Modeling of Customer Adoption of Distributed Energy Resources


Book Description

This report describes work completed for the California Energy Commission (CEC) on the continued development and application of the Distributed Energy Resources Customer Adoption Model (DER-CAM). This work was performed at Ernest Orlando Lawrence Berkeley National Laboratory (Berkeley Lab) between July 2000 and June 2001 under the Consortium for Electric Reliability Technology Solutions (CERTS) Distributed Energy Resources Integration (DERI) project. Our research on distributed energy resources (DER) builds on the concept of the microgrid ([mu]Grid), a semiautonomous grouping of electricity-generating sources and end-use sinks that are placed and operated for the benefit of its members. Although a [mu]Grid can operate independent of the macrogrid (the utility power network), the [mu]Grid is usually interconnected, purchasing energy and ancillary services from the macrogrid. Groups of customers can be aggregated into [mu]Grids by pooling their electrical and other loads, and the most cost-effective combination of generation resources for a particular [mu]Grid can be found. In this study, DER-CAM, an economic model of customer DER adoption implemented in the General Algebraic Modeling System (GAMS) optimization software is used, to find the cost-minimizing combination of on-site generation customers (individual businesses and a [mu]Grid) in a specified test year. DER-CAM's objective is to minimize the cost of supplying electricity to a specific customer by optimizing the installation of distributed generation and the self-generation of part or all of its electricity. Currently, the model only considers electrical loads, but combined heat and power (CHP) analysis capability is being developed under the second year of CEC funding. The key accomplishments of this year's work were the acquisition of increasingly accurate data on DER technologies, including the development of methods for forecasting cost reductions for these technologies, and the creation of a credible example California [mu]Grid for use in this study and in future work. The work performed during this year demonstrates the viability of DER-CAM and of our approach to analyzing adoption of DER.




Distributed Energy Resources Customer Adoption Modeling with Combined Heat and Power Applications


Book Description

In this report, an economic model of customer adoption of distributed energy resources (DER) is developed. It covers progress on the DER project for the California Energy Commission (CEC) at Berkeley Lab during the period July 2001 through Dec 2002 in the Consortium for Electric Reliability Technology Solutions (CERTS) Distributed Energy Resources Integration (DERI) project. CERTS has developed a specific paradigm of distributed energy deployment, the CERTS Microgrid (as described in Lasseter et al. 2002). The primary goal of CERTS distributed generation research is to solve the technical problems required to make the CERTS Microgrid a viable technology, and Berkeley Lab's contribution is to direct the technical research proceeding at CERTS partner sites towards the most productive engineering problems. The work reported herein is somewhat more widely applicable, so it will be described within the context of a generic microgrid (mGrid). Current work focuses on the implementation of combined heat and power (CHP) capability. A mGrid as generically defined for this work is a semiautonomous grouping of generating sources and end-use electrical loads and heat sinks that share heat and power. Equipment is clustered and operated for the benefit of its owners. Although it can function independently of the traditional power system, or macrogrid, the mGrid is usually interconnected and exchanges energy and possibly ancillary services with the macrogrid. In contrast to the traditional centralized paradigm, the design, implementation, operation, and expansion of the mGrid is meant to optimize the overall energy system requirements of participating customers rather than the objectives and requirements of the macrogrid.







Distributed Energy Resources in Practice


Book Description

This report describes a Berkeley Lab effort to model the economics and operation of small-scale (




Operation of Distributed Energy Resources in Smart Distribution Networks


Book Description

Operation of Distributed Energy Resources in Smart Distribution Networks defines the barriers and challenges of smart distribution networks, ultimately proposing optimal solutions for addressing them. The book considers their use as an important part of future electrical power systems and their ability to improve the local flexibility and reliability of electrical systems. It carefully defines the concept as a radial network with a cluster of distributed energy generations, various types of loads, and energy storage systems. In addition, the book details how the huge penetration of distributed energy resources and the intermittent nature of renewable generations may cause system problems. Readers will find this to be an important resource that analyzes and introduces the features and problems of smart distribution networks from different aspects. Integrates different types of elements, including electrical vehicles, demand response programs, and various renewable energy sources in distribution networks Proposes optimal operational models for the short-term performance and scheduling of a distribution network Discusses the uncertainties of renewable resources and intermittent load in the decision-making process for distribution networks




CERTS Customer Adoption Model


Book Description

This effort represents a contribution to the wider distributed energy resources (DER) research of the Consortium for Electric Reliability Technology Solutions (CERTS, http://certs.lbl.gov) that is intended to attack and, hopefully, resolve the technical barriers to DER adoption, particularly those that are unlikely to be of high priority to individual equipment vendors. The longer term goal of the Berkeley Lab effort is to guide the wider technical research towards the key technical problems by forecasting some likely patterns of DER adoption. In sharp contrast to traditional electricity utility planning, this work takes a customer-centric approach and focuses on DER adoption decision making at, what we currently think of as, the customer level. This study reports on Berkeley Lab's second year effort (completed in Federal fiscal year 2000, FY00) of a project aimed to anticipate patterns of customer adoption of distributed energy resources (DER). Marnay, et al., 2000 describes the earlier FY99 Berkeley Lab work. The results presented herein are not intended to represent definitive economic analyses of possible DER projects by any means. The paucity of data available and the importance of excluded factors, such as environmental implications, are simply too important to make such an analysis possible at this time. Rather, the work presented represents a demonstration of the current model and an indicator of the potential to conduct more relevant studies in the future.




A Model of U.S. Commercial Distributed Generation Adoption


Book Description

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems over the next two decades. Forecasts of DG adoption published by the Energy Information Administration (EIA) in the Annual Energy Outlook (AEO) are made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. NEMS is also used for estimating the future benefits of Department of Energy research and development used in support of budget requests and management decisionmaking. The NEMS approach to modeling DG has some limitations, including constraints on the amount of DG allowed for retrofits to existing buildings and a small number of possible sizes for each DG technology. An alternative approach called Commercial Sector Model (ComSeM) is developed to improve the way in which DG adoption is modeled. The approach incorporates load shapes for specific end uses in specific building types in specific regions, e.g., cooling in hospitals in Atlanta or space heating in Chicago offices. The Distributed Energy Resources Customer Adoption Model (DER-CAM) uses these load profiles together with input cost and performance DG technology assumptions to model the potential DG adoption for four selected cities and two sizes of five building types in selected forecast years to 2022. The Distributed Energy Resources Market Diffusion Model (DER-MaDiM) is then used to then tailor the DER-CAM results to adoption projections for the entire U.S. commercial sector for all forecast years from 2007-2025. This process is conducted such that the structure of results are consistent with the structure of NEMS, and can be re-injected into NEMS that can then be used to integrate adoption results into a full forecast.




Modelling Distributed Energy Resources in Energy Service Networks


Book Description

The smart-grid concept can mean many things, however there is a consensus that its objective involves seamlessly adopting new technologies to existing infrastructures and maximising the use of resources. Modelling Distributed Energy Resources in Energy Service Networks focuses on modelling two key infrastructures in urban energy systems with embedded technologies. These infrastructures are natural gas and electricity networks and the embedded technologies include cogeneration and electric vehicle devices. The subject is addressed using a holistic modelling framework which serves as a means to an end; this end being to optimise in a coordinated manner the operation of natural gas and electrical infrastructures under the presence of distributed energy resources, thus paving the way in which smart-grids should be managed. The modelling approach developed and presented in this book, under the name 'time coordinated optimal power flow' (TCOPF), functions as a decision maker entity that aggregates and coordinates the available DERs according to multiple criteria such as energy prices and utility conditions. The examples prove the TCOPF acts effectively as an unbiased intermediary entity that manages cost-effective interactions between the connected technologies and the distribution network operators, therefore showcasing an integral approach on how to manage new technologies for the benefit of all stakeholders.




Smart Grid Handbook, 3 Volume Set


Book Description

Comprehensive, cross-disciplinary coverage of Smart Grid issues from global expert researchers and practitioners. This definitive reference meets the need for a large scale, high quality work reference in Smart Grid engineering which is pivotal in the development of a low-carbon energy infrastructure. Including a total of 83 articles across 3 volumes The Smart Grid Handbook is organized in to 6 sections: Vision and Drivers, Transmission, Distribution, Smart Meters and Customers, Information and Communications Technology, and Socio-Economic Issues. Key features: Written by a team representing smart grid R&D, technology deployment, standards, industry practice, and socio-economic aspects. Vision and Drivers covers the vision, definitions, evolution, and global development of the smart grid as well as new technologies and standards. The Transmission section discusses industry practice, operational experience, standards, cyber security, and grid codes. The Distribution section introduces distribution systems and the system configurations in different countries and different load areas served by the grid. The Smart Meters and Customers section assesses how smart meters enable the customers to interact with the power grid. Socio-economic issues and information and communications technology requirements are covered in dedicated articles.The Smart Grid Handbook will meet the need for a high quality reference work to support advanced study and research in the field of electrical power generation, transmission and distribution. It will be an essential reference for regulators and government officials, testing laboratories and certification organizations, and engineers and researchers in Smart Grid-related industries.




Distributed Solar Adoption in Orlando: A Household-Level Model for Distribution Resource Planning


Book Description

Potential for rooftop solar in Florida is massive (47% of retail sales, 3rd overall nationally), yet adoption lags (12th nationally). A 2018 Florida Public Service Commission ruling authorizing solar third-party ownership (leasing) has substantially increased attention on distributed solar in the state. The city of Orlando has committed to a 100% clean-energy target by 2050 and deployment of solar and storage are expected to contribute significantly to reaching the goal. Deployment of customer-adopted solar, unlike utility-procured solar, is uncertain, but known to be spatially correlated with demographic factors and existing adoption. We develop a new method to adapt NREL's dGen model in order to represent building-level agents in adoption forecasts for the Orlando Utility Commission (OUC) service territory. Using the agent-based model we develop projections of solar adoption, subject to scenarios varying future solar costs and valuation, and aggregate adoption predictions by OUC distribution feeder. We find substantial spatial heterogeneity in the projected level of adoption by OUC distribution feeder. For instance, 25% of all projected adoption through 2050 would be concentrated on just 5% of feeders and 88% of projected adoption on 50% of feeders. Because of the uncertainty in adoption, bottoms-up solar adoption forecasting methods at the household-level are integral to long-term resource planning by anticipating system needs as customers increasingly adopt distributed solar, storage, electric vehicles, and other distributed energy resources.