Solar Engineering Of Thermal Processes

Annual Energy Outlook

ライブラリー Annual Energy Outlook 2000

Microgrids energy management systems: A critical review on methods, solutions, and prospects

Energy sustainability and environmental preservation have become worldwide concerns with the many manifestations of climate change and the continually increasing demand for energy. As cities and nations become more technologically advanced, electricity consumption rises to levels that may no longer be manageable if left unattended. The Smart Grid offers an answer to the shift to more sustainable technologies such as distributed generation and microgrids. A general public awareness and adequate attention from potential researchers and policy makers is crucial. This paper presents an overview of the Smart Grid with its general features, functionalities and characteristics. It presents the Smart Grid fundamental and related technologies and have identified the research activities, challenges and issues. It demonstrates how these technologies have shaped the modern electricity grid and continued to evolve and strengthen its role in the better alignment of energy demand and supply. Smart Grid implementation and practices in various locations are also unveiled. Concrete energy policies facilitate Smart Grid initiatives across the nations. Interestingly, Smart Grid practices in different regions barely indicate competition but rather an unbordered community of similar aspirations and shared lessons.

A review of the development of Smart Grid technologies

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

We utilize a for-profit aggregator-based residential demand response (DR) approach to the smart grid resource allocation problem. The aggregator entity, using a given set of schedulable residential customer assets (e.g., smart appliances), must set a schedule to optimize for a given objective. Here, we consider optimizing for the profit of the aggregator. To encourage customer participation in the residential DR program, a new pricing structure named customer incentive pricing (CIP) is proposed. The aggregator profit is optimized using a proposed heuristic framework, implemented in the form of a genetic algorithm, that must determine a schedule of customer assets and the CIP. To validate our heuristic framework, we simulate the optimization of a large-scale system consisting of 5555 residential customer households and 56 642 schedulable assets using real-pricing data over a period of 24-h. We show that by optimizing purely for economic reasons, the aggregator can enact a beneficial change on the load profile of the overall power system.

Heuristic Optimization for an Aggregator-Based Resource Allocation in the Smart Grid

Real-time pricing (RTP) is a utility-offered dynamic pricing program to incentivize customers to make changes in their energy usage. A home energy management system (HEMS) automates the energy usage in a smart home in response to utility pricing signals. We present three new HEMS techniques—one myopic approach and two non-myopic partially observable Markov decision process (POMDP) approaches—for minimizing the household electricity bill in such a RTP market. In a simulation study, we compare the performance of the new HEMS methods with a mathematical lower bound and the status quo. We show that the non-myopic POMDP approach can provide a 10%–30% saving over the status quo.

A Partially Observable Markov Decision Process Approach to Residential Home Energy Management

Energy management of remote microgrids considering battery lifetime

This paper describes the integrated grid modeling system (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing platforms to offer unprecedented resolution from independent system operator (ISO) markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed ISO markets and automatic generator control-level reserve deployment. IGMS uses a new message passing interface-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate open-source tools for wholesale markets, bulk ac power flow, and full-featured distribution systems including physics-based end-use and distributed generation models (many instances of GridLAB-D). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar photovoltaic and price responsive load scenarios.

Timothy M. Hansen

Papers

Virtual Inertia: Current Trends and Future Directions

Heuristic Optimization for an Aggregator-Based Resource Allocation in the Smart Grid

A Partially Observable Markov Decision Process Approach to Residential Home Energy Management

Energy management of remote microgrids considering battery lifetime

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System