Exploring Regulation Policies in Distribution Networks through a Multi-Agent Simulator

This paper presents a multi-agent simulator that describes the interactions between the agents of a distribution network (DN), and an environment. The agents are the users of the DN and the electricity distribution system operator. The environment is the set of rules (tariff design, technology costs, or incentive schemes) that impacts the agents interactions. For a given environment, we can simulate the evolution of the agents and the environment itself. We assume the electricity consumers are rational agents that may deploy distributed renewable energy installations if they are cost-efficient compared to the retail electricity tariff. The deployment of such installations may alter the cost recovery scheme of the distribution system operator, by inducing a change in the way the user use of the grid. By modelling the cost recovery mechanism of the distribution system operator, the system simulates the evolution of the retail electricity tariff in response to such a change in the aggregated consumption and production.Peer reviewe

A Stackelberg game for incentive-based demand response in energy markets

In modern buildings renewable energy generators and storage devices are spreading, and consequently the role of the users in the power grid is shifting from passive to active. We design a demand response scheme that exploits the prosumers' flexibility to provide ancillary services to the main grid. We propose a hierarchical scheme to coordinate the interactions between the distribution system operator and a community of smart prosumers. The framework inherits characteristics from price-based and incentive-based schemes and it retains the advantages of both. We cast the problem as a Stackelberg game with the prosumers as followers and the distribution system operator as leader. We solve the resulting bilevel optimization program via a KKT reformulation, proving the existence and the convergence to a local Stackelberg equilibrium. Finally, we provide numerical simulations to corroborate our claims on the benefits of the proposed framework.Comment: Submitted to CDC 2022, 8 pages, 7 figure

A Response-Function-Based Coordination Method for Transmission-Distribution-Coupled AC OPF

With distributed generation highly integrated into the grid, the transmission-distribution-coupled AC OPF (TDOPF) becomes increasingly important. This paper proposes a response-function-based coordination method to solve the TDOPF. Different from typical decomposition methods, this method employs approximate response functions of the power injections with respect to the bus voltage magnitude in the transmission-distribution (T-D) interface to reflect the "reaction" of the distribution to the transmission system control. By using the response functions, only one or two iterations between the transmission system operator (TSO) and the distribution system operator(s) (DSO(s)) are required to attain a nearly optimal TDOPF solution. Numerical tests confirm that, relative to a typical decomposition method, the proposed method does not only enjoy a cheaper computational cost but is workable even when the objectives of the TSO and the DSO(s) are in distinct scales.Comment: This paper will appear at 2018 IEEE PES Transmission and Distribution Conference and Expositio

Capacity Market for Distribution System Operator – with Reliability Transactions – Considering Critical Loads and Microgrids

Conventional distribution system (DS) asset planning methods consider energy only from transmission systems (TS) and not from distributed energy resources (DER), leading to expensive plans. Newer transactive energy DS (TEDS) asset planning models, built on capacity market mechanisms, consider energy from both TS and DERs, leading to lower-cost plans and maximizing social welfare. However, in both methods the cost of higher reliability requirements for some users are socialized across all users, leading to lower social welfare. In this paper, a novel transactive energy capacity market (TECM) model is proposed for DS asset planning. It builds on TEDS incremental capacity auction models by provisioning for critical loads to bid and receive superior reliability as a service. The TECM model considers these reliability transactions, in addition, to selling energy transactions from TS and DERs, buying energy transactions from loads, and asset upgrade transactions from the network operator. The TECM model allows for islanded microgrids and network reconfiguration to maximize social welfare. The TECM model is assessed on several case studies, demonstrating that it achieves higher social welfare and a lower plan cost