SALSA: A Formal Hierarchical Optimization Framework for Smart Grid

Abstract

The smart grid, by the integration of advanced control and optimization technologies, provides the traditional grid with an indisputable opportunity to deliver and utilize the electricity more efficiently. Building smart grid applications is a challenging task, which requires a formal modeling, integration, and validation framework for various smart grid domains. The design flow of such applications must adapt to the grid requirements and ensure the security of supply and demand. This dissertation, by proposing a formal framework for customers and operations domains in the smart grid, aims at delivering a smooth way for: i) formalizing their interactions and functionalities, ii) upgrading their components independently, and iii) evaluating their performance quantitatively and qualitatively.The framework follows an event-driven demand response program taking no historical data and forecasting service into account. A scalable neighborhood of prosumers (inside the customers domain), which are equipped with smart appliances, photovoltaics, and battery energy storage systems, are considered. They individually schedule their appliances and sell/purchase their surplus/demand to/from the grid with the purposes of maximizing their comfort and profit at each instant of time. To orchestrate such trade relations, a bilateral multi-issue negotiation approach between a virtual power plant (on behalf of prosumers) and an aggregator (inside the operations domain) in a non-cooperative environment is employed. The aggregator, with the objectives of maximizing its profit and minimizing the grid purchase, intends to match prosumers' supply with demand. As a result, this framework particularly addresses the challenges of: i) scalable and hierarchical load demand scheduling, and ii) the match between the large penetration of renewable energy sources being produced and consumed. It is comprised of two generic multi-objective mixed integer nonlinear programming models for prosumers and the aggregator. These models support different scheduling mechanisms and electricity consumption threshold policies.The effectiveness of the framework is evaluated through various case studies based on economic and environmental assessment metrics. An interactive web service for the framework has also been developed and demonstrated.iii ResuméEt smart grid, ved at integrere avancerede styrings-og optimeringsteknologier, giver det traditionelle net en ubestridelig mulighed for at levere og udnytte el mere effektivt. Opbygning af smart grid applikationer er en udfordrende opgave, som kraever et formelt rammevaerk for modellering-, integration og validering af forskellige domaener. Designflowet af sådanne applikationer skal tilpasse sig netkravene og sikre forsynings-og efterspørgselssikker-heden. Denne afhandling, ved at foreslå et formelt rammevaerk for kundeog driftdomaener i smart grid, sigter mod at levere en smidig måde at: i) formalisere deres interaktioner og funktionaliteter, ii) opgradere deres komponenter uafhaengigt og iii) vurdere deres...

A Non-Cooperative Framework for Coordinating a Neighborhood of Distributed Prosumers

“…dec j,i (t), as modeled in (3), is affected by the corresponding binary flexibility status flex j,i (t) ∈ B. The status is updated according to the flexibility deadline θ j,i ∈ Z ≥0 , which is adjusted by the prosumer, defining for how long the prosumer is flexible in having the appliance's operation finished after its normal end time [26]. Each prosumer is equipped with a locally installed PV system (behind the meter).…”

“…where σ res A (t) is the reservation offer package of the aggregator denoting m • min ∀ρi∈P ℵ i (t) amount of electric power must be exchanged (in the worst case) with the grid for p l (t). It is coupled with a satisfaction index SI res A (t) ∈ (0, 2] (calculated by (26)). Similarly, the aggregator will not accept any offer package with the utility value less than ψ A (SI res A (t)).…”