Sharing Storage in a Smart Grid: A Coalitional Game Approach

Sharing economy is a transformative socio-economic phenomenon built around the idea of sharing underused resources and services, e.g., transportation and housing, thereby reducing costs and extracting value. Anticipating continued reduction in the cost of electricity storage, we look into the potential opportunity in electrical power system where consumers share storage with each other. We consider two different scenarios. In the first scenario, consumers are assumed to already have individual storage devices and they explore cooperation to minimize the realized electricity consumption cost. In the second scenario, a group of consumers is interested to invest in joint storage capacity and operate it cooperatively. The resulting system problems are modeled using cooperative game theory. In both cases, the cooperative games are shown to have non-empty cores and we develop efficient cost allocations in the core with analytical expressions. Thus, sharing of storage in cooperative manner is shown to be very effective for the electric power system

Distributed solution methods for MPC based energy management method of interconnected microgrids: Dual ascent vs ADMM

This paper considers an optimal energy management problem for a network of interconnected microgrids. A model predictive control (MPC) approach is used to avoid capacity constraint violation and to cope with uncertainties of forecasted power demands. By employing a dual ascent method and a proximal alternative direction multiplier method (ADMM), respectively, two distributed methods are designed to allow every agent using only local information to determine its own optimal control decisions. The effectiveness of the proposed method is verified via numerical simulations

Ubicación de recursos distribuidos basado en flujos de potencia usando optimización por enjambre de partículas.

This article presents an analysis of the location, selection and optimal sizing of distributed generation in electrical distribution networks, obtaining an optimal power flow with active power compensation, through the implementation of the particle swarm optimization algorithm (PSO). The PSO allowed to solve the problem selecting the optimal nodes and the capacity of the distributed generation to install, fulfilling the objective of improving the parameters of quality and efficiency at the lowest possible cost. The simulation and analysis were made in a typical system of radial distribution of 15 nodes, with the Matlab computational tool, achieving a power flow that meets technical, economic and environmental conditions. The injection of active power by means of distributed generation allowed to obtain values of improved voltages in each node, minimizing indexes of average voltage deviation and maximum deviation. The proposed results were achieved by increasing the voltage levels, reducing power losses in the lines and complying with a minimum cost criterion.Este artículo presenta un análisis de ubicación, selección y dimensionamiento óptimo de generación distribuida en redes de distribución eléctrica, obteniendo un flujo óptimo de potencia con compensación de potencia activa, mediante la implementación del algoritmo de optimización por enjambre de partículas (PSO). El PSO permitió resolver el problema seleccionando los nodos óptimos y la capacidad de la generación distribuida a instalar, cumpliendo con el objetivo de mejorar los parámetros de calidad y eficiencia al menor costo posible. La simulación y análisis se realizaron en un sistema típico de distribución radial de 15 nodos, con la herramienta computacional Matlab, consiguiendo un flujo de potencia que cumple con condiciones técnicas, económicas y ambientales. La inyección de potencia activa mediante generación distribuida, permitió obtener valores de voltajes mejorados en cada nodo, minimizando índices de desviación promedio de voltaje y de máxima desviación. Los resultados propuestos se lograron, aumentando los niveles de voltaje, reduciendo pérdidas de potencia en las líneas y cumpliendo con un criterio de mínimo costo

Distributed optimal coordination for distributed energy resources in power systems

Driven by smart grid technologies, distributed energy resources (DERs) have been rapidly developing in recent years for improving reliability and efficiency of distribution systems. Emerging DERs require effective and efficient coordination in order to reap their potential benefits. In this paper, we consider an optimal DER coordination problem over multiple time periods subject to constraints at both system and device levels. Fully distributed algorithms are proposed to dynamically and automatically coordinate distributed generators with multiple/single storages. With the proposed algorithms, the coordination agent at each DER maintains only a set of variables and updates them through information exchange with a few neighbors. We show that the proposed algorithms with properly chosen parameters solve the DER coordination problem as long as the underlying communication network is connected. The simulation results are used to illustrate and validate the proposed method