flexibility at the same time due to its thermal energy storage (TES). It is ideal generation to power systems lacking in flexibility to accommodate variable renewable energy (VRE) generation such as wind power and photovoltaics. However, its investment cost currently is too high to justify its benefit in terms of providing renewable energy only. In this paper we evaluate the economic benefit of CSP in high renewable energy penetrated power systems from two aspects: generating renewable energy and providing operational flexibility to help accommodating VRE. In order to keep the same renewable energy penetration level during evaluation, we compare the economic costs between the system with a high share of VRE and another in which some part of the VRE generation is replaced by CSP generation. The generation cost of a power system is analyzed through chronological operation simulation over a whole year. The benefit of CSP is quantified into two parts: (1) energy benefit—the saving investment of substituted VRE generation and (2) flexibility benefit—the reduction in operating cost due to substituting VRE with CSP. The break-even investment cost of CSP is further discussed. The methodology is tested on a modified IEEE RTS-79 system. The economic justifications of CSP are demonstrated in two practical provincial power systems with high penetration of renewable energy in northwestern China, Qinghai and Gansu, where the former province has massive inflexible thermal power plants but later one has high share of flexible hydro power. The results suggest that the CSP is more beneficial in Gansu system than in Qinghai. The levelized benefit of CSP, including both energy benefit and flexibility benefit, is about 0.177–0.191 $/kWh in Qinghai and about 0.238–0.300 $/kWh in Gansu, when replacing 5–20% VRE generation with CSP generation.

Netload-constrained Unit Commitment Considering Increasing Renewable Energy Penetration Levels: Impact of Generation Schedules and Operational Cost

In the context of low carbon power systems, the penetration levels of Renewable Energy Sources (RES) are expected to increase dramatically. In this regard, this paper investigates the maximum RES penetration level constrained by net load while considering an inflexible Unit Commitment (UC) model. To solve the UC problem, an enhanced priority list (EPL) based method is developed. In the proposed method, the plants were activated sequentially based on the operational price. The system constraint violations were repeatedly corrected until all system constraints (such as net load and spinning reserves) were satisfied. The proposed EPL method was efficient to achieve a near optimal solution under high shares of RES. Furthermore, the research work investigates three different scenarios representing penetration levels of 10% solar-only, 14.5% wind-only and 27.5% mixture of both solar and wind. The impact of each penetration level on the system scheduling and operational cost were analyzed in detail. The analysis presented shows that a potential operational cost savings of 21.6 $/MW, 20 $/MW and 11.1 $/MW is feasible under each of the represented scenarios, respectively.

Influence of Stochastic Dependence on Small-Disturbance Stability and Ranking Uncertainties

A high level of stochastic dependence (or correlation) exists between different uncertainties (i.e., loads and renewable generation), which is nonlinear and non-Gaussian and it affects power system stability. Accurate modeling of stochastic dependence becomes more important and influential as the penetration of correlated uncertainties (such as renewable generation) increases in the network. The stochastic dependence between uncertainties can be modeled using 1) copula theory and 2) joint probability distributions. These methods have been implemented in this paper and their performances have been compared in assessing the small-disturbance stability of a power system. The value of modeling stochastic dependence with increased renewables has been assessed. Subsequently, the critical uncertainties that most affect the damping of the most critical oscillatory mode have been identified and ranked in terms of their influence using advanced global sensitivity analysis techniques. This has enabled the quantification and identification of the impact of modeling stochastic dependence on the raking of critical uncertainties. The results suggest that multivariate Gaussian copula is the most suitable approach for modeling correlation as it shows consistently low error even at higher levels of renewable energy penetration into the power system.

Representation of Storage Operations in Network-Constrained Optimization Models for Medium- and Long-Term Operation

This paper proposes a model to carry out analysis of storage facilities operation including a transmission network. The model represents a short-term storage operation in an approximated way that reduces computational requirements, which makes it suitable for medium- and long-term operational planning in power systems with a high level of renewable energy penetration. In the proposed model, we cluster hourly data using the so-called system-states framework developed in previous work. Within this framework, nonconsecutive similar time periods are grouped, while chronological information is represented by a transition matrix among states. We extend the system-state framework from a single-bus system to a transmission network. We define and analyze two alternative sets of representative variables for clustering hours to obtain system states when the transmission network is considered. This extension of the system states framework allows us to evaluate the impact of transmission congestions in medium- and long-term planning models in a reasonable computation time. A case study shows that the proposed model is 235 times faster than an hourly approach, used as benchmark, whereas the overall system cost is approximated with less than 2% error. The overall charging/discharging trends are similar enough to those of the hourly model, being hydro storage better approximated than fast-ramping batteries. Besides, for the analyzed case study, it is shown how congestion in the transmission network in fact improves the accuracy of the proposed approach.

Reliability Evaluation of Renewable Energy Share in Power Systems

In this research, Renewable Energy (RE) represents the existing power systems with different levels. However, because of the intermittent nature of these sources, it is necessary to analyze systems’ reliability with different RE penetration levels. This work presented a simulation method for reliability evaluation of renewable penetrated power systems. Some reliability indices were proposed for the case of power systems with renewable power plants. The adopted approach used the historical data of renewable energy resources, mainly wind and solar to estimate the power that can be generated and compared with the demand to find the power mismatch. Therefore, this approach can be utilized to determine the penetration level that renewable energy can be shared, and it also helps the system operators in deciding the percentage of the generation that RE power plant can provide.

Determining the Flexible Ramping Capacity of Electric Vehicles to Enhance Locational Flexibility

A high penetration level of renewable energy in a power system increases variability and uncertainty, which can lead to ramping capability shortage. This makes the stable operation of a power system difficult. However, appropriate management of electric vehicles (EVs) can overcome such difficulties. In this study, EVs were applied as a flexible ramping product (FRP), and a method was developed to increase the system ramping capability. When increasing the FRP to the amount required for the system, the effect on transmission lines cannot be neglected. Thus, the required FRP considering transmission constraints is calculated separately for each zone to secure deliverability. To make adjustment possible, the zonal available capacity is calculated by considering the probabilities of the location and the plugged and charged states of EVs. The applicability of EVs as an FRP resource is examined, and the results showed that they can be used at a more significant level considering the transmission constraints.

Two-Stage Stochastic Model Using Benders’ Decomposition for Large-Scale Energy Resource Management in Smart Grids

The ever-increasing penetration level of renewable energy and electric vehicles threatens the operation of the power grid. Dealing with uncertainty in smart grids is critical in order to mitigate possible issues. This paper proposes a two-stage stochastic model for a large-scale energy resource scheduling problem of aggregators in a smart grid. The idea is to address the challenges brought by the variability of demand, renewable energy, electric vehicles, and market price variations while minimizing the total operation cost. Benders' decomposition approach is implemented to improve the tractability of the original model and its computational burden. A realistic case study is presented using a real distribution network in Portugal with high penetration of renewable energy and electric vehicles. The results show the effectiveness of the proposed approach when compared with a deterministic model. They also reveal that demand response and storage systems can mitigate the uncertainty.