Improve Grid Reliability Research Articles

A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach

With the modern advanced information and communication technologies in smart grid systems, demand response (DR) has become an effective method for improving grid reliability and reducing energy costs due to the ability to react quickly to supply-demand mismatches by adjusting flexible loads on the demand side. This paper proposes a dynamic pricing DR algorithm for energy management in a hierarchical electricity market that considers both service provider’s (SP) profit and customers’ (CUs) costs. Reinforcement learning (RL) is used to illustrate the hierarchical decision-making framework, in which the dynamic pricing problem is formulated as a discrete finite Markov decision process (MDP), and Q-learning is adopted to solve this decision-making problem. Using RL, the SP can adaptively decide the retail electricity price during the on-line learning process where the uncertainty of CUs’ load demand profiles and the flexibility of wholesale electricity prices are addressed. Simulation results show that this proposed DR algorithm, can promote SP profitability, reduce energy costs for CUs, balance energy supply and demand in the electricity market, and improve the reliability of electric power systems, which can be regarded as a win-win strategy for both SP and CUs.

Coordinated Control of Wind Turbine and Energy Storage System for Reducing Wind Power Fluctuation

This paper proposes a method for the coordinated control of a wind turbine and an energy storage system (ESS). Because wind power (WP) is highly dependent on wind speed, which is variable, severe stability problems can be caused in power systems, especially when the WP has a high penetration level. To solve this problem, many power generation corporations or grid operators have begun using ESSs. An ESS has very quick response and good performance for reducing the impact of WP fluctuation; however, its installation cost is high. Therefore, it is important to design the control algorithm by considering both the ESS capacity and WP fluctuation. Thus, we propose a control algorithm to mitigate the WP fluctuation by using the coordinated control between the wind turbine and the ESS by considering the ESS capacity and the WP fluctuation. Using de-loaded control, according to the WP fluctuation and ESS capacity, we can expand the ESS lifespan and improve grid reliability by avoiding the extreme value of state of charge (SoC) (i.e., 0 or 1 pu). The effectiveness of the proposed method was validated via MATLAB/Simulink by considering a small power system that includes both a wind turbine generator and conventional generators that react to system frequency deviation. We found that the proposed method has better performance in SoC management, thereby improving the frequency regulation by mitigating the impact of the WP fluctuation on the small power system.

Co‐simulation platform for integrated real‐time power system emulation and wide area communication

Phasor measurement units (PMUs) are increasingly being deployed in electric power systems in an attempt to improve grid reliability and make the grid smarter through real-time wide area situational awareness, monitoring, protection and control applications. PMU-based applications require communication networks in the transmission of synchrophasor measurements from the substations to the control centres. However, the quality-of-service of these synchrophasor measurements are not guaranteed when transmitted over a global wide area network especially in the presence of non-deterministic communication network conditions. This study presents the design, development, and integration of an IEEE Std. C37.118-based co-simulation platform comprising of power system hardware-in-the-loop simulations using the real-time digital simulator interfaced to a communication network. The impact of adverse communication network conditions such as latency, packet losses, and corruption on the exchange of data using the co-simulation platform and their impact on a centralised wide area monitoring, protection, and control (WAMPAC) system was investigated with software-in-the-loop simulations. Moreover, the maximum allowable adverse communication conditions are quantified with respect to the WAMPAC applications during emergency conditions.

Synchrophasor Technology and the DOE: Exciting Opportunities Lie Ahead in Development and Deployment

synchrophasor technology has grown from a handful of phasor measurement units (PMUs) in the U.S. Pacific Northwest to a continental network of almost 2,000 PMUs in the past decade, which has helped to improve reliability of the North American electric bulk power grid. This progress is due in large part to research and deployment investments that the U.S. Department of Energy (DOE) has been making since the late 1990s to accelerate the development, adoption, and maturity of this valuable technology. The DOE?s early vision was that better real-time tools could improve grid reliability and prevent blackouts; today, the entire industry recognizes that synchrophasor technology can improve grid planning and investment decisions, enhance operational reliability, facilitate renewables integration, and reduce many operating and asset costs.

No Inverter Left Behind: Protection, Controls, and Testing for High Penetrations of PV Inverters on Distribution Systems

The increased penetration of distributed energy resources (DERs) and interest in improved grid reliability, power quality, and resiliency have changed the characteristics of distribution systems. Inverter-based renewable energy sources, such as photovoltaic (PV) plants, are regarded as the fastest-growing and most crucial technologies in the proliferation of DERs on distribution systems. Many North American utilities have already begun experiencing high penetration of distributed (rooftop) and large-scale centralized PV systems on radial distribution feeders. In many areas?especially between 11 a.m. and 2 p.m.?PV generation can surpass feeder loading, causing reverse power flow and voltage rise toward the end of feeders. Bidirectional power flows, drastic changes in voltage profiles, and events with fast dynamics are becoming more common in today?s distribution systems, bringing complex planning and operational impacts. Understanding these issues requires a deep knowledge of distribution system dynamic behavior supported by detailed engineering studies and sophisticated testing methods.

When the Lights Went Out (Nye, D.; 2010) [Book Review

David Nye's newest book, When the Lights Went Out, is an examination of how the role of blackouts in America has evolved from a minor inconvenience to a potential terrorist plot. He contends that blackouts are a "break in the flow of social time" that reveal fundamental truths about the socioeconomic climate and the role of electricity in our lives. However, his concluding chapter on voluntary "greenouts" feels half-hearted without a discussion of technology-focused initiatives such as smart grid to improve grid reliability and encourage efficiency.

Application of Model Predictive Control for Active Load Management in a Distributed Power System With High Wind Penetration

This paper introduces an experimental platform (SYSLAB) for the research on advanced control and power system communication in distributed power systems and one of its components-an intelligent office building (PowerFlexHouse), which is used to investigate the technical potential for active load management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching of demand and supply can be achieved. With this demand side control study, it is expected that MPC strategy for active load management can dramatically raise energy efficiency and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.

Model Predictive Controller Design for a Load Management Research Facility in a Distributed Power System

This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system with a high penetration of renewable energy. A description of the facility based on a distributed power system (SYSLAB) is followed by a discussion of the software platform on which building controllers can be executed. Finally, this paper shows how to design a thermal model predictive controller for the power consumption prediction in this distributed power system. The control of the PowerFlexHouse allows studies to be performed on the reaction of this intelligent house to a hybrid power grid. With this demand side control study, we hope we can not only dramatically improve grid reliability, but also raise energy efficiencies and reduce power cost for users.

Strategies to meet grid challenges for safety and reliability

Interconnected and integrated electrical power systems, by their very dynamic nature are complex. These multifaceted systems are subject to a host of challenges (e.g. aging infrastructure, distributed resources, reliability coordination). Recent worldwide events have demonstrated that it is time to re-examine traditional planning, operating, system design, and protection and control application, coordination, and setting criteria, to identify and implement solutions and tools. This article describes the strategies to meet grid challenges in providing reliable power delivery. Solutions are offered through applications of modern technology, advanced feedback control schemes using wide area measurements, wide-area visualisation techniques, and intelligent operational tools using IEC-61850 and information semantics to improve grid reliability under complicated power system conditions. The goal is to provide a vision for a comprehensive and systematic approach to meeting the grid safety and reliability management challenges through new information services.