Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm

n this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.This research was partially funded by Ministerio de Economía, Industria y Competitividad, project number TIN2017-85887-C2-1-P and TIN2017-85887-C2-2-P, and by the Comunidad Autónoma de Madrid, project number S2013ICE-2933_02

Grid computing technologies for renewable electricity generator monitoring and control

In this paper we discuss the use of real-time Grid computing for the monitoring, control and simulation of renewable electricity generators and their associated electrical networks. We discuss briefly the architectural design of GRIDCC and how we have integrated a number of real (solar, CHP) and simulated conventional power generators into the GRIDCC environment. A local weather station has also been attached to an Instrument Manager to alert experts appropriately when the Solar Array is not generating. The customised remote control and monitoring environment (a virtual control room), distributed using a standard web server, is discussed

Renewable energy integration into the Australian National Electricity Market: Characterising the energy value of wind and solar generation

This paper examines how key characteristics of the underlying wind and solar resources may impact on their energy value within the Australian National Electricity Market(NEM). Analysis has been performed for wind generation using half hour NEM data for South Australia over the 2008-9 financial year. The potential integration of large scale solar generation has been modelled using direct normal solar radiant energy measurements from the Bureau of Meteorology for six sites across the NEM. For wind energy, the level and variability of actual wind farm outputs in South Australia is analysed. High levels of wind generation in that State have been found to have a strong secondary effect on spot prices. Wind generation's low operating costs will see it displacing higher operating cost fossil-fuel plant at times of high wind. At the same time, the increased variability of wind may impose additional challenges and costs on conventional plant which will also be reflected in wholesale spot market prices. It is shown that this is proving particularly important during high wind penetration periods, which are contributing to an increased frequency of low or even negative prices. The solar resource in South Australia is shown to be highly variable; however, as seen with wind power, geographical dispersion of generators can significantly reduce power variability, even with as few as six sites. The correlation of the solar resource with spot prices also appears to be superior to wind generation. Modelling using the Adelaide solar resource showed that, for electricity sold into the spot market, two-axis tracking solar generators would achieve an average price that is over twice that received by wind generators over the year 2008-9 analysed. Of course, significant solar generation deployment might drive similar price impacts as seen with wind generation, thereby reducing this advantage. Considering the potential implications of both major wind and solar generation within South Australia, the solar and wind resources within the State appear, on average, to be non-correlated for the magnitude, and the change in magnitude, across half an hour. The analysis shows that solar and wind resources within the NEM have key characteristics that can markedly impact on their energy value within the wholesale electricity market. High levels of renewable electricity are already affecting spot prices, highlighting the need for low bidding renewable generators to attain power purchase contracts and for developers to consider this effect when choosing a site location for renewable generators. Other generators within the NEM may also be significantly impacted by major renewable energy deployment. The long-term success of renewable generation will likely depend on maximising the energy value that it contributes to the electricity industry.Energy value, Integration, NEM, Solar, Variability, Wind, Environmental Economics and Policy, Resource /Energy Economics and Policy,

Architectures for smart end-user services in the power grid

Abstract-The increase of distributed renewable electricity generators, such as solar cells and wind turbines, requires a new energy management system. These distributed generators introduce bidirectional energy flows in the low-voltage power grid, requiring novel coordination mechanisms to balance local supply and demand. Closed solutions exist for energy management on the level of individual homes. However, no service architectures have been defined that allow the growing number of end-users to interact with the other power consumers and generators and to get involved in more rational energy consumption patterns using intuitive applications. We therefore present a common service architecture that allows houses with renewable energy generation and smart energy devices to plug into a distributed energy management system, integrated with the public power grid. Next to the technical details, we focus on the usability aspects of the end-user applications in order to contribute to high service adoption and optimal user involvement. The presented architecture facilitates end-users to reduce net energy consumption, enables power grid providers to better balance supply and demand, and allows new actors to join with new services. We present a novel simulator that allows to evaluate both the power grid and data communication aspects, and illustrate a 22% reduction of the peak load by deploying a central coordinator inside the home gateway of an end-user