Search

India’s plan for electric vehicle (EV) only sales by 2030, which translates to over 206 million EVs, represent energy and power system challenges. While facing intensified renewable integration and continued grid reliability issues, EVs’ new demand for power will invariably further strain the power grid. These challenges represent an opportunity for India’s goal to reduce greenhouse gas (GHG) emission intensity by 30–35% by 2030 relative to 2005 levels. The electrification of transportation sector represents opportunities for (1) new markets; (2) reduced oil imports; (3) reduced vehicular GHG emissions and air quality improvements, and (4) axiomatic new revenue to distressed electric grid distribution companies (DISCOM). Toward a strategic roadmap to unlock these opportunities, this study proposes macro-level methodologies to assess the grid impacts from EV charging and flexibility using the projections based on historical trends in vehicle sales and driving patterns. The results form the preliminary analysis show new annual revenue opportunities of at least $36 billion for DISCOMs, cost savings of $70 billion from oil imports, and grid impacts that can be mitigated by flexibility services. The policy-makers and grid operators can use the results to optimally plan and operate the energy and power needed for the EVs and develop spatially and temporally flexible EV charging infrastructure.

Increases in peak electricity demands and the growing use of renewable energy --- with associated intermittency and variable output --- present new challenges to electricity service providers (ESPs). ESPs employ demand charges, variable tariffs and demand response (DR) programs to influence the consumption behavior of consumers to partially mitigate these challenges. Due to their high load and potential flexibility, supercomputing centers (SCs) are increasingly gaining importance in the grid. This paper presents a qualitative study of service contracts between ESPs and SCs in the United States and Europe. From this we extract a contract typology used to understand how, and to what extent, variable tariffs, DR programs, and demand charges are imposed on SCs. Further, we highlight the actions taken by SCs in response to these contractual elements. Finally, we present perspectives on grid integration of SCs to enhance their collaboration with their ESPs to benefit supply stability and resilience.

Author(s): Yin, Rongxin; Ghatikar, Girish; Piette, Mary | Abstract: This report describes research to characterize the status of, and trends in, big-data analytics for the electricity grid. The research focused on 1) identifying power-grid big-data sources, types, and characteristics; and 2) characterizing big-data architecture, analytic methods, technology applications, and challenges. The first part of this report describes the main sources and characteristics of big data for the smart grid and comprehensively reviews big-data architecture, technologies, and applications in the power sector. The second part of this report presents case studies of big data applications in the power industry: (1) a smart-meter data and predictive analytics method for demand response (DR), (2) synchrophasor data analytics for the distribution grid, and (3) utility data for peak-demand management. For the predictive analytics case study, smart-meter-data-driven and physical models were developed to predict the potential kilowatt (kW) capacity reduction from DR. The DR estimation framework that was developed works for both small and large-scale customers. The synchrophasor case study demonstrates use of an algorithm applied to time-series data to detect events that appear as significant changes, known as “edges,” in voltage magnitude measurements. The synchrophasor case study also introduces an approach for clustering sets of events to reveal unique features that distinguish them (e.g., distinguishing capacitor bank switching from transformer tap changes). The peak-demand management case study describes the use of the data analytics to enable DR programs to limit forecasted peak demand, resulting in cost savings to the utility. The findings from the research described in this report support identification of opportunities and technologies for big-data and analytics applications for demand-side management in the power sector as well as other approaches to modernizing the electricity grid.

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side Distributed Energy Resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. This paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). The results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.

This study addresses the role of Smart microgrids in shaping a “3.0 Smart Grid” to anchor Smart city development. The paper examines how “advanced or Smart microgrids” could contribute to developing an interactive, flexible, and innovative grid in India—one that would use information and communications technologies to increase the independence, flexibility, and intelligence for optimization of energy use and management within local energy networks and to cost-effectively integrate local energy resources into the Smart Grid. In this regard, the paper discusses integrating Smart microgrids with distribution utility “Advanced Distribution Management Systems,” enabling “dynamic” microgrids that interact with distribution networks according to locally based Smart delivery architecture, with a view to harnessing cost-effectively the benefits of distributed resources for customers, the community, and the macrogrid. The paper also focuses on developing Smart microgrid “Infrastructure as a Service Platform” for resource-efficient community development, where microgrids manage and optimize local energy across multiple end-use sectors (power, transportation, water, waste, buildings, etc.). By leveraging data sets that span diverse facilities, systems, and purposes, Smart microgrids could interlink and optimize energy-using functions of diverse infrastructure systems and the built environment within cities. As part of this discussion, the paper will explore technical and regulatory innovations that could spur investment in advanced microgrids and the development of a 3.0 Smart Grid to help achieve India’s Smart City policy objectives.

Electric vehicles (EV) represent a large market opportunity to address macro- and micro-level carbon emissions, electric grid integration, and technological advances. Studies forecast that by 2040, 25% of the global car fleet will be EVs, leading to large carbon reduction in cities. India’s National Electric Mobility Mission Plan plans to deploy six-to-seven million hybrid and battery electric EVs by 2020. This significant challenge to accelerate deployment of EVs in India’s nascent market requires an understanding of global EV deployment practices and their impacts on the electric grid—primarily the distribution system with last-mile connectivity to the consumers. This study provides a contextual overview of battery-based EV (BEV) global deployment practices and unravels their impacts on the Delhi’s distribution grid. The study reviewed global practices for incentives, technologies, charging infrastructure, and demonstrations to contextually recommend BEV adoption strategies in India. The study conducted a limited and preliminary case study for impacts on Delhi’s power systems. Recommendations are provided to accelerate BEV adoption, consumer engagement, and integrated electric grid for the nascent transportation eco-system in India.

Some of the largest supercomputing centers (SCs) in the United States are developing new relationships with their electricity service providers (ESPs). These relationships, similar to other commercial and industrial partnerships, are driven by a mutual interest to reduce energy costs and improve electrical grid reliability. While SCs are concerned about the quality, cost, environmental impact, and availability of electricity, ESPs are concerned about electrical grid reliability, particularly in terms of energy consumption, peak power demands, and power fluctuations. The power demand for SCs can be 20 MW or more – the theoretical peak power requirements are greater than 45 MW – and recurring intra-hour variability can exceed 8 MW. As a result of this, ESPs may request large SCs to engage in demand response and grid integration.

In recent years, demand response and load control automation has gained increased attention from regulators, system operators, utilities, market aggregators, and product vendors. It has become a cost-effective demand-side alternative to traditional supply-side generation technologies to balance the power grid, enable grid integration of renewable energy, and meet growing demands for electricity. There are several factors that have played a role in the development of demand response programs. Existing research are however limited on reviewing in a systematic approach how these factors work together to drive this development. This paper makes an attempt to fill this gap. It provides a comprehensive overview on how policy and regulations, electricity market reform, and technological advancement in the US and other countries have worked for demand response to become a viable demand-side resource to address the energy and environmental challenges. The paper also offers specific recommendations on actions needed to capture untapped demand response potentials in countries that have developed active demand response programs as well as countries that plan to pursue demand response.

In recent years, extreme weather events have severely affected the performance of the electric grid. Very large-scale events (VLSE) with potentially catastrophic impacts on the grid pose more than an inconvenience in today's electricity-driven lifestyle, and the frequency and severity of such events may continue to increase as a consequence of global climate change. This article summarizes the state of the art in leveraging distributed resources to improve resilience of the electric grid. It also highlights the technical questions that need to be addressed through additional research and development if the value of distributed resources is to be maximized. Published in "Power and Energy Magazine", Volume: 12, Issue: 5

This chapter provides a basic and contextual representation of the Internet of Things (IoT) and Smart Grid systems integration requirements and why the IoTs must leverage data standards to effectively address the unique challenges faced by the current and next‐generation grid. The IoTs that support Smart Grid must achieve end‐to‐end interoperability and security. When systems with diverse characteristics interact within the Smart Grid, the IoTs must possess basic ability to process application‐level messages. The Internet‐enabled network of connected devices supports Smart Grid applications to either improve existing practices or offer emerging technologies and services for the Smart Grid. Interoperability standards are key for “seamless communications” and “ubiquity” of IoT objects. The application domain standards for IoT data communications have the potential to address the diversity in distributed energy resources (DER), distributed generation (DG), distribution systems, and supporting markets and operations for electricity consumers.

After almost 70-years after independence in 1947, India stands at the deterministic crossroads of economic growth and energy needs for over a billion people, while facing challenges to lower carbon emissions and to improve energy security. India's transportation sector growth is one of the major contributors of deteriorating air quality in the urban cities, accounting for 30% of the total fine particulate matter (PM 2.5 ) emissions. India is taking significant policy initiatives to leapfrog and transform electric vehicle (EV) adoption to embrace a tryst with electric transportation. India's National Electricity Mobility Mission (NEMM) Plan 2020 outlines an ambitious target to deploy six to seven million hybrid and EVs. Through stakeholder feedback and qualitative and quantitative analysis, this paper reviews goals and objectives of India's policies, their associated challenges experienced by the Indian ministries, and suggests the action plan, which is unique to the Indian context, to accelerate EVs and EV charging infrastructure, and technology development and deployment to meet the NEMM targets. This first-of-its-kind analyses for India can accelerate EV adoption, open innovation opportunities for both transportation and electric industry, and support energy security and improved urban air-quality objectives.

Global data center energy consumption is growing rapidly. In India, information technology industry growth, fossil-fuel generation, and rising energy prices add significant operational costs and carbon emissions from energy-intensive data centers. Adoption of energy-efficient practices can improve the global competitiveness and sustainability of data centers in India. Previous studies have concluded that advancement of energy efficiency standards through policy and regulatory mechanisms is the fastest path to accelerate the adoption of energy-efficient practices in the Indian data centers. In this study, we reviewed data center energy efficiency practices in the United States, Europe, and Asia. Using evaluation metrics, we identified an initial set of energy efficiency standards applicable to the Indian context using the existing policy mechanisms. These preliminary findings support next steps to recommend energy efficiency standards and inform policy makers on strategies to adopt energy-efficient technologies and practices in Indian data centers.

Over the last decade, advancements in information technology, communications, and controls drove investments in infrastructures to enable smart grids worldwide. More recently, growing integration of renewable generation in electricity grids around the world presented issues such as unplanned forecast errors, intrahour variability, over generation, and steep ramping of renewable resources. In this chapter, we provide a building-centric view of the smart grid, including descriptions of demand-side activities and their impact, how to facilitate the growing need for flexibility of demand-side resources, and the vision of multiple domains of timescales for which buildings can transact with electricity grid signals. We also give examples of how these concepts have been implemented in buildings and projects around the United States.

Smart Grid investments and research promise significant benefits to both customers and the grid. One major benefit is data and communications that enable customer-side resources to participate in electricity programs—i.e., transact with the electric grid. The U.S. Smart Grid activities and investments, which account for nearly three billion dollars in publicly documented expenses, build on interoperability standards activity. Standards interoperability for grid transactions can be viewed from two key interfaces—between (1) Smart Grid domain interfaces, and (2) customer-side resources and the electric grid. Conformance testing and certification is key to ensuring that standards are interoperable and secure. This paper describes the conformance development and certification process for a key communications standard—Open Automated Demand Response (OpenADR)—as an interface between customers' systems and electricity service providers, to enable demand response and price transactions. Through this process, we describe the benefits of conformance to support low-cost automated DR (AutoDR) and customer-side transactions within the distribution electric grid. The paper evaluates examples of applications and further developments for emerging transactive energy concepts that can be used to scale existing systems and to leverage the investments and support compliance to any building codes and appliance standards. The conformance process can be the key to realizing interoperability benefits and market acceptance. Conformance is also a key to enabling native DR and price transaction capabilities in customers' systems; a feature that can be replicated for diffusion and can lower DR technology costs by a significant margin.

Replacing the traditional fossil-based electricity generation with clean renewable energy is critical to address carbon emissions and climate change in particular. Denmark has a particularly aggressive strategy for renewable energy generation. By 2020 50% of electricity production is to be wind based and by 2050 the goal is to have an energy production based entirely on renewable energy. Renewable energy such as solar and wind is subject to variations due to changing weather conditions. This requires additional balancing capacity and ancillary services in order to balance the grid for transmission system operators and distribution system operators and balance errors in forecasts made by balance responsible parties. By enabling the demand-side to adapt consumption to match power generation, we can address this in a cost-effective and environmental sound way. In this context, data centers are of special interest as they account for 500 GWh of consumption in Denmark or nearly 2% of the total electricity consumption. This paper performs an analysis on load management capabilities of data centers in Denmark based on the experiences in the U.S. We characterize the load management capabilities of the data centers based on their types, technology, and their application as grid management resources. Further, we identify demand-side entry barriers towards market participation. Our findings suggest that groups of data centers can offer dynamic load flexibility as virtual power plants, and thereby support the evolution of the Danish energy systems towards its 2020 and 2050 goals. Replacing the traditional fossil-based electricity generation with clean renewable energy is critical to address carbon emissions and climate change in particular. Denmark has a particularly aggressive strategy for renewable energy generation. By 2020 50% of electricity production is to be wind based and by 2050 the goal is to have an energy production based entirely on renewable energy. Renewable energy such as solar and wind is subject to variations due to changing weather conditions. This requires additional balancing capacity and ancillary services in order to balance the grid for transmission system operators and distribution system operators and balance errors in forecasts made by balance responsible parties. By enabling the demand-side to adapt consumption to match power generation, we can address this in a cost-effective and environmental sound way. In this context, data centers are of special interest as they account for 500 GWh of consumption in Denmark or nearly 2% of the total electricity consumption. This paper performs an analysis on load management capabilities of data centers in Denmark based on the experiences in the U.S. We characterize the load management capabilities of the data centers based on their types, technology, and their application as grid management resources. Further, we identify demand-side entry barriers towards market participation. Our findings suggest that groups of data centers can offer dynamic load flexibility as virtual power plants, and thereby support the evolution of the Danish energy systems towards its 2020 and 2050 goals.

The Transactional Network Project is a multi-lab activity funded by the US Department of Energy?s Building Technologies Office. The project team included staff from Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The team designed, prototyped and tested a transactional network (TN) platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). PNNL was responsible for the development of the TN platform, with agents for this platform developed by each of the three labs. LBNL contributed applications to measure the whole-building electric load response to various changes in building operations, particularly energy efficiency improvements and demand response events. We also provide a demand response signaling agent and an agent for cost savings analysis. LBNL and PNNL demonstrated actual transactions between packaged rooftop units and the electric grid using the platform and selected agents. This document describes the agents and applications developed by the LBNL team, and associated tests of the applications.

Expanding Buildings-to-Grid (B2G) Objectives in India Girish Ghatikar and Venkata Ganti Lawrence Berkeley National Laboratory Chandrayee Basu University of California Berkeley July 2013 Prepared for: The U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy

Demonstration and Results of Grid Integrated Technologies at the Demand to Grid Laboratory (D2G Lab): Phase I Operations Report Girish Ghatikar, Venkata Ganti, Mary Ann Piette, Janie Page, Sila Kiliccote, Chuck McParland Lawrence Berkeley National Laboratory Dave Watson Slice Energy, Inc. July 2013

LBNL-XXXXX Best Practices Guide for High- Performance Indian Office Buildings Singh, Reshma; Sartor, Dale; and Ghatikar, Girish Environmental Energy Technologies Division April 2013

LBNL-XXXXX Miscellaneous and Electronic Loads Energy Efficiency Opportunities for Commercial Buildings: A Collaborative Study by the United States and India Girish Ghatikar, Iris Cheung, and Steven Lanzisera Lawrence Berkeley National Laboratory Bob Wardell, Manoj Deshpande and Jayraj Ugarkar Infosys Technologies Limited Environmental Energy Technologies Division April 2013

Assessing the Control Systems Capacity for Demand Response in California Industries Girish Ghatikar, Aimee McKane, Sasank Goli, Peter Therkelsen, Daniel Olsen Lawrence Berkeley National Laboratory January 2012

Advances in communications and control technology, the strengthening of the Internet, and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto‐DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components, systems, end‐uses and whole building energy performance metrics. The paper presents a framework about when energy is used, levels of services by energy using systems, granularity of control, and speed of telemetry. DR, when defined as a discrete event, requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.

This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

Demand Response and Open Automated Demand Response Opportunities for Data Centers Girish Ghatikar, Mary Ann Piette, Sydny Fujita, Aimee McKane, Junqiao Han Dudley, and Anthony Radspieler Lawrence Berkeley National Laboratory K C Mares Megawatt Consulting Dave Shroyer SCG January 2010 The work described in this report was coordinated by the Demand Response Research Center and funded by the California Energy Commission (Energy Commission), Public Interest Energy Research (PIER) Program, under Work for Others Contract No. 500-03-026, Pacific Gas and Electric Company (PG&E) under Work for Others Contract No PGZ0803 and by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

LBNL-2899E ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Building Energy Information Systems: State of the Technology and User Case Studies Jessica Granderson, Mary Ann Piette, Girish Ghatikar, Phillip Price Environmental Energy Technologies Division November 2009