Electric Load Growth Research Articles

Overbuilding transmission: A case study and policy analysis of the Indian power sector

Policies to substantially increase the amount of renewable energy produced and electrify much of the transportation and industrial sectors to achieve greenhouse gas reduction goals envision an extensive expansion of the transmission system. One set of proposals calls for anticipatory transmission planning, namely, building transmission to regions with the potential to develop renewable energy resources before their actual development. This paper presents a case study of transmission expansion planning in India. Our study finds that it is possible to overbuild the transmission system even in a country that is rapidly developing thermal and renewable resources and has sizeable electricity load growth. Anticipatory transmission planning, high guaranteed returns and weak governance can result in transmission overbuilding. This cautionary finding motivates several recommended public policy reforms to reduce future overbuilds, while supporting economically efficient and environmentally sound transmission development.

Multi-stage Co-planning Model for Power Distribution System and Hydrogen Energy System Under Uncertainties

The increased deployment of electricity-based hydrogen production strengthens the coupling of power distribution system (PDS) and hydrogen energy system (HES). Considering that power to hydrogen (PtH) has great potential to facilitate the usage of renewable energy sources (RESs), the coordination of PDS and HES is important for planning purposes under high RES penetration. To this end, this paper proposes a multi-stage co-planning model for the PDS and HES. For the PDS, investment decisions on network assets and RES are optimized to supply the growing electric load and PtHs. For the HES, capacities of PtHs and hydrogen storages (HSs) are optimally determined to satisfy hydrogen load considering the hydrogen production, tube trailer transportation, and storage constraints. The overall planning problem is formulated as a multistage stochastic optimization model, in which the investment decisions are sequentially made as the uncertainties of electric and hydrogen load growth states are revealed gradually over periods. Case studies validate that the proposed co-planning model can reduce the total planning cost, promote RES consumption, and obtain more flexible decisions under long-term load growth uncertainties.

Optimal Allocation of Capacitor Banks and DSTATCOMs in Radial Distribution System Considering Electric Vehicle Load Growth

Optimal Allocation of Capacitor Banks and DSTATCOMs in Radial Distribution System Considering Electric Vehicle Load Growth

Long-term forecasting for growth of electricity load based on customer sectors

The availability of electrical energy is an important issue. Along with the growth of the human population, electrical energy also increases. This study addresses problems in the operation of the electric power system. One of the problems that occur is the power imbalance due to scale growth between demand and generation. Alternative countermeasures that can be done are to prepare for the possibility that will occur in the future or what we are familiar with forecasting. Forecasting using the multiple linear regression method with this research variable assumes the household sector, business, industry, and public sectors, and is considered by the influence of population, gross regional domestic product, and District Minimum Wage. In forecasting, it is necessary to evaluate the accuracy using mean absolute percentage error (MAPE). MAPE evaluation results show a value of 0.142 % in the household sector, 0.085 % in the business sector, 1.983 % in the industrial sector, and 0.131 % in the total customer sector.

Design of Inductive Power Taking System for Smart Grid Monitoring Equipment

Due to the continuous growth of urban electricity load and the increasing development of high-voltage transmission technology, the effective operation of the online monitoring equipment of the transmission line is particularly important, which is also a necessary condition for the development of the smart grid. However, the power supply conditions for the usage scenarios of smart grid monitoring equipment are limited. Conventional power supply methods such as battery power supply and new energy power generation have disadvantages such as cumbersome battery replacement, and the power supply stability is greatly affected by the environment, so they are difficult to meet the development trend of a rapid capacity increase of power grid and stable power supply of power equipment. Aiming at the technical bottleneck of smart grid monitoring equipment in power supply, this paper proposes a current transformer inductive power taking method based on capacitive reactance matching shunt, using the open air gap current transformer secondary winding set on the bus to connect the capacitor and its excitation inductance in series carry out capacitive impedance matching, and then shunt through another branch with load and connect it at both ends of the open air-gap current transformer to obtain electric energy. Through the circuit model experiment of the inductive power-taking system, it is verified that the current transformer inductive power-taking method based on capacitive reactance matching shunt can obtain more power.

PEMANFAATAN PANEL SURYA ON GRID PADA RUMAH TINGGAL BERDASARKAN JUMLAH BEBAN

Savings in electricity consumption at this time is something to note because the growth of electricity load in urban areas is very fast while the growth of power plants tends to be slow. One way to save PLN electricity consumption is to utilize solar panels as an alternative energy source, where some or all of the electricity load can be transferred to solar power plants (PLTS) on the grid. The research was conducted by load design methods and simulations of the loading of electrical power. The power generated by PLTS on grid is calculated based on the level of solar radiation, ranging from 06:30 to 18:00. Based on the results of the analysis obtained that by using PLTS on grid as an alternative energy source in residential homes, it can provide savings in PLN electricity consumption of 34.78% to 89.54%. These results show that the use of PLTS on grid is very suitable for its use in urban areas in order to support electricity saving policies

Probabilistic spatial load forecasting for assessing the impact of electric load growth in power distribution networks

Recently, high rates of urbanization reveal the need for more granular approaches of long-term load forecasting. The development of modern spatial load forecasting (SLF) methods can contribute to more effective planning of power distribution networks, while serving as decision making tools in the hands of regional planners and distribution system operators (DSOs). Nonetheless, the ever-present error of spatial allocation of future electric loads arises the need for probabilistic assessment of the long-term point forecasts. This paper proposes a methodology of probabilistic SLF that can be employed to assess the impact of load growth in power distribution networks. Firstly, an hierarchical trend method forecasts the peak of the electric loads at each subarea of the study area. Subsequently, the spatial root-mean-squared error across the service territory is calculated to be used for the construction of prediction intervals. Finally, a probabilistic power flow study based on Monte Carlo simulation seeks potential technical issues on the distribution network. The proposed methodology is demonstrated on a real-world distribution network. The results prove that the proposed probabilistic SLF method can lead DSOs to more reliable decisions in comparison to business-as-usual approaches.

Optimal siting of capacitors in distribution grids considering electric vehicle load growth using improved flower pollination algorithm

The optimal VAr compensation using capacitor banks (CBs) in radial distribution networks (RDNs) is solved in this paper while taking the growth of the load from electric vehicles (EVs) into consideration. This is accomplished by adapting an improved variant of the flower pollination algorithm (IFPA) with an enhanced local search capability. The primary objective of determining the locations and sizes of CBs is to minimize the distribution losses in the operation and control of RDNs. Additionally, the effect of CBs is shown by the increased net savings, greater voltage stability, and improved voltage profile. A voltage stability index (VSI) was used in the optimization process to determine the predefined search space for CB locations, and a double-direction learning strategy (DLS) was then considered to optimize the locations and sizes while maintaining a balance between the exploration and exploitation phases. Three IEEE RDNs were used to simulate various EV load increase scenarios as well as typical loading situations. According to a comparison with the literature, the IPFA produced global optimum results, and the proposed CBs allocation approach demonstrated enhanced performance in RDNs under all scenarios of EV load growth.

Развитие распределительных электрических сетей напряжением 11 и 33 кВ Республики Союз Мьянма

A drastic (by about a factor of three) increase of electricity demand is predicted for the next decade in the Republic of the Union of Myanmar. It is planned to connect all households to the country’s national power grid. These electrical load growth rates will require, first of all, a significant development of the 11 kV and 33 kV electrical distribution networks. The load curves of 33 kV substations are given. The results of the first load measurements in 11 kV electrical distribution networks are presented. Based on the load curves and load measurement results, the loading patterns of 11 kV and 33 kV power lines and 33/11 kV and 11/0.4 kV transformers were analyzed for the studied electrical networks of the Republic of Myanmar Mandalay district. In most cases, the existing load of 33/11 kV and 11/0.4 kV transformers does not exceed 65%, which allows their loading to be doubled without exceeding the permissible systematic overload capacity. The 33 kV lines also have at least a 100% transmission capacity margin. Most of 11 kV lines have no more than 40% capacity margin. The load of some 11 kV lines has reached the maximum level. Based on the obtained analysis results, the development lines of distribution networks in the Republic of the Union of Myanmar have been determined.

Techno‐economic optimization of a grid‐connected hybrid energy system considering electric and thermal load prediction

AbstractOptimal planning of hybrid energy systems has always been a considerable task. While several studies have conducted techno‐economic analysis on hybrid energy systems, most of them have neglected to consider appropriate electric and thermal load growth rates. This paper proposes an efficient strategy for optimizing a grid‐connected hybrid energy system considering electric and thermal load growth rates. HOMER software is used for optimizing hybrid energy systems. It uses a nonderivative optimization to recognize the system with the minimum net present cost (NPC) among hundreds of configurations. The exponential smoothing method is also used for predicting upcoming load peak values based on historical data. The proposed hybrid system includes solar photovoltaic (SPV) system, wind turbine (WT) system, converter, battery storage system (BSS), gas generator (GasGen), fuel cell (FC), fuel‐fired boiler, and resistive boiler. Unlike previous studies, electricity price growth and SPV degradation rates are considered in this study. The grid‐connected system has also been compared to the stand‐alone system to understand grid connection impacts on the optimization results. Environmental analysis has been performed to analyze the greenhouse gas emissions of each system. The effects of growth rates in thermal and electric loads and electricity price are comprehensively investigated. Neglecting load growth rates affected the financial results severely. In this condition, the NPC and COE are achieved −11 383.4 US$ and −0.02376 US$/kWh. Results indicate that the combination of WT system (15 kW), converter (10 kW), resistive, and fuel‐fired (10 kW) boilers is the most economical configuration in grid‐connected mode. The WT system plays an essential role in the electric power provision and revenues of the hybrid system. The net present cost (NPC) and the cost of energy (COE) for grid‐connected operating mode are achieved −0.0162272 US$/kWh and −5243.956 US$, respectively. For off‐grid operating mode, the NPC and COE are obtained 47 024.19 US$ and 0.1983879 US$/kWh, respectively. Thanks to the feed‐in‐tariff (FiT) policy, the proposed grid‐connected system is more economical and environmentally friendly than the stand‐alone system. In off‐grid operating mode, 63 575.45285 kg CO2 is produced, which is higher than CO2 production in the grid‐connected mode (more than 8262 kg).

BASIC STAGES OF ENERGY DEVELOPMENT PROGRAM IMPLEMENTATION IN THE CHECHEN REPUBLIC

The article discusses the issues of energy complex development of the Chechen Republic, which requires the creation of a stable multi-vector energy that can satisfy the growing needs of the population and economy of the region. The main emphasis is made on the development of the renewable energy sources, which need to be paid close attention, drawing on the experience of other entities and countries developing innovative technologies in this direction. The analysis of the energy development program implementation in the Chechen Republic (2011-2030) over the past eight years has been carried out, which includes four subprograms describing the potential of resources and the prospects for the energy development in the Chechen Republic,. The estimation of power consumption indicators and maximum loads in the Chechen Republic until 2018 and for the long term (“calculated”, “optimistic” and “actual” options) is given. The analysis of the state and potential for the water energy development in the Chechen Republic is carried out. The analysis of natural resources potential of the republic is carried out in order to implement effectively and develop each of the considered renewable energy sources, taking into account the development of modern innovative technologies to reduce electrical energy consumption. The state estimation of the existing integrated power grid of the Chechen Republic is given, where the initial tasks of work coordination to improve the efficiency of the republic’s energy system are outlined. The results of total indicators of electric grid construction and facilities reconstruction for 2011-2019 are derived. Possible directions (calculated and optimistic options) of the electrical energy industry development are considered. In order to develop successfully the energy sector of the Chechen Republic, taking into account the electrical energy load growth, the development of modern program for the of alternative and renewable energy sources development was proposed that will allow to create additional electrical energy sources in combination with traditional ones. At the same time, the implementation of fundamental and applied research in the field of renewable energy was proposed.

Evaluation of DC Power Quality Based on Empirical Mode Decomposition and One-Dimensional Convolutional Neural Network

With the rise in the use of DC distributed energy resources and the growth of DC electricity load, the difficulty in improving DC power quality has become an important research direction. The research on DC power quality has an important impact on the development of DC power distribution theory and technology. In this paper, an evaluation method that combines empirical mode decomposition (EMD) with a one-dimensional convolutional neural network (1D-CNN) of DC power quality is proposed. As a method of data preprocessing, EMD decomposes the original electrical signal into several intrinsic mode functions (IMFs). Then, the 1-D CNN with a residual module is used to train the data obtained from EMD and conducts a comprehensive evaluation with different levels. In addition, the proposed network was compared with other state-of-the-art deep neural networks, and the experiment proved its effectiveness. Finally, an example analysis is carried out with the data provided by the Gree Photovoltaic Direct-driven Inverter Multi VRF (variable refrigerant flow) System to show the validity of the proposed method for evaluating DC power quality in a real case.

Rapid modelling for flexible DC distribution network considering droop control

With the growth of DC electricity load, the difficulty to improve the power quality, and the increasing penetration of renewable power, flexible DC distribution network, which contains complex renewable energy generation equipment and a large number of power electronic converters, become an important research direction. The modelling of the DC distribution network is an essential step for the research on the coordination control. However, the traditional modelling will be a burden for simulation software. This article models all electrical devices as equivalent power sources based on the proportional–integral control and the power–voltage curve, ignoring the complex internal control processes. Based on the simplified models of power, load, DC/DC converters, and AC/DC converters considering droop control, a simplified model of a multi-terminal flexible DC distribution network is derived. Taking the impact of droop control into account, the simulation of DC distribution power flow under the different distribution of generation and load is done. Results show that the simplified model of DC distribution network with droop control can accurately and rapidly simulate the transient process and steady states of the testing network.

The impact of quick charge on power quality of high-voltage grid

With the continuous development of electric vehicles, a large number of electric vehicles have connected to the grid. This impacts the security and economic operation of power systems deeply. When large-scale electric vehicles are charging, it will bring the problem of electricity load growth and cause the peak-valley difference of power grid. The paper analyzes the impact of electric vehicles quick charge on power quality. According to Monte Carlo method, the daily load curve of quick charging mode in Beijing in 2030 is set up. Newton Raphson method and forward-backward substitution method are used to analyze the voltage deviation and power loss of each node in the typical power system.

Study on power grid characteristics in summer based on Linear regression analysis

The correlation analysis of power load and temperature is the precondition and foundation for accurate load prediction, and a great deal of research has been made. This paper constructed the linear correlation model between temperature and power load, then the correlation of fault maintenance work orders with the power load is researched. Data details of Jiangxi province in 2017 summer such as temperature, power load, fault maintenance work orders were adopted in this paper to develop data analysis and mining. Linear regression models established in this paper will promote electricity load growth forecast, fault repair work order review, distribution network operation weakness analysis and other work to further deepen the refinement.

Optimal placement and sizing of distributed generators for voltage-dependent load model in radial distribution system

The power demand is expanding consistently, which results in the increment of power losses and dropped voltage of the distribution system. Integrating distributed generation (DG) substantially reduces the power loss and increases the voltage profile. In order to get maximum compensation from DG, it ought to be coordinated with optimal placement and sizing. In this paper, an extensive investigation is exhibited for the optimal placement and sizing of different types of one and multiple DGs with existing and increased loads. Electrical load growth is modelled for the base year and next three years with the predetermined load growth. In practice, the distribution system has different types of consumers, assuming constant power load model will lead to inappropriate results. Thus, five different types of load models such as constant, residential, industrial, commercial and mixed loads are considered. Three distinct sorts of DGs were chosen for this study, that is, active, reactive and combination of active–reactive power DG. The proposed study has been applied to the IEEE 33 radial distribution system with basic particle swarm optimization (PSO) algorithm. The results reveal that combination of active–reactive power DG is giving better results for power loss reduction and voltage profile improvement, compared to the other DG types.

Upcoming Challenges of Future Electric Power Systems: Sustainability and Resiliency

Going back and taking a quick glance at the history of developed countries prove that prosperity of any society is tightly intertwined with resiliency and sustainability of its preliminary infrastructures. Surely, in modern societies, electricity is among the most important infrastructures whose resiliency and sustainability is a key driving force toward development of the society. This is verified by the fact that, since the industrial revolution, per capita electricity consumption has taken as a key index showing the level of economic development and standard of living in a country. This paper focuses on the concept of resiliency and sustainability of electric power systems. The paper, initially, introduces the concept and evaluation procedure of power systems resiliency. Then, it strives to introduce the most challenging issues faced by resilient and sustainable power grids. The challenging issues are electricity load growth, energy crisis, environmental emissions and climate changes, unexpected events, aging infrastructures, and cyber challenges. Then, the most effective solutions proposed by power industry scientists and engineers are discussed. The solutions are asset management, renewable energy resources, demand response, controlled islanding and micro grids, and automation, self-healing , and monitoring systems. Finally, a typical sustainable and resilient power system is described.

Research on Sitting Transformer Substations in Rural Areas Based on Improved Genetic Algorithm

The process of urbanization, Beijing faces a number of environmental problems. Especially in the last few years, there has been constantly sustained fog and haze, which makes the implementation of electric heating in rural areas gradually on the agenda. After the implementation of electric heating, the irrationality of the regional power grid layout will be further amplified. With the rapid growth of electricity load in the planning area, the requirement of the power supply grid reliability and power quality is also increasing. Therefore, on the basis of power load forecasting in consideration of the the electric heating, and based on the particularity of rural power network, we achieve the Huairou District substation site with the use of improved genetic algorithm. The results can provide reference for the selection of substation of the whole Beijing rural area.

Comprehensive structure of domiciliary energy awareness and consumption in Mumbai – mega city of Asia

This article explores the pattern of electricity consumption in households of Mumbai, the economic capital of India. It presents the results of a survey questionnaire distributed to more than 550 households in Mumbai sphere, for investigating the level of awareness towards usage of electricity. The research is a survey model with cluster approach to describe the current status of energy awareness of each home cluster in Mumbai. It measures the energy consumption recording approach, basic energy knowledge, energy-saving elasticity, usage aspects about home appliances of Mumbaikars. It concludes by providing commendations for how to improve efforts to promote energy conservation and reduce electricity load growth in Mumbai and beyond.

Extensible Electricity System Model for High Penetration Rate Renewable Integration Impact Analysis

AbstractA simple yet extensible electrical system model, suitable for studying the effects of renewable energy integration, is presented. The model uses publically available historical data to create a representative sample time-series of system loads. Historical conditions are scaled to future target years in accordance with projected system-wide electrical load growth. Renewable energy generation is evaluated regionally and subregionally from coincident climatic conditions, combined with regionally appropriate generator transform functions. Renewable energy generation is scaled to target years based on legislated requirements or projected growth. Future dispatchable generation requirements and conditions are developed as the difference between the projected load and projected renewable energy deployment. A case study conducted in the eastern Canadian province of Nova Scotia is presented. Legislated renewable energy targets will significantly increase the ramp rates required of dispatchable generation.