Massachussets Institute of Technology. Cambridge (Estados Unidos de América)
01 de septiembre de 2018
This dissertation demonstrates a novel integrated electric power system planning framework that incorporates distributed energy resources (DERs), flexible and price-responsive demand, and distribution network losses and reinforcement costs. New methods are developed and demonstrated to derive the aggregate impact of demand and DERs on distribution network losses and upgrade costs from detailed distribution network simulations. The results from these simulations are used to parameterize a novel and tractable representation of distribution networks at an aggregate scale in a new formulation of the electricity resource capacity planning problem. A set of case studies demonstrate the utility of this modeling framework for modeling competition amongst distributed and centralized resources, exploring tradeoffs between economies of unit scale and locational value of various resources, assessing the value of price-responsive electricity demand, and considering the impact of policy or regulation that drives the adoption of DERs. Methodologically, this dissertation makes a set of contributions, including: 1. A new approach to using AC power flow simulations to accurately derive the effect of aggregate changes in power withdrawals and injections on resistive network losses in large-scale distribution networks. 2. A method for adapting AC optimal power flow simulations to identify the minimum quantity of net reductions in coincident peak demand (achieved either by demand flexibility or distributed generation or storage) necessary to accommodate demand growth in large-scale distribution networks without investment in new network assets (e.g., 'non-wires' alternatives). 3. A method for using a distribution network planning model to determine the cost of traditional network upgrades required to accommodate an equivalent increase in peak demand. 4. An integrated electricity resource capacity planning model that employs results from the above methods to incorporate DERs and flexible demand and consider key sources of locational value or cost, including impacts on transmission and distribution network costs and losses. Electricity system planning models provide decision support for electric utilities, insight for policy-makers, and a detailed techno-economic framework to evaluate emerging technologies. Collectively, the new methods demonstrated herein expand the capabilities of these important planning tools to keep pace with a rapidly evolving electric power sector.
J. D. Jenkins (2018), Electricity system planning with distributed energy resources : new methods and insights for economics, regulation, and policy. Massachussets Institute of Technology. Cambridge (Estados Unidos de América).