Power Grid Integration Research Articles

Design of cascaded controller based on coyote optimizer for load frequency control in multi-area power systems with renewable sources

Electricity generation from renewable sources is on the rise. The irregular presence of these sources increases the frequency variations induced by the load variance. The penetration of renewable energy sources increases the instability of the integrated power grid due to decreased system inertia. Therefore, this paper presents an optimal controller design of proportional-derivative with filter cascaded-proportional-integral (PDn-PI) using an innovative coyote optimization algorithm (COA). The modelling of the renewable energy sources (RESs) of photovoltaic (PV) and wind farm interconnection is considered in the load frequency control (LFC). The COA is adopted and integrated with the PI/ PID/ cascaded PDn-PI controllers for the sake of optimally tuning and specifying their gains. Furthermore, the powerful performance of the proposed COA-tuned PDn-PI controller is validated, under all cases studied, not only over PI and PID controllers but also, over the previously reported approaches. To get complete picture of the string of victories gained by the proposed technique, the dynamical uncertainties of load demand and RESs are investigated in both models as third case. The simulation investigation reveals the robustness and superiority dynamic responses of the cascaded PDn-PI with COA in direct contrast to other approaches even under these uncertainties.

Short-term Global Horizontal Irradiance Prediction Based on Deep Echo State Network

The prediction of global horizontal irradiance have a great impact on the stability and economic benefits of photovoltaic (PV) power generation. In this paper, we adopt the method of Deep Echo State Network (DESN) to predict the global horizontal irradiance in different areas one hour in advance. Under the same conditions, the results show that DESN are better than BP, SVM, ESN methods in the prediction accuracy. Experiments show that the proposed models show superior ability in predicting solar irradiance and have great application potential in power grid integration.

A METHOD TO MITIGATE THE IMPACT OF CYCLING OPERATION AND CARBON EMISSIONS

In developed countries, the average daily variation in hourly demand for electric power is about 40% of the peak demand. To meet the variation in hourly demand, the steam power plants must vary the generation using cycling operation. Many large countries such as USA, Russia, and European Union use multiple time zones in their territory to match their standard time with the daylight hours. However, these time zones do not focus on reducing the cycling operation of steam power plants. This model proposes the use of a precise algorithm in setting up multiple time zones in a territory to reduce the cycling operation of steam power plants. It recommends setting up multiple time zones in any geographic territory across the globe with an integrated power grid where the longitude difference between the Far East and Far West is more than an hour of solar time. It has been demonstrated by applying this model that the differential between peak and off-peak electrical power demand in the target territory can be reduced. This has a direct influence on the load following operations of steam power plants and shall reduce carbon emissions from the target territory.

WEC Array Optimization with Multi-Resonance and Phase Control of Electrical Power Take-Off

This new research provides transformative marine energy technology to effectively power the blue economy. Harmonizing the energy capture and power from Wave Energy Converter (WEC) arrays require innovative designs for the buoy, electric machines, energy storage systems (ESS), and coordinated onshore electric power grid (EPG) integration. This paper introduces two innovative elements that are co-designed to extract the maximum power from; i) individual WEC buoys with a multi-resonance controller design and ii) synchronized with power packet network phase control through the physical placement of the WEC arrays reducing ESS requirements. MATLAB/Simulink models were created for the WEC array dynamics and control systems with Bretschneider irregular wave spectrum as inputs. The numerical simulation results show that for ideal physical WEC buoy array phasing of 60 degrees the ESS peak power and energy capacity requirements are minimized while the multi-resonant controllers optimize EPG power output for each WEC buoy.

Forword Special Issue: “Best Papers From the 2021 IEEE Photovoltaic Specialists Conference”

The IEEE Photovoltaic Specialists Conference (PVSC) is the leading venue for presentation of the latest results on PV materials and devices. The conference focuses on the following 12 topical areas: 1) fundamentals and new concepts for future technologies; 2) chalcogenide thin film solar cells; 3) high-efficiency multijunction and concentrator technologies; 4) silicon photovoltaic materials and devices; 5) characterization methods; 6) perovskite and organic materials and solar cells; 7) space and specialty technologies; 8) PV modules, manufacturing, systems, and applications; 9) PV module and system reliability; 10) power electronics and grid integration; 11) solar resource for PV and forecasting; 12) PV deployment, policy, and sustainability. This year, for the first time, the program committee was asked to invite authors of particularly important or interesting contributions to submit their work to the IEEE JOURNAL OF PHOTOVOLTAICS in place of publishing in the conference proceedings. A total of 73 articles were invited to contribute manuscripts and 29 were submitted to the journal. A total of 23 of these have been accepted for publication and are included in a Special Issue of the journal. Accepted articles include topics from areas 2), 4), 5), 8), 9), 11), and 12) from the abovementioned list.

Исследование влияния переменной выработки альтернативных источников энергии на работу объединенной энергосистемы

The aim of the work was to analyze the efficiency of solar and wind power plants when they work as part of an integrated power grid using the example of the IPS of the South, to determine the share of electricity that can be generated at RES facilities, taking into account their intermittent operation, and to assess the possibility of balancing the network with a decrease in RES generation at night and in calm weather at the expense of electricity from wind farms in other regions of the IPS of the South. An analysis of the possible generation of electricity by renewable energy facilities showed that with an installed capacity of 13% per year, they will be able to meet 3.5% of the needs of the regions included in the UES of the South. During the day, the maximum consumption was recorded in the region of 11-12 hours and 19-21 hours. Solar generation has a maximum at noon, so it can compensate for the daily peak in consumption. In the evening hours, wind generation and solar generation are minimal. Therefore, they cannot be used to compensate for increased consumption, and traditional generation is necessary. As a result, it is not possible to reduce the installed capacity of traditional RES generation. To compensate for the decrease in WPP generation in summer, the installed capacity of WPP and SPP should be equal, and at present, in the IPS of the South, the capacity of WPP exceeds the capacity of SPP twice

Deep decarbonization of integrated power grid of eastern South Asia considering hydrogen and CCS technology

This study integrates grid-connected hydrogen storage and carbon capture and storage (CCS) technology in a spatially disaggregated capacity expansion model, that can explicitly characterize the operational behavior of other conventional technologies. The model is then used to assess the decarbonizing pathways of the integrated power grid of four countries: Bangladesh, Bhutan, India, and Nepal of South Asia under multiple policy scenarios. The impact of the cost associated with hydrogen system components, and with capturing, transporting, and injecting CO2 in storage sites on the technology choices and their capacities are further evaluated through sensitivity analysis. The hydrogen storage system is effective in tapping surplus energy produced from intermittent renewables mostly in coal deficit regions for both short as well as long-term duration, but its large-scale deployment depends on electrolyzer and fuel cell cost reductions by more than 20% to compete against battery technology. In a very optimistic situation of 90% cost reduction, northern, western, southern parts of India and Bangladesh can completely decarbonize its power sector by 2050 through the installation of about 593 GW, 395 GW, 138 GW, and 120 GW of hydrogen storage tank. The storage and production profiles of hydrogen are influenced by seasonal, weather, and diurnal variations. Under limited solar PV and nuclear scenario, India should start operating CCS-based coal power plants from 2030 to meet the 80% emission reduction target and techno-economically feasible capacity requirements reach about 179 GW, 106 GW, and 35 GW by 2050 in the eastern, western, and southern parts of India respectively.

Research on the New Topology and Coordinated Control Strategy of Renewable Power Generation Connected MMC-Based DC Power Grid Integration System

The modular multilevel converter (MMC) station connected to the islanded renewable energy generation system needs to adopt the voltage frequency (VF) control to provide AC voltage. The single-pole converter fault will unbalance the input and output power of the DC power grid, which causes the DC voltage or the bridge arm current of the non-fault pole to exceed the protection value in the time scale of tens to hundreds of milliseconds, leading to cascading failures. To realize the fault ride-through (FRT) of single-pole converter fault, this paper analyzes the electrical characteristic of the system. Based on the analysis, the existing topology is optimized and the reasonable operation reserved margin is designed. Furthermore, the corresponding control strategy is proposed, which can not only ensure the single-pole converter block fault ride-through but can also realize economic, stable, and resilient power supply and address asymmetrical problems. Finally, the simulation model is built in PSCAD/EMTDC and the simulation results validate the effectiveness of the proposed control strategy.

A Hybrid GA–PSO–CNN Model for Ultra-Short-Term Wind Power Forecasting

Accurate and timely wind power forecasting is essential for achieving large-scale wind power grid integration and ensuring the safe and stable operation of the power system. For overcoming the inaccuracy of wind power forecasting caused by randomness and volatility, this study proposes a hybrid convolutional neural network (CNN) model (GA–PSO–CNN) integrating genetic algorithm (GA) and a particle swarm optimization (PSO). The model can establish feature maps between factors affecting wind power such as wind speed, wind direction, and temperature. Moreover, a mix-encoding GA–PSO algorithm is introduced to optimize the network hyperparameters and weights collaboratively, which solves the problem of subjective determination of the optimal network in the CNN and effectively prevents local optimization in the training process. The prediction effectiveness of the proposed model is verified using data from a wind farm in Ningxia, China. The results show that the MAE, MSE, and MAPE of the proposed GA–PSO–CNN model decreased by 1.13–9.55%, 0.46–7.98%, and 3.28–19.29%, respectively, in different seasons, compared with Single–CNN, PSO–CNN, ISSO–CNN, and CHACNN models. The convolution kernel size and number in each convolution layer were reduced by 5–18.4% in the GA–PSO–CNN model.

Flexible Dispatch for Integrated Power and Gas Systems Considering Power-to-Gas and Demand Response

Aiming at the problem of insufficient flexibility of the power system caused by large-scale wind power grid integration, a flexible economic dispatch model of the electricity-gas integrated system that considers power-to-gas and demand responses is proposed. First, it elaborates on the scheduling flexibility and demand response model. Secondly, the power system and the natural gas system are regarded as different stakeholders; with the goal of minimizing their respective operating costs, a two-tier distributed coordination optimization model of electricity and gas system is established. In order to achieve the coordination and optimization of the upper and lower systems, slack variables are introduced to describe the infeasible part of the power system scheduling results in the natural gas system and are used for interactive iterative solution of the model. The numerical results of the revised IEEE 30-node power system and 10-node natural gas system illustrate the effectiveness and necessity of the proposed model, as well as the superiority of comprehensively considering power-to-gas and demand response in improving the flexibility and economy of the power system.

A convolutional neural network-based approach to composite power system reliability evaluation

This paper proposes a machine learning-based approach in conjunction with Monte Carlo simulation (MCS) to improve the computation efficiency of composite power system reliability evaluation. Traditional composite system reliability evaluation approaches are computationally demanding and may become inapplicable to large integrated power grids due to the requirements of repetitively solving optimal power flow (OPF) for a large number of system states. Machine learning-based approaches have been used to avoid solving OPF in composite system reliability evaluation except in the training stage. However, current approaches have been derived to classify system states into success and failure states (i.e., up or down). In other words, they can be used to evaluate power system probability and frequency reliability indices, but they cannot be used to evaluate power and energy reliability indices unless OPF is solved for each failure state to determine minimum load curtailments. In this paper, a convolutional neural network (CNN)-based regression approach is proposed to determine the minimum amount of load curtailments of sampled states without solving OPF, except in the training stage. Minimum load curtailments are then used to evaluate power and energy indices (e.g., expected demand not supplied) as well as to evaluate the probability and frequency indices. The proposed approach is applied on several systems including the IEEE Reliability Test Systems (The IEEE RTS and IEEE RTS-96) and Saskatchewan Power Corporation in Canada. Results show that the proposed approach is computationally efficient (fast and accurate) in calculating the most common composite system reliability indices. The developed source code of the proposed method is available to the community for future research and development.

An ultra-short-term scheduling model for cascade hydropower regulated by multilevel dispatch centers suppressing wind power volatility

In China, cascade hydropower stations are widely used in the ultra-short-term scheduling of power grids to eliminate power fluctuations caused by large-scale wind power grid integration due to their quick load tracking characteristics. They are usually operated jointly by multilevel dispatch centers (MLDCs). However, the ultra-short-term hydropower scheduling (USHS) of cascade hydropower stations controlled by MLDCs faces difficulties in coordinating power output regulation (POR) among stations with different dispatch levels, frequent fluctuations in the station power output, and complex solution difficulties. In this paper, a USHS model for cascade hydropower regulated by MLDCs suppressing wind power volatility is developed to address the above problems based on mixed-integer linear programming. First, a novel objective function that minimizes the POR of cascade hydropower considering the planed load rate and operating state is combined with the coordination strategy to cooperate the POR among MLDC stations. Then, the minimum continuous generating period constraint containing the output ramping limit is proposed to prevent the hydropower station power output from fluctuating frequently. Finally, the power output function of the hydropower station, obtained by aggregation technology from multiple nonlinear characteristic curves, is linearized by improved special ordered sets of type two to achieve an efficient solution. The scheduling results from the Beipan River in southwest China demonstrate the feasibility and validity of the model, and the model can obtain reasonable POR results in an acceptable computational time.

A Critical Survey on Renewable Energy Applications in the Philippines and China: Present Challenges and Perspectives

China’s Belt and Road (B&R) initiative provides new ideas and opportunities for international cooperation. Renewable energy plays a crucial role not only in the national sustainable development framework of China and the Philippines but also in bilateral cooperation between them. However, some obstacles still need to be addressed because renewable energy cooperation between China and the Philippines has not been thoroughly and comprehensively studied to date. Based on an in-depth analysis of current renewable energy cooperation between China and the Philippines, this paper employs PESTEL analysis to fully investigate the cooperative advantages and disadvantages by considering politics (P), economy (E), society (S), technology (T), environment (E), and legislation (L) and proposes several constructive suggestions. The ultimate purpose was to design feasible schemes to ensure the sufficient utilization of renewable energy and the construction of integrated power grid systems to meet shortages of electricity supply especially in the isolated small islands in the Philippines through cooperation with China. In particular, it offers valuable advice concerning the U.S.-China trade war and COVID- 19 pandemic, outlining how cooperation in the exploitation of potential renewable energy is vital.

Power Grid Integration and Use-Case Study of Acid-Base Flow Battery Technology

There are many different types of energy storage systems (ESS) available and the functionality that they can provide is extensive. However, each of these solutions come with their own set of drawbacks. The acid-base flow battery (ABFB) technology aims to provide a route to a cheap, clean and safe ESS by means of providing a new kind of energy storage technology based on reversible dissociation of water via bipolar electrodialysis. First, the main characteristics of the ABFB technology are described briefly to highlight its main advantages and drawbacks and define the most-competitive use-case scenarios in which the technology could be applied, as well as analyze the particular characteristics which must be considered in the process of designing the power converter to be used for the interface with the electrical network. As a result, based on the use-cases defined, the ESS main specifications are going to be identified, pointing out the best power converter configuration alternatives. Finally, an application example is presented, showing an installation in the electrical network of Pantelleria (Italy) where a real pilot-scale prototype has been installed.

Using Thermal Energy Storage to Relieve Wind Generation Curtailment in an Island Microgrid

The uncertainty and intermittency of the available wind resource in nature would potentially cause wind generation curtailment when the flexibility of the integrated power grid is limited, especially in small-scale microgrids for islands. In this paper, an optimal configuration method is proposed to use thermal energy storage (TES) to relieve wind generation curtailment in an island microgrid. The thermal network is modeled along with the electrical network to utilize its regulation capability, while TES is introduced as an additional flexibility resource. The detailed cost models of combined heat and power (CHP) units and TES are presented to realize the objective of minimizing the overall operating cost. The performance of TES in improving wind power utilization is firstly validated by using an electrical boiler (EB) as a benchmark and further analyzed under different scenarios considering the growths of wind power capacity, electrical load, and heat load. The effectiveness of the proposed method is validated using real-world data obtained from the practical island microgrid.

A Deep Reinforcement Learning-Based Multi-Agent Framework to Enhance Power System Resilience Using Shunt Resources

Existing power system resilience enhancement methods, such as proactive generation rescheduling, movable sources dispatch, and network topology reconfiguration, do not explore the capability and flexibility of shunts to maintain voltage stability during and after disrupting events. Besides, existing methods rely on accurate system models that are not easily scalable for large integrated power grids. In this paper, a data-driven multi-agent framework based on a deep-reinforcement-learning algorithm is proposed to overcome the computation and scalability concerns related to precise system models and to plan for the deployment of shunts for power system resilience enhancement. Specifically, voltage violations due to outages of multiple lines during windstorms are taken as an example of a power system resilience improvement problem. Then, a multi-agent based hybrid soft actor critic (HSAC) algorithm is developed for offline siting and sizing as well as online controlling of shunt reactive power compensators to enhance voltage resilience. The HSAC algorithm is derived from the fundamental SAC algorithms that contain both continuous and discrete action spaces. The proposed multi-agent framework learns from previous experiences and eventually gets trained to determine proper locations and sizes for shunts to avoid voltage violations during multiple line failures. The proposed approach is demonstrated on the IEEE 57-bus and IEEE 300-bus systems. The results show that the proposed multi-agent framework is effective for installation planning and controlling of shunts to enhance power system resilience.

Multilevel Converter Applications in the Area of Renewable Energy, More-Electric Propulsion, Electric Vehicles and Power Grid Integration

The papers in this special section focus on Multilevel converter applications in the area of renewable energy, electric propulsion, electric vehicles and power grid integration. Today, power electronics converters have shifted into a decisive part of our ways of living, noticeably for the profitable utilization of renewable energy sources (RESs). Electric network grid, even standalone type, “more-electric” propulsion, electric vehicles, space applications, military, medical, process/heavy industries, etc., are all affected by converters. In the last few years, we have seen a rising demand for the grid-connected multilevel converter (MC) structures, precisely with RES integration.

ЗАБЕЗПЕЧЕННЯ СТАЛОГО РОЗВИТКУ ЕКОНОМІКИ ТА ПІДВИЩЕННЯ ЕНЕРГЕТИЧНОЇ БЕЗПЕКИ НА ОСНОВІ ВИКОРИСТАННЯ ВЕД: ПРОБЛЕМИ ТА ПЕРСПЕКТИВИ

Анотація. Обґрунтовано, що фактором економічного зростання, підвищення економічної та енергетичної безпеки, збереження навколишнього середовища від згубного впливу наслідків споживання вуглеводневих джерел енергоресурсів є сталий розвиток відновлюваної енергетики. Розглянуто стан і перспективи використання відновлюваних джерел енергії (ВДЕ) у світі. Представлено рейтинг країн за питомою вагою електроенергії, виробленої з ВДЕ у відсотках до первинних джерел за період 2015—2019 рр., який показує, що найбільшу ефективність ВДЕ мають такі країни, як Ісландія, Кенія і Латвія, а найбільше зростання спостерігається в Україні, Великобританії, Туреччині, Данії, Японії, Франції, США і Німеччині. Узагальнено фактори зростання попиту на ВДЕ, зокрема: паритет ціни і продуктивності внаслідок зниження ціни на ВДЕ; підвищення ефективності виробництва енергії внаслідок технологічного прогресу та впровадження інноваційних технологій у ВДЕ; інтеграція енергомереж і збалансування навантаження на них; стимулювання попиту на ВДЕ великими містами — реалізація стратегії «розумного міста», яка включає «розумну» енергетику; розвиток громадського володіння мережами і ВДЕ; активна участь країн, що розвиваються, у поширенні відновлюваної енергетики; зростаюча участь корпоративного сектору в розвитку відновлюваної енергетики. Визначено взаємозв’язок цілей розвитку сфери енергетики щодо її доступності, надійності, стійкості та цілей у галузі сталого розвитку. Так, скорочення масштабів бідності (ціль 1) передбачає розширення доступу до базових ресурсів і послуг, наявності сучасної інфраструктури, елементом якої є ВДЕ; використання екологічно чистої відновлюваної енергетики сприятиме зниженню ризиків для здоров’я (запобігання хворобам і боротьбі з пандеміями) — ціль 3; створення стійкої інфраструктури, сприяння інноваціям (ціль 9) передбачає застосування чистих та екологічно безпечних технологій і сталого розвитку енергетики; використання ВДЕ має синергетичний зв’язок із реалізацією цілі 13 — термінові заходи боротьби зі зміною клімату і його наслідками. Ключові слова: цілі сталого розвитку, зростання економіки, енергетична безпека, відновлювані джерела енергії, вуглеводневе паливо, декарбонізація. Формул: 0; рис.: 0; табл.: 2; бібл.: 17.

An X-shaped-switching-network high-step-up converter for grid integration of renewable energy sources

Power converters play a pivotal role in forming modern renewable energy sources integrated power grids. Among all grid-forming converters, high step-up converters with great nonlinear dynamic responses and fault recovery abilities have been sought after and developed in recent decades. This study proposes a novel X-shaped switching network (X-net)-based high-step-up converter. Specifically, an X-shaped switching network is designed to realize energy conversion of the converter, which, different from traditional impedance networks, only comprises switches and diodes. With this radically new X-shaped network, the proposed X-net converter is able to realise additional voltage pumping and low capacitor stress, hence improving dynamic responses and system reliability. In this study, the theory, analysis and simulation and prototype experiments of the proposed X-net converter with additional voltage pumping are presented in detail. Extensive comparisons between the X-net converter and its traditional counterparts are also presented which verifies the superiority of the proposition. The proposed X-net based high step-up converter bears significant potential as future grid-forming converters.

Research Hotspots and Tendency of Green Building Based on Bibliometric Analysis

Green building is a research hotspot in the field of Construction Engineering in recent years. This paper is based on 987 articles collected from the web of Science (WOS) core collection database, using Excel as the data statistical tool, the statistical research is carried out from the aspects of time output, hot institutions, hot journals, hot authors; VOSviewer is used to analyze the knowledge graph of hot authors and hot countries and regions, CiteSpace is used to analyze the co-occurrence words and burst words of Keywords, and the frontier of international green building research is obtained. The results show that: the research process of green building can be divided into three main stages: initial development, stable development, rapid development; At present, the eight major research topics are green roof, comparative assessment, building health, conventional building material, engineering design, building green, indoor environment quality, low-carbon integrated power grid.