Title:  Valuation Methodology of Distributed Energy Resources Portfolios Based on an Electric Grid Business Model Innovation Framework for Renewable Energy Integration

Committee:

Dr. Santiago Grijalva, ECE, Chair , Advisor

Dr. Maryam Saeedifard, ECE, Co-Advisor

Dr. Shabbir Ahmed, ISyE

Dr. Lukas Graber, ECE

Dr. Juan Moreno-Cruz, ECON

Dr. Eric Overby, Business

Abstract:

Adoption of distributed energy resources (DERs) such as solar photovoltaic generators, energy storage, demand response devices, energy efficiency and electric vehicles is expected to grow in the coming years. This creates complex challenges for electric utilities planning and operations, as well as major effects on the electric utility business model. In response to this, regulatory entities are transforming their electric grid planning, operations, market processes, and utility business models to a model that is customer and DER-centric. In the near term, these regulatory reforms call for the valuation of DER portfolios to defer or avoid traditional electric utility distribution investments by allowing customers and energy service companies to offer DER services as alternatives. Therefore, there is a need for new and integrated methodology that allows to valuate DER portfolios and compare investment alternatives. Traditional valuation methodologies rely on average system-level input assumptions that do not take into consideration the locational and temporal constraints of DERs, the network model, market prices, uncertainty of renewables, risk of large deviations in the expected operational cost and how DERs are operated. This dissertation developed a valuation methodology of distributed energy resource portfolios based on an electric grid business model innovation architecture for renewable energy integration. The methodology consists of: 1) a system-level architecture to identify the market regulations and market actors, 2) a prosumer-based benefit-cost framework, 3) an economic-emissions optimization model to estimate operational cost impacts at the bulk system-level, 4) a DER portfolio economic schedule optimization at the distribution system, and 5) a two-stage stochastic optimization-based model and valuation method of DER portfolios. The methodology is demonstrated with realistic data sets. The results show that DER value depends on: the network characteristics, DER location, market prices, renewable output uncertainty, expected operational cost risk and how the DERs are operated. The framework provides electric utilities and regulators a valuation methodology to: 1) quantify the value of a DER portfolio to offer grid related services located in a distribution circuit under different scenarios of DER forecast, location and dispatch schedules; 2) assess the avoided cost enabled by a proposed DER non-wire alternative; 3) assess the operational adequacy of proposed DER non-wire alternative;  and 3) create an optimal DER portfolio by combining and comparing different third-party proposals.