Future Electric Power Research Articles

Modeling Electricity Generation and Consumption in Cameroon

Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models' results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26%, 5.26%, and 5.77% deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

Hydrogen Energy in Electrical Power Systems: A Review and Future Outlook

Hydrogen energy, as a zero-carbon emission type of energy, is playing a significant role in the development of future electricity power systems. Coordinated operation of hydrogen and electricity will change the direction and shape of energy utilization in the power grid. To address the evolving power system and promote sustainable hydrogen energy development, this paper initially examines hydrogen preparation and storage techniques, summarizes current research and development challenges, and introduces several key technologies for hydrogen energy application in power systems. These include hydrogen electrification technology, hydrogen-based medium- and long-term energy storage, and hydrogen auxiliary services. This paper also analyzes several typical modes of hydrogen–electricity coupling. Finally, the future development direction of hydrogen energy in power systems is discussed, focusing on key issues such as cost, storage, and optimization.

The pitfall in designing future electrical power systems without considering energy return on investment in planning

Measuring the limitations of transitioning to 100% renewable energy systems partly equates with the capability of quantifying associated net-energy production. To foresee future possibilities, an advanced systemwide energy-return-on-investment (EROI) model was constructed. Driven by the thorough consideration of the existing weaknesses of EROI, the model integrates the concept of energy statistics, life cycle assessment techniques and energy system modelling in order to overcome the underlying primary energy quality issues, boundary condition problems and energy system design related uncertainties that compromises comparability of EROI during the energy transition. This model was applied to the Israeli power system that presents a unique opportunity to examine the vulnerability of depending on limited resources and the connection of EROI to system design. This study demonstrates the dependency of EROI on the energy transition path, system design requirements expressed via interactive linkages of curtailment, variable renewable energy penetration and storage system design, and resource diversity. Achieving a very high variable renewable energy penetration by 2050 with solar photovoltaics carries a risk of falling below an EROI value of 10, such vulnerability can be largely minimised by well-conducted manoeuvring of the system design and resource diversification. Despite the large uncertainty of this study, the need for a multicriteria designing technique is out of the question.

Laboratory for Analysis of Microgrid with Real Time Simulation

It becomes essential for Brazil the formation of critical mass and technological base in the microgrid subject and, mainly, the creation of an infrastructure that allows the accomplishment of research in this area of knowledge. Faced with this necessity, it was verified the viability of implementing a laboratory to perform analysis of microgrids systems in the actual premises of the Laboratory of Automation and Simulation of Electrical Systems, which is allocated in Itaipu Technological Park Foundation - Brazil dependencies. In the presented context, this work brings the description of the provisioned infrastructure - whose the main feature will be to add flexibility of analysis through the joint application of real, emulated elements and real time simulation platform, being at the same level of international reference laboratories as well as the fundamental aspects that provides the basis for your design and the possibilities of research envisaged from its implementation. The joint action of several researchers and enterprises will be stimulated and characterized as fundamental role for the transformation of this laboratory into a national reference in the study of microgrids serving as support for the electrical sector for the complete understanding of the new development trends of the future electrical power.

Trends and challenges of the interactions between microclimate and electric power systems

<p>The increasing penetration of renewables has made electric power systems meteorology-sensitive. Meteorology has become one of the decisive factors and the key source of uncertainty in the power balance. Macro-scale meteorology might not fully represent the actual ambient conditions of the loads, renewables, and power equipment, thus hindering an accurate description of load and renewables output fluctuation, and the causes of power equipment ageing and failure. Understanding the interactions between microclimate and electric power systems, and making decisions grounded on such knowledge, is a key to realising the sustainability of the future electric power systems. This review explores key interactions between microclimate and electric power systems across loads, renewables, and connecting transmission lines. The microclimate-based applications in electric power systems and related technologies are described. We also provide a framework for future research on the impact of microclimate on electric power systems mainly powered by renewables.</p>

Change in Electric Power Consumption in Mongolia in 2020 and the Impact of the COVID-19 Pandemic

This paper deals with the change in electric power (EP) consumption in Mongolia in 2020 based on data on the maximum and minimum EP consumption a day, provided by NPTG. The changes in EP consumption in Mongolia in detail as weekly or seasonal changes as well as the impact of the COVID-19 pandemic have not been clear, even though annual EP consumption was provided from the reports of the World Bank, IEA, and other international institutes as statistical data. Differences in the maximum average hourly and the minimum EP consumption in a day was 277 MWh (30.2%) and in the maximum and minimum daily EP consumption in 2020, which appeared in winter and summer, respectively, was 933 MWh (71.3%). Also, a 104-MWh (14.8%) drop was confirmed on special days like Naadam. To discuss the impact of COVID-19, the values of 2017 were used as a criterion for a year absent of a pandemic, and the stringency index, an indicator used to quantify the severity and stringency of government policies and measures, was introduced, and compared with the monthly EP consumption in 2020. The COVID-19 pandemic decreased the EP consumption of 40 MWh (2 to 6%) except in December due to the free-electricity policy. The EP consumption showed the dependency of the stringency index, particularly a clear drop over 50 of the index values. These new findings of EP consumption properties are expected to apply EP demand forecasting and make design plans for future EP systems in Mongolia.

A real time peer-to-peer energy trading for prosumers utilizing time-varying building virtual energy storage

With the increasing penetration of distributed energy resources (DER) in the electric power system, Peer-to-Peer (P2P) energy trading has become a promising paradigm for future electric power systems. Building thermal load, which is an important demand side resource, should be considered carefully in the design of a P2P trading method. In this paper, we investigate the application of building thermal energy storage capability in P2P energy trading. We aggregate and model building thermal loads as a virtual energy storage and derive a time-varying virtual energy storage system (T-VESS) model to quantify the flexibility of a building. Key parameters of T-VESS, including charging/discharging rate, energy capacity, and state of charge (SOC), are analyzed so that T-VESS can be embedded in the building prosumer model to participate effectively in electricity-oriented P2P energy trading. We propose a real time P2P energy trading method of prosumers based on model predictive control (MPC). This method consists of an energy supply and demand quantification stage and a transaction price optimization stage, which can effectively capture the time-varying nature of T-VESS. To preserve the trading preference for prosumers, we propose a distributed P2P energy trading actions implementation method based on the continuous double auction (CDA) considering multiple trading preference grades. Numerical results demonstrate that the proposed P2P energy trading method considering T-VESS can reduce the operational cost of prosumers by 3.7%, while also promoting the local integration of renewable energy by 3.1%. Furthermore, compared to existing P2P trading methods considering single preference grade, the proposed method greatly enhances the utilities of both individual prosumers and the overall community.

Addressing the Security risk of a Massive Deployment of Photovoltaic Power for Electric Power Systems

Future electric power systems will incorporate a high percentage of Photovoltaic (PV) power generation as a means of mitigating environmental issues including global warming and energy depletion. The author observes that if the increase in uncertainties brought about by the PV penetration cannot be prevented, then it will be difficult to carry out the N-1 security level. To ensure the N-1 security requirement is met despite the uncertainties, paper has suggested a new notion of "robust power system security" along with many conditions to be met. In this research, and offer a model of uncertainties caused by PV generation, and use robust power system security to guide our choice of parameters. Next, simulate the system to learn more about, how PV and load disconnections affect stability, and how Fault Ride Through (FRT) and Dynamic Voltage Support (DVS) influence stability. Finally, it is demonstrated that the massive penetration of PV would significantly raise the complexity of burden jobs in future power system operation planning and real-time operation.

Power availability of PV plus thermal batteries in real-world electric power grids

As variable renewable energy sources comprise a growing share of total electricity generation, energy storage technologies are becoming increasingly critical for balancing energy generation and demand.In this study, a real-world electricity system was modeled rather than modeling hypothetical future electric power systems where the existing electricity infrastructure are neglected. In addition, instead of modeling the general requirements of storage in terms of cost and performance, an existing thermal energy storage concept with estimated capital cost that are sufficiently low to enable large-scale deployment in the electric power system were modeled. The storage unit is coupled with a photovoltaic (PV) system and were modeled with different storage capacities, whereas each storage unit had various discharge capacities.The modeling was performed under a baseline case with no emission constraints and under hypothetical scenarios in which CO2 emissions were reduced. The results show that power availability increases with increasing storage size and vastly increases in the hypothetical CO2 reduction scenarios, as the storage unit is utilized differently. When CO2 emissions are reduced, the power system must be less dependent on fossil fuel technologies that currently serve the grid, and thus rely more on the power that is served from the PV + storage unit.The proposed approach can provide increased knowledge to power system planners regarding how adding PV + storage systems to existing grids can contribute to the efficient stepwise decarbonization of electric power systems.

Real and virtual testing of the future electrical power systems

Real and virtual testing of the future electrical power systems

Are utilities overspending on electric power resilience? How can that be?

Few people doubt that the U.S. will encounter future electric power outages of long durations, disrupting a large number of people and businesses. Most industry observers believe that any improvement in the resilience of the U.S. electric-power network would be cost-beneficial. From an economic perspective, the desirability of improved resilience depends on the marginal benefits and marginal costs. Marginal benefits are especially hard to measure. There is also the question of whether utilities are applying the most cost-effective actions to improve resilience, which is difficult to judge but often ignored by state utility regulators in evaluating utility “resilience” plans. State utility regulators and electric system operators face the burden of answering to the heated public after an extended power outage. They will, not surprisingly, tend to err on the side of excessive resilience, which translates into higher electricity prices. Two probable explanations for this behavior are probability neglect and the precautionary principle. This essay concludes by posing less standard alternatives for policymakers to consider in addressing electric power resilience and the “outage” problem. Two alternatives are exploiting the price mechanism and compensating utility customers for extended power outages.

Benefits and barriers concerning demand response stakeholder value chain: A systematic literature review

Demand Response (DR) is acknowledged to play a relevant role in future electrical power systems. To achieve decarbonization, increasing shares of renewable electricity will induce changes in market design and system operation. New opportunities and challenges will emerge for all market participants. However, regulatory and technology bottlenecks combined with conflicts of interest among actors may deaccelerate DR implementation.This research performed a systematic literature review on five different databases to identify DR benefits and barriers attributable to different actors. Both benefits and barriers were found for all the stakeholders. Consumer bill savings and financial incentives were the most common benefits attributable to DR, on the contrary, consumer lack of interest and knowledge, privacy protection and cyber security were the most common referred barriers. In the second stage, both benefits and barriers were respectively divided into four main categories: Society-wide; Technology-wide; Financial and Market-wide and Environmental-wide benefits and Technology-wide, Economic and Market-wide context barriers. The classification of individual benefits and barriers demonstrated that some categories, such as technology-wide, are relevant both for benefits and barriers. DR implementation complexity and the number of stakeholders involved require DR policies to have certain specific characteristics to give them directionality towards DR successful implementation.

Carbon dioxide from oxy-fuel coal-fired power plant integrated green ammonia for urea synthesis: Process modeling, system analysis, and techno-economic evaluation

A high proportion of renewable energy integration will be one of the significant characteristics of future electric power grid, and power-to-NH3 technologies will become an important approach for inter-quarter long-term energy storage. Meanwhile, as an important method of peak regulation in power systems, coal-based power plant is necessary to implement CO2 capture. This study constructed a novel urea synthesis process based on renewable energy, including water electrolyzers, air separation, green ammonia, oxy-fuel combustion power plant, CO2 purification, and urea synthesis units. Coal- and natural gas-based urea synthesis processes were selected as the contrasting processes.The results showed that CO2 emissions from the novel process proposed in this work were 0.124–0.174 t CO2/t urea, which was much lower than that of the coal and natural gas-based urea processes (1.4 and 0.8 t CO2/t urea, respectively). In the current technical economy (with coal and natural gas prices of 450 CNY/t and 1.7 CNY/m3, respectively), the production cost of this new process was about 1.0–2.2 times higher than that of traditional processes. When the carbon tax values were 121 and 371 CNY/t, the total production costs of the natural gas- and coal-based urea process would exceed that of the new process, respectively. This study will provide a promising method for urea production based on renewable energy to realize CO2 utilization from coal-fired power plant.

Forecasting future electric power consumption in Busan New Port using a deep learning model

As smart and environmentally friendly technologies and equipment are introduced in the sea port industry, electric power consumption is expected to rapidly increase. However, there is a paucity of research on the creation of electric power management plans, specifically in relation to electric power consumption forecasting, in ports. In order to address this gap, this study forecasts future electric power consumption in Busan New Port (South Korea's largest container port) and, comparing this with the current standard electric power supply capacity, investigated the feasibility of maintaining a stable electric power supply in the future. We applied a Long Short-Term Memory (LSTM) model trained using electric power consumption and throughput data of the last 10 years to forecast the future electric power consumption of Busan New Port. According to the results, electric power consumption is expected to increase at an annual average of 4.9 % until 2040, exceeding the predicted annual 4.7 % increase in throughput during the same period. Given these results, the current standard electric power supply capacity is forecast to reach only 35 % of demand in 2040, indicating that additional electrical power supply facilities will be needed for stable port operation in the future.

2050年革新的超長期電力システムビジョン検討ツールの開発

2050年革新的超長期電力システムビジョン検討ツールの開発

Multi-source electricity information fusion methods: A survey

With the vigorous development of the global economy, the demand for electricity quality from all walks of life is also increasing, so it is essential to ensure the electric power grid’s safe, stable, and efficient operation. Multi-source electric power information fusion, as the core technology of electric power grid data processing, has become the foundation to promote the intelligent and automatic development of the electric power grid. This paper presents the first work on the survey of the methods of electricity information fusion. It first gives an overview of the process of electricity information fusion and shows the types of electricity data. Then, we provide different classifications of existing methods in view of communication annotation and electric power data, and conduct a thorough comparison and analysis of them. Moreover, we introduce the relevant data sets and evaluation criteria of electric power information and summarize the corresponding evaluation scenarios. Finally, we conclude the maturity of existing works and provide an outlook on future multi-source electric power information fusion methods.

Decentralized, Democratized, and Decarbonized Future Electric Power Distribution Grids: A Survey on the Paradigm Shift From the Conventional Power System to Micro Grid Structures

Decentralized, Democratized, and Decarbonized Future Electric Power Distribution Grids: A Survey on the Paradigm Shift From the Conventional Power System to Micro Grid Structures

Computational model for thermohydraulic analysis of an integral pressurized water reactor with mixed oxide fuel (Th, Pu)O2

The use of advanced generation III+ and IV nuclear reactors, and their applications, has become important, seen as a means capable of contributing to the global transition to more sustainable, affordable and reliable energy systems. This technology, which could be integrated into future carbon-free electric power generation systems with high proportions of different renewable energy sources, includes Small Modular Reactors (SMR). There are about 100 different proposed projects of Generation III+ and IV, of which about 50 are SMR concepts, in various stages of development and of different types of technologies. Other important issues for achieving the long-term sustainability of nuclear energy are the proper use of its fuel sources and the improvement of nuclear waste management. Therefore, fuels based on a mixture of oxides have been used successfully in several countries. In addition, the incorporation of thorium-based fuel is a current challenge for the new designs of advanced reactors. The present paper focuses on the analysis of a small modular integral pressurized water reactor (iPWR) with Thorium-Uranium Oxide (Th-U MOX) mixtures. A thermohydraulic model is developed using the Ansys CFX program, which allows the calculation of the temperature distribution in the section where the highest power is produced within the SMR IPWR core (critical section). The temperature distributions in the fuel, clad and coolant were calculated with the objective of verifying that they were within the safety limits.

Machine learning based demand response scheme for IoT enabled PV integrated smart building

The short-term forecasting of electric power consumption and renewable energy generation with high efficiency and advanced demand side management is essential for improving the energy flexibility provided by the smart buildings. However, the recent literature fails to present the mechanism for developing demand side management for energy flexibility. This article addresses the importance of developing an electric power consumption and renewable energy generation short-term forecasting model using a supervised machine learning approach. In this work, random forest and decision tree regression models are developed and used to forecast future electric power consumption and renewable energy generation. To validate the forecasting model performance using the MAE, RMSE, MAPE, and R2. This article proposes a day ahead dynamic pricing model for the demand response scheme. The day ahead dynamic pricing minimizes the peak time demand and end-user electricity tariff. A smart grid system must know the future short-term electric power consumption and renewable energy generation to enable the demand response scheme. The educational institute smart substation and weather station are integrated into the internet of things devices to enable real-time monitoring and control of the electric power consumption and renewable energy generation. The results show that the proposed DR scheme benefits end electricity users and smart grid operators.

Modified manta ray foraging optimization algorithm based improved load frequency controller for interconnected microgrids

The recent environmental crisis and global warming have compelled an energy transition, particularly in the power generation and transportation sectors. Increased energy competence and production will necessitate enormous efforts. Admittedly, power system inertia metrics have revealed reduced inertia attributes, which could lead to a catastrophic shutdown and security issues in future electrical power systems. The design of the load frequency controller is essential for improving frequency regulation and power system stability. Nonetheless, more research is needed into control development and design approaches that take into account renewable energy characteristics, complexities, connected electric vehicles (EVs), and uncertainties. Metaheuristic-based design methods and fractional order control have recently demonstrated an improved response when compared to classical design methods and integer-order controllers. This work presents an improved fractional order hybrid control system based on two modified versions of the Manta Ray Foraging Optimization (MRFO) Algorithm. The exploration and exploitation stages of the modified MRFO are enhanced by utilizing a chaotic map and a weighting factor. The transients and steady-state performance of the studied two-areas interconnected microgrids have been significantly improved by incorporating the advantages of both the suggested fractional order-based control approach and the proposed modified MRFO algorithms. While assessing the feasibility of the developed controller and modified optimizers, uncertainty, renewable energy fluctuations, load transients, and electric vehicle attributes are all properly considered. The modified MRFO's performances are evaluated using 23 benchmark functions, and the results are compared to the original MRFO and recent well-known optimization algorithms. Both statistical analysis and time-domain results demonstrate the superiority of the proposed modified optimizers and the proposed load frequency controller.