Distributional Analysis for Model Predictive Deferrable Load Control

Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In this paper, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance.Comment: 12 pages, technical report for CDC 201

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

Architecture for intelligent power systems management, optimization, and storage.

The management of power and the optimization of systems generating and using power are critical technologies. A new architecture is developed to advance the current state of the art by providing an intelligent and autonomous solution for power systems management. The architecture is two-layered and implements a decentralized approach by defining software objects, similar to software agents, which provide for local optimization of power devices such as power generating, storage, and load devices. These software device objects also provide an interface to a higher level of optimization. This higher level of optimization implements the second layer in a centralized approach by coordinating the individual software device objects with an intelligent expert system thus resulting in architecture for total system power management. In this way, the architecture acquires the benefits of both the decentralized and centralized approaches. The architecture is designed to be portable, scalable, simple, and autonomous, with respect to devices and missions. Metrics for evaluating these characteristics are also defined. Decentralization achieves scalability and simplicity through modularization using software device objects that can be added and deleted as modules based on the devices of the power system are being optimized. Centralization coordinates these software device objects to bring autonomy and intelligence of the whole power system and mission to the architecture. The centralization approach is generic since it always coordinates software device objects; therefore it becomes another modular component of the architecture. Three example implementations illustrate the evolution of this power management system architecture. The first implementation is a coal-fired power generating station that utilized a neural network optimization for the reduction of nitrogen oxide emissions. This illustrates the limitations of this type of black-box optimization and serves as a motivation for developing a more functional architecture. The second implementation is of a hydro-generating power station where a white-box, software agent approach illustrates some of the benefits and provides initial justification of moving towards the proposed architecture. The third implementation applies the architecture to a vehicle to grid application where the previous hydro-generating application is ported and a new hybrid vehicle application is defined. This demonstrates portability and scalability in the architecture, and linking these two applications demonstrates autonomy. The simplicity of building this application is also evaluated

Unlocking the Potential of Flexible Energy Resources to Help Balance the Power Grid

Flexible energy resources can help balance the power grid by providing different types of ancillary services. However, the balancing potential of most types of resources is restricted by physical constraints such as the size of their energy buffer, limits on power-ramp rates, or control delays. Using the example of Secondary Frequency Regulation, this paper shows how the flexibility of various resources can be exploited more efficiently by considering multiple resources with complementary physical properties and controlling them in a coordinated way. To this end, optimal adjustable control policies are computed based on robust optimization. Our problem formulation takes into account power ramp-rate constraints explicitly, and accurately models the different timescales and lead times of the energy and reserve markets. Simulations demonstrate that aggregations of select resources can offer significantly more regulation capacity than the resources could provide individually.Comment: arXiv admin note: text overlap with arXiv:1804.0389

Frequency control studies: A review of power system, conventional and renewable generation unit modeling

Over the last decades, renewable energy sources have increased considerably their generation share in power systems. As a consequence, in terms of frequency deviations, both grid reliability and stability have raised interest. By considering the absence of a consensual set of models for frequency control analysis, both for the different generation units (conventional and renewables) and the power system itself, this paper provides extensive and significant information focused on the models and parameters for studies about frequency control and grid stability. An extensive analysis of supply-side and power system modeling for frequency stability studies over the last decade is presented and reviewed. Parameters commonly used and assumed in the specific literature for such simulations are also given and compared. Modeling of generation units are described as well, including both conventional and renewable power plants.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper

An insight into the integration of distributed energy resources and energy storage systems with smart distribution networks using demand-side management

Demand-side management (DSM) is a significant component of the smart grid. DSM without sufficient generation capabilities cannot be realized; taking that concern into account, the integration of distributed energy resources (solar, wind, waste-to-energy, EV, or storage systems) has brought effective transformation and challenges to the smart grid. In this review article, it is noted that to overcome these issues, it is crucial to analyze demand-side management from the generation point of view in considering various operational constraints and objectives and identifying multiple factors that affect better planning, scheduling, and management. In this paper, gaps in the research and possible prospects are discussed briefly to provide a proper insight into the current implementation of DSM using distributed energy resources and storage. With the expectation of an increase in the adoption of various types of distributed generation, it is estimated that DSM operations can offer a valuable opportunity for customers and utility aggregators to become active participants in the scheduling, dispatch, and market-oriented trading of energy. This review of DSM will help develop better energy management strategies and reduce system uncertainties, variations, and constraints

Groundwater research and management: integrating science into management decisions. Proceedings of IWMI-ITP-NIH International Workshop on "Creating Synergy Between Groundwater Research and Management in South and Southeast Asia," Roorkee, India, 8-9 February 2005

Groundwater management / Governance / Groundwater development / Artificial recharge / Water quality / Aquifers / Groundwater irrigation / Water balance / Simulation models / Watershed management / Water harvesting / Decision making / South East Asia / Bangladesh / China / India / Nepal / Pakistan / Syria

Control and Optimization of Energy Storage in AC and DC Power Grids

Energy storage attracts attention nowadays due to the critical role it will play in the power generation and transportation sectors. Electric vehicles, as moving energy storage, are going to play a key role in the terrestrial transportation sector and help reduce greenhouse emissions. Bulk hybrid energy storage will play another critical role for feeding the new types of pulsed loads on ship power systems. However, to ensure the successful adoption of energy storage, there is a need to control and optimize the charging/discharging process, taking into consideration the customer preferences and the technical aspects. In this dissertation, novel control and optimization algorithms are developed and presented to address the various challenges that arise with the adoption of energy storage in the electricity and transportation sectors. Different decentralized control algorithms are proposed to manage the charging of a mass number of electric vehicles connected to different points of charging in the power distribution system. The different algorithms successfully satisfy the preferences of the customers without negatively impacting the technical constraints of the power grid. The developed algorithms were experimentally verified at the Energy Systems Research Laboratory at FIU. In addition to the charge control of electric vehicles, the optimal allocation and sizing of commercial parking lots are considered. A bi-layer Pareto multi-objective optimization problem is formulated to optimally allocate and size a commercial parking lot. The optimization formulation tries to maximize the profits of the parking lot investor, as well as minimize the losses and voltage deviations for the distribution system operator. Sensitivity analysis to show the effect of the different objectives on the selection of the optimal size and location is also performed. Furthermore, in this dissertation, energy management strategies of the onboard hybrid energy storage for a medium voltage direct current (MVDC) ship power system are developed. The objectives of the management strategies were to maintain the voltage of the MVDC bus, ensure proper power sharing, and ensure proper use of resources, where supercapacitors are used during the transient periods and batteries are used during the steady state periods. The management strategies were successfully validated through hardware in the loop simulation

Impact of vehicle to grid in the power system dynamic behaviour

This work was supported in part by FCT-Fundação para a Ciência e a Tecnologia de Portugal, under the grant SFRH/BD/47973/2008 and within the framework of the Project "Green Island" with the Reference MIT-PT/SES-GI/0008/2008, by the European Commission within the framework of the European Project MERGE - Mobile Energy Resources in Grids of Electricity, contract nr. 241399 (FP7) and by INESC Porto - Instituto de Engenharia de Sistemas e Computadores do PortoTese de doutoramento. Sistemas Sustentáveis de Energia. Universidade do Porto. Faculdade de Engenharia. 201

Battery Integration to the Power Grid and Frequency Regulation

The growing interest in battery energy storage systems (BESSs) at both small-scale and large-scale levels in power grids highlights their significant roles in future power grids. The future grid in the presence of renewable resources such as hydro-power, wind, and solar energy face two major technical challenges; location of potential renewable sources and uncertainty, which can cause serious issues such as blackouts in power systems. However, in both cases, BESSs is one of the promising solutions. While small-scale battery energy storage systems can decrease the need for long-distance heavy load transportation in the power system, which is one of the primary reasons for the blackouts, large-scale BESSs can provide load frequency control to their fast response. A well-managed large-scale battery integration to the power grid reduces load flow deviation in the tie-lines and frequency oscillations caused by small load disturbances. In general, the battery’s small time-constants, fast response, and high energy density creates a large spectrum of potential applications for BESSs in power systems. This thesis focuses on the battery integration to the power system in both distribution and transmission level to evaluate its potential impact on power grid; then, it focuses on the frequency regulation by taking the advantage of the small-scale and large-scale batteries. The first part of this research investigates the small-scale battery integration to the power system in the distribution level and its potential effects on the transmission level\u27s frequency deviation. It is shown that the higher penetration level of the renewables can cause serious issues such as overvoltage, thermal, and frequency deviation issues in the distribution and transmission levels under current tariffs. The load profile\u27s sensitivity to the battery characteristics and its efficiency, and electricity tariffs are studied. Then, tariff modification as one of the promising tools for load profile adjustment is introduced to modify the customers\u27 load profile and mitigate the frequency deviation. The results under modified tariffs are compared to the frequency control results in a small microgrid using model predictive control. In the second chapter, the effect of those new loads on the power flow and inter-area oscillation modes are studied. Then a servomechanism controller is designed to damp the inter-area oscillations. Considering the small time constant of the large-scale battery, we model a large-scale battery integration to the power system to study the effect of its integration on the power system\u27s stability. Finally, centralized and decentralized hybrid controls are designed on the inverter\u27s firing angle to manage the large-scale battery\u27s active and reactive power to damp the oscillations. Results show a notable improvement on frequency deviations