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• This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency. • A demand response program integrated with home energy storage systems is presented to optimize energy consumption. • To modify the consumption pattern of household consumers, a real-time pricing algorithm is proposed. • A self-healing system reconfiguration program integrated with distributed energy resources is presented. • Real data of California households are considered to model the home appliances and home energy storage systems. This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency of the Distribution Network (DN). A Demand Response Program (DRP) integrated with Home Energy Storage Systems (HESSs) is presented to optimize the energy consumption of household consumers. Each consumer implements a Smart Home Energy Management System (SHEMS) to optimize their energy consumption according to their desired comfort and preferences. To modify the consumption pattern of household consumers, a Real-Time Pricing (RTP) algorithm is proposed to reflect the energy price of the wholesale market to the retail market and consumers. In addition, a Self-Healing System Reconfiguration (SHSR) program integrated with Distributed Energy Resources (DER), reactive power compensation equipment, and Energy Storage Systems (ESSs) is presented to manage the DN energy and restore the network loads in disruptive events. The reconfiguration operation is performed by converting the isolated part of the DN from the upstream network to several self-sufficient networked virtual microgrids without executing any switching process. Real data of California households are considered to model the home appliances and HESSs. The proposed comprehensive program is validated on the modified IEEE 123-bus feeder in normal and emergency operating conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

One of the reasons for the emerging adoption of behind-the-meter distributed energy resources (DERs), particularly photovoltaic (PV) and storage, is the impressive decrease in technology costs over the last years together with favorable policy and regulatory environments that created early-stage incentives to the proliferation of these assets. However, when looking at the next decade, the evolution of the regulatory framework and the trajectory of technology costs are difficult to predict. This uncertainty poses a new challenge to prosumers and microgrid owners who are trying to find the best moment to invest in these DERs. In particular, unpredictable changes in the conditions of the investments may translate into economic risks to potential DER adopters, which raises the need for new risk-mitigation methods to support their investment decisions. To address this issue, this paper proposes a multi-period DER investment model with economic risk constraints, considering technology costs and regulatory uncertainties. A case study, involving a large building in California, is used to show that different types of economic risk constraints can affect not only the size, but also the optimal timing of these investments in a multi-year planning horizon with significant DER technology costs and regulatory uncertainties. • Adds technology and regulatory uncertainty to the DER planning. • Optimizes multi-year DER investments strategies with risk constraints. • Presents DER planning strategies in a "cost-risk" decision-support framework. • Analyzes how different risk criteria impact DER investment solutions. [ABSTRACT FROM AUTHOR]