Fuzzy-based power exchange management between grid-tied interconnected residential microgrids

This paper presents a fuzzy-based power exchange management between two neighboring residential grid-connected microgrids comprising both photovoltaic generation and battery energy storage system (BESS). The proposed power exchange management accounts for the magnitude of the energy rate-of-change of each microgrid and the charge difference between the BESSs of both microgrids to charge the ESS that has an energy deficit. As such, the proposed power exchange management can reduce the amount of power absorbed from the mains of each microgrid by operating jointly with each other rather than separately, and it also synchronizes the ESS of both microgrids, improving the behavior of ESSs. A comparison of the simulated results for a scenario with and without power exchange is presented in order to demonstrate the adequate behavior of the proposed power exchange management.This work is part of the projects 2019-PIC-003-CTE and 2020-EXT-007 from the Research Group of Propagation, Electronic Control, and Networking (PROCONET) of Universidad de las Fuerzas Armadas ESPE. This work has been developed with the support of VLIR-UOS and the Belgian Development Cooperation (DGD) under the project EC2020SIN322A101. This work has been partially supported by the Spanish Ministry of Industry and Competitiveness under the grants DPI2015-67292-R and FEDER ECO 1823-2015

Chance-constrained Calculation of the Reserve Service Provided by EV Charging Station Clusters in Energy Communities

The concept of energy community is currently under investigation as it is considered central into the energy transition process. One of the main aspects of the successful implementation of community lays in the energy management system that coordinates exchanges among prosumers. This paper deals with the optimal energy management of a local energy community of dc microgrids with electric vehicle charging stations, considering local reserve provided by storage units and vehicle batteries. A two-stage optimal procedure is proposed to assess the optimal scheduling of resources for each community participant. Additionally, the optimal up and down reserve levels able to cover random fluctuations in photovoltaic generation within each EV-based microgrid are determined by a set of specific chance constraints

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

Control and Energy Management of Standalone Interconnected AC Microgrids

This thesis considered microgrids as local area distribution mini-power grids formed by distributed generation sources, energy storage systems and loads. They are reliable and can operate at different voltages and frequencies to meet the requirements of the load. Microgrids have limited renewable energy source (RES) capacity, which can only supply a limited load and increasing the load beyond a specifically designed limit can lead to stability issues. Irrespective of its limited capacity, there has been an increased widespread deployment of renewable energy-based microgrids worldwide orchestrated by the 2015 Paris Agreement and the war in Ukraine and as a solution to meet the global demand for energy in electricity deficit zones aimed to achieve universal access to affordable, reliable, and sustainable energy. Fast forward to the future, flooded singly operated microgrids face the problem of more curtailing of RES and load shedding. Multiple microgrids can be interconnected to mitigate the limitations of single microgrids and improve supply reliability, enhance power supply availability, stability, reserve capacity, reduce investment in new generating capacity and control flexibility. As a result, this thesis proposes a new structure and control technique for interconnecting multiple standalone AC microgrids to a common alternating current (AC) bus using a back-to-back power electronic converter and a traditional transformer. Each microgrid considered in this thesis comprises a renewable energy source (RES), battery, auxiliary unit, and load. The battery maintains the AC bus voltage and frequency and balances the difference in power generated by the RES and that consumed by the load. Each microgrid battery’s charge/discharge is maintained within the safest operating limit to maximise the RES power utilisation. The back-to-back converters are used to decouple the connecting standalone microgrid frequencies and facilitate power exchange between microgrids. The transformer is used to transmit electric power over long distances efficiently. The control technique for all the connecting bidirectional back-to-back converters is developed to manage the bidirectional power flow between each microgrid and other microgrids in the network and to balance the energy in the global bus of the interconnected microgrid with no communication. The control strategy uses a frequency signalling mechanism to limit the power demand of individual global converters and adjusts its droop coefficients accordingly and in proportion to deviation in frequency. The global droop controllers of the global connecting converters receive information about the status of the frequencies of individual microgrids using a low bandwidth communication link to enhance network power flow. MATLAB/Simulink results validate the performance of the proposed structure and control strategy. A decentralised control scheme is further proposed for the standalone interconnected AC microgrid structure. This thesis presented a high-level global droop controller that exchanges power between the interconnected microgrids. Renewable power curtailment and auxiliary power supplement mechanisms are designed based on the bus frequency signalling technique to achieve balance and continuity of supply. In case of power shortage in one microgrid, priority will first be given to power import from other microgrids. A power supplement is used if the power imported is insufficient to control the battery state of charge (SOC). Similarly, in case of a power surplus, priority will be given to power export, and if this is not enough, power from RES will be curtailed. Performance evaluation shows that the proposed controller maximises renewable power utilisation and minimises auxiliary power usage while providing better load support. The performance validation of the proposed structure and control strategy has been tested using MATLAB/Simulink. Furthermore, this thesis investigated a centralised control and energy management of multiple interconnected standalone AC microgrids using the Nelder-Mead simplex algorithm (Fminsearch optimisation toolbox in MATLAB) based on the new proposed model. The main objective is to minimise the total cost of energy from the auxiliary unit produced from gas. The results obtained are compared with those obtained from an unoptimised system. The performance evaluation investigation results are compared with the unoptimised results to determine the percentage optimal performance of the system. The comparison outcome shows that the proposed optimisation method minimises the total auxiliary energy cost by about 9% compared with the results of the unoptimised benchmark

Optimal allocation and operation of droop controlled islanded microgrids: a review

Copyright: © 2021 by the authors. This review paper provides a critical interpretation and analysis of almost 150 dedicated optimization research papers in the field of droop-controlled islanded microgrids. The significance of optimal microgrid allocation and operation studies comes from their importance for further deployment of renewable energy, reliable and stable autonomous operation on a larger scale, and the electrification of rural and isolated communities. Additionally, a comprehensive overview of islanded microgrids in terms of structure, type, and hierarchical control strategy was presented. Furthermore, a larger emphasis was given to the main optimization problems faced by droop-controlled islanded microgrids such as allocation, scheduling and dispatch, reconfiguration, control, and energy management systems. The main outcome of this review in relation to optimization problem components is the classification of objective functions, constraints, and decision variables into 10, 9 and 6 distinctive categories, respectively, taking into consideration the multi-criteria decision problems as well as the optimization with uncertainty problems in the classification criterion. Additionally, the optimization techniques used were investigated and identified as classical and artificial intelligence algorithms with the latter gaining popularity in recent years. Lastly, some future trends for research were put forward and explained based on the critical analysis of the selected papers