Energy is vital for sustainable development of any nation – be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.

Energy models for demand forecasting—A review

In electrical islands, frequency excursions are sizeable and automatic load shedding is often required in response to disturbances. Moreover, the displacement of conventional generation with wind and solar plants, which usually do not provide inertial response, further weakens these power systems. Fast-acting storage, by injecting power within instants after the loss of a generating unit, can back up conventional generation assets during the activation of their primary reserve. This paper relies on dynamic simulations to study the provision of such a dynamic frequency control support by energy storage systems in the French island of Guadeloupe with large shares of wind or solar generation. The results show that fast-acting storage, by acting as a synthetic inertia, can mitigate the impact of these sources on the dynamic performance of the studied island grid in the case of a major generation outage. The other concerns raised by renewables (e.g., variability, forecast accuracy, low voltage ride-through, etc.) have not been addressed within this project.

Dynamic Frequency Control Support by Energy Storage to Reduce the Impact of Wind and Solar Generation on Isolated Power System's Inertia

Energy consumption forecasting for buildings has immense value in energy efficiency and sustainability research. Accurate energy forecasting models have numerous implications in planning and energy optimization of buildings and campuses. For new buildings, where past recorded data is unavailable, computer simulation methods are used for energy analysis and forecasting future scenarios. However, for existing buildings with historically recorded time series energy data, statistical and machine learning techniques have proved to be more accurate and quick. This study presents a comprehensive review of the existing machine learning techniques for forecasting time series energy consumption. Although the emphasis is given to a single time series data analysis, the review is not just limited to it since energy data is often co-analyzed with other time series variables like outdoor weather and indoor environmental conditions. The nine most popular forecasting techniques that are based on the machine learning platform are analyzed. An in-depth review and analysis of the ‘hybrid model’, that combines two or more forecasting techniques is also presented. The various combinations of the hybrid model are found to be the most effective in time series energy forecasting for building.

A review on time series forecasting techniques for building energy consumption

The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating them as grid following units can lead to frequency instability. Many researchers have pointed towards using inverters with virtual inertia control algorithms so that they appear as synchronous generators to the grid, maintaining and enhancing system stability. This paper presents a literature review of the current state-of-the-art of virtual inertia implementation techniques, and explores potential research directions and challenges. The major virtual inertia topologies are compared and classified. Through literature review and simulations of some selected topologies it has been shown that similar inertial response can be achieved by relating the parameters of these topologies through time constants and inertia constants, although the exact frequency dynamics may vary slightly. The suitability of a topology depends on system control architecture and desired level of detail in replication of the dynamics of synchronous generators. A discussion on the challenges and research directions points out several research needs, especially for systems level integration of virtual inertia systems.

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Virtual Inertia: Current Trends and Future Directions

Continuously expanding deployments of distributed power-generation systems (DPGSs) are transforming the conventional centralized power grid into a mixed distributed electrical network. The modern power grid requires flexible energy utilization but presents challenges in the case of a high penetration degree of renewable energy, among which wind and solar photovoltaics are typical sources. The integration level of the DPGS into the grid plays a critical role in developing sustainable and resilient power systems, especially with highly intermittent renewable energy resources. To address the challenging issues and, more importantly, to leverage the energy generation, stringent demands from both utility operators and consumers have been imposed on the DPGS. Furthermore, as the core of energy conversion, numerous power electronic converters employing advanced control techniques have been developed for the DPGS to consolidate the integration. In light of the above, this paper reviews the power-conversion and control technologies used for DPGSs. The impacts of the DPGS on the distributed grid are also examined, and more importantly, strategies for enhancing the connection and protection of the DPGS are discussed.

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Distributed Power-Generation Systems and Protection

Review of contribution to frequency control through variable speed wind turbine

Based on the boundary characteristic of a dc transmission line, the response of transient harmonic current in the line-commutated converter HVDC transmission system is analyzed under various fault conditions in this paper. A new transient harmonic current protection scheme is proposed. The discrete Fourier transform is used to extract transient harmonic currents at both terminals of the dc transmission line and the type of fault can be identified by the transient harmonic currents. Two main factors including fault resistance and fault location that affect performance of the protection are also discussed in this study. The test system is modeled based on the CIGRE benchmark including distributed parameters of the dc transmission line. Comprehensive test studies show that the performance of the transient harmonic current protection scheme is encouraging. It can not only identify internal faults and external faults correctly and quickly, but also can respond to high ground resistance faults.

A Transient Harmonic Current Protection Scheme for HVDC Transmission Line

The relation between the parameters of dc transmission line and the variation of transient energy has been analyzed under various fault conditions in this paper. According to that, a new transient energy protective scheme is proposed. It is developed based on the distributed parameter line model in which the transient energy distribution over the line can be obtained from the voltage and current measurements at both terminals and the fault can be recognized from the calculated value simply. The test system is modeled based on the CIGRE benchmark and considered the distributed parameters of the dc transmission line. Comprehensive test studies show that the performance of transient energy protection scheme is encouraging. It can not only identify internal fault and external faults correctly and quickly, but can also respond to the high ground resistance fault. Finally, two main factors, including fault resistance and transmission distance, that affect the performance of the protection are also discussed.

A Transient Protection Scheme for HVDC Transmission Line

Distribution networks (DNs) gradually become more active and flexible with the massive integration of renewable resources. The conventional protection methods are unsuitable for the promising active DNs. This paper proposes a protection scheme on the basis of measured impedance, which includes an impedance differential method and an inverse-time low-impedance method. The former approach identifies fault instant and provides time reference for the exchanged data. As primary protection, it is able to clear different types of faults as soon as possible. The latter method operates in an automatic coordination way with inverse-time characteristic. It can be used as backup protection or provide protection for single-end lines alone. Both of the methods are independent of operation modes and are able to clear faults with high sensitivity. The efficiency of the protection scheme is validated by PSCAD/EMTDC.

Tai Nengling

Papers

Review of contribution to frequency control through variable speed wind turbine

A Transient Harmonic Current Protection Scheme for HVDC Transmission Line

A Transient Protection Scheme for HVDC Transmission Line

An Impedance Protection Scheme for Feeders of Active Distribution Networks

Techniques of applying wavelet transform into combined model for short-term load forecasting