Canonical Coalitional Games vs. Coalition Formation Games for Power Exchange Management of Networked Microgrids

The concept of networked microgrids, which refers to a cluster of microgrids connected with each other, has emerged in the literature as a consequence of the increasing development of renewable energy. Energy management systems have been developed for planning, monitoring and controlling the power exchange into networked microgrids. Their main components are optimization algorithms for power exchange management. Several optimization algorithms based on coalition formation games were proposed to minimize distribution and transformation power loss of networked microgrids. Unlike these approaches, this paper proposes a non-lineal model based on canonical coalitional game for power exchange management of networked microgrids. To show the performance of the proposed model, results of the model and results of an algorithm based on coalition formation games recently reported in the literature are com-pared with. The main conclusion of this work is, when the objective is to minimize total power losses, the problem of power exchange management of networked microgrids should be modelled as a canonical coalition games and not as coalition formation games.Sociedad Argentina de Informática e Investigación Operativ

Canonical Coalitional Games vs. Coalition Formation Games for Power Exchange Management of Networked Microgrids

The concept of networked microgrids, which refers to a cluster of microgrids connected with each other, has emerged in the literature as a consequence of the increasing development of renewable energy. Energy management systems have been developed for planning, monitoring and controlling the power exchange into networked microgrids. Their main components are optimization algorithms for power exchange management. Several optimization algorithms based on coalition formation games were proposed to minimize distribution and transformation power loss of networked microgrids. Unlike these approaches, this paper proposes a non-lineal model based on canonical coalitional game for power exchange management of networked microgrids. To show the performance of the proposed model, results of the model and results of an algorithm based on coalition formation games recently reported in the literature are com-pared with. The main conclusion of this work is, when the objective is to minimize total power losses, the problem of power exchange management of networked microgrids should be modelled as a canonical coalition games and not as coalition formation games.Sociedad Argentina de Informática e Investigación Operativ

A Risk-Based Decision Framework for the Distribution Company in Mutual Interaction with the Wholesale Day-ahead Market and Microgrids

One of the emergent prospects for active distribution networks ( DN ) is to establish new roles to the distribution company ( DISCO ). The DISCO can act as an aggregator of the resources existing in the DN , also when parts of the network are structured and managed as microgrids ( MG s). The new roles of the DISCO may open the participation of the DISCO as a player trading energy in the wholesale markets, as well as in local energy markets. In this paper, the decision making aspects involving the DISCO are addressed by proposing a bilevel optimization approach in which the DISCO problem is modeled as the upper-level problem and the MG s problems and day-ahead wholesale market clearing process are modeled as the lower-level problems. To include the uncertainty of renewable energy sources, a risk-based two-stage stochastic problem is formulated, in which the DISCO 's risk aversion is modeled by using the conditional value at risk. The resulting nonlinear bilevel model is transformed into a linear single-level one by applying the Karush–Kuhn–Tucker conditions and the duality theory. The effectiveness of the model is shown in the application to the IEEE 33-bus DN connected to the IEEE RTS 24-bus power system

Peer-to-Peer Energy Trading for Networked Microgrids

Considering the limitations of the existing centralized power infrastructure, research interests have been directed to decentralized smart power systems constructed as networks of interconnected microgrids. Therefore, it has become critical to develop secure and efficient energy trading mechanisms among networked microgrids for reliability and economic mutual benefits. Furthermore, integrating blockchain technologies into the energy sector has gained significant interest among researchers and industry professionals. Considering these trends, the work in this thesis focuses on developing Peer-to-Peer (P2P) energy trading models to facilitate transactions among microgrids in a multiagent network. Price negotiation mechanisms are proposed for both islanded and grid-connected microgrid networks. To enable a trusted settlement of electricity trading transactions, a two-stage blockchain-based settlement consensus protocol is also developed. Simulation results have shown that the model has successfully facilitated energy trading for networked microgrids

Self-organizing Coordination of Multi-Agent Microgrid Networks

abstract: This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.Dissertation/ThesisDoctoral Dissertation Systems Engineering 201