Multi-agent MPC protocols for microgrid energy management and optimization

Navržení efektivního a spolehlivého řízení mikrosítí s vysokým podílem energie z obnovitelných zdrojů, je jednou z výzev při jejich nasazení. Prediktivní řízení (MPC) systému je slibný přístup, jak vyřešit tento problém v určitém časovém horizontu. Tento přístup umožňuje integraci řízení na základě minimalizace funkce, která dává do souvislosti různé druhy nákladů a omezení systému, ve vazbě na výrobu a spotřebu energie. Navržené multiagentní MPC řízení bylo vyvinuto jako dvoustupňová architektura, založená na konsensuálním algoritmu více agentů, který zajišťuje výkonovou rovnováhu v mikrosíti a centralizovaném MPC, který zefektivňuje řízené procesy tak, aby dosáhly vytyčených cílů. Při zkoumání navržených simulací byla ověřena předpokládaná korelace získaných výsledků a řídicích parametrů. Dále byla identifikována a analyzována situace s nejvyšším zlepšením ve srovnání s výsledky referenční řídící architektury. Na základě výsledků testů řídicího protokolu na testovaných datech, které byly měřeny v reálné mikrosíti, je vidět možnost významného snížení nákladů na provoz mikrosítě. Navrhované řešení tedy ukazuje vhodnost jeho implementace a přínos, jak pro provozovatele mikrosítí, tak pro zákazníky distribuční soustavy.One of the challenges of microgrids under the influence of high shares of intermittent renewable energy sources (RES) is an effective and reliable control. Model predictive control (MPC) is a promising approach to solve this problem for a specified time horizon since it allows integrating of a cost-minimizing objective function and system boundaries while taking power demand and supply into account. An agent-based MPC scheme was developed as a two-level architecture based on multi-agent control system (MAS) consensus algorithm providing power balance in the microgrid and centralized MPC that is aspiring to streamline the control processes to reach the targeted objectives. During the examination of the simulated results, the expected correlation of the result properties and control parameters was found. Additionally, the situations with the highest improvement ratio in comparison with the results of the reference control architecture were discovered and analysed. Based on the results, a significant cost reduction can be seen in most of the tested datasets that were measured on a real-life microgrid solution. Therefore, the implementation of the suggested control can prove to be appropriate and beneficial for microgrid operators and grid customers

Reducing Grid Distortions Utilizing Energy Demand Prediction and Local Storages

© 2021 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.Energy storage systems will play a key role in the establishment of future smart grids. Specifically, the integration of storages into the grid architecture serves several purposes, including the handling of the statistical variation of energy supply through increasing usage of renewable energy sources as well as the optimization of the daily energy usage through load scheduling. This article is focusing on the reduction of the grid distortions using non-linear convex optimization. In detail an analytic storage model is used in combination with a load forecasting technique based on socio-economic information of a community of households. It is shown that the proposed load forecasting technique leads to significantly reduced forecasting errors (relative reductions up-to 14.2%), while the proposed storage optimization based on non-linear convex optimizations leads to 12.9% reductions in terms of peak to average values for ideal storages and 9.9% for storages with consideration of losses respectively. Furthermore, it was shown that the largest improvements can be made when storages are utilized for a community of households with a storage size of 4.6-8.2 kWh per household showing the effectiveness of shared storages as well as load forecasting for a community of households.Peer reviewe

Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

planning tool for polygeneration design in microgrids

Abstract This work suggests a methodology to assist the designer during the planning phase of microgrids and eco-districts. A mixed integer linear programming model is designed to mathematically describe the different energy systems and the physical relations among them. Given the different electrical/thermal demand profiles, the micro grid's topology and a set of boundary conditions, the model can identify the optimum mix of (poly-)generation units and energy storage systems, as well as the necessary district heating/cooling infrastructure. Both economic and energetic cost functions are defined to explore the problem from different perspectives. The described tool is applied to study an actual district of the NTU campus in Singapore, comprising 5 multi-purpose buildings and a district cooling network supplied by centralized electrical chillers. The planning tool was run to assess the optimal configuration that minimizes the overall cost (initial investment and OM the outcome results presented a layout and a mix of energy systems different from the present one. In particular, the optimal configuration results to be a district cooling system served by a mix of electrical chiller plant, trigeneration distributed energy system and sensible cold thermal energy storage

Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources : A comprehensive review

The hybrid AC/DC microgrids have become considerably popular as they are reliable, accessible and robust. They are utilized for solving environmental, economic, operational and power-related political issues. Having this increased necessity taken into consideration, this paper performs a comprehensive review of the fundamentals of hybrid AC/DC microgrids and describes their components. Mathematical models and valid comparisons among different renewable energy sources’ generations are discussed. Subsequently, various operational zones, control and optimization methods, power flow calculations in the presence of uncertainties related to renewable energy resources are reviewed.fi=vertaisarvioitu|en=peerReviewed

Short-term Self-Scheduling of Virtual Energy Hub Plant within Thermal Energy Market

Multicarrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among multiple energy systems and energy hubs in different energy markets. By the advent of the local thermal energy market in many countries, energy hubs' scheduling becomes more prominent. In this article, a new approach to energy hubs' scheduling is offered, called virtual energy hub (VEH). The proposed concept of the energy hub, which is named as the VEH in this article, is referred to as an architecture based on the energy hub concept beside the proposed self-scheduling approach. The VEH is operated based on the different energy carriers and facilities as well as maximizes its revenue by participating in the various local energy markets. The proposed VEH optimizes its revenue from participating in the electrical and thermal energy markets and by examining both local markets. Participation of a player in the energy markets by using the integrated point of view can be reached to a higher benefit and optimal operation of the facilities in comparison with independent energy systems. In a competitive energy market, a VEH optimizes its self-scheduling problem in order to maximize its benefit considering uncertainties related to renewable resources. To handle the problem under uncertainty, a nonprobabilistic information gap method is implemented in this study. The proposed model enables the VEH to pursue two different strategies concerning uncertainties, namely risk-averse strategy and risk-seeker strategy. For effective participation of the renewable-based VEH plant in the local energy market, a compressed air energy storage unit is used as a solution for the volatility of the wind power generation. Finally, the proposed model is applied to a test case, and the numerical results validate the proposed approach