Multi-Energy Microgrid Systems Planning and Energy Management Optimisation

Abstract

Conventional power systems are predominantly composed of centralised large-scale generation sites that provide electricity to a large number of customers in a top-down unidirectional fashion and through transmission and distribution networks. To increase penetration of Renewable Energy Resources (RES) into this traditional power system and promotion of Distributed Energy Resources (DER) concept as an effective solution to deal with the challenges being faced in the conventional power system such as the energy losses, peak demand, peak generation, the infrastructure depreciation, and environmental effect, Microgrid (MG) concept is introduced. MG is defined as a locally controlled small unit of the power system that usually is in interaction with the main grid and is regarded as the building blocks of future Smart Grids (SGs). However, these systems are also capable of operating independently and isolated from the main grid, particularly in remote areas where access to the main grid is impossible or there is a disruptive event on the power system. The emergence of cutting-edge advances in the energy conversion and energy storage technologies and their commercial availability as well as introduction of various lucrative grid services that both grid and customers can benefit from derived the planners and engineers to further expand the flexibility, resilience and efficiency of MGs. To achieve this, Multi-Energy Microgrid System (MEMGS) concept as an expanded definition of MG was introduced to improve the efficiency of conventional energy systems, reduce air pollution as well as energy utilisation. MEMGS incorporates various energy technologies such as axillary boiler, gas turbine, RESs, thermal and battery energy storage systems that are fed by multiple energywares such as gas and electricity to supply multiple types of demands simultaneously such as electrical, heating and cooling loads. However, the integration of clusters of various technologies and concurrent delivery of different energy services causes additional complexities into the modelling and optimisation of these systems due to the potential interactions of energy vectors and various technologies at the consumer level. The economic viability of MGs and MEMGSs rely on the configuration and operating management of the technologies. Therefore, is a need to develop an effective and efficient planning framework that can handle the interaction complexities and nonlinearities of the system, determining the most appropriate architecture, selecting the energy conversion and energy storage technologies and energy supply alternatives from a candidate pool. This thesis aims at addressing these challenges by initially developing a comprehensive and accurate dynamic model for MGs and MGESs components, investigating the technical and economic aspects, the nonlinear behaviour, maintenance and degradation phenomena, and uncertainties associated with technologies through Mixed-Integer Linear Programming (MILP) and Mixed Integer Quadratic Programming (MIQP). Then the established model is employed to establish and propose a multi-objective linearised planning optimisation approach. The architecture and choice of equipment of MEMGSs involve various elements such as availability and costs of the energy sources and equipment, and characteristics of the energy demand. Considering these factors, the proposed strategy allocates the size of the components utilised in the MGs and EMMGSs while meeting the defined performance indices such as degradation factor, reliability and grid power fluctuations smoothing indices. Once, the configuration and capacity of components are optimally determined, efficient energy management is required. The last part of this research focuses on energy management system scheduling and optimisation where the EMS scheduling module for MGs and MEMGSs are inspected considering the Time of Use tariff, peak shaving and valley filling functions, degradation of energy storage devices, along with the operating criteria and cost of the energy conversion units. Moreover, a real-time EMS solution is provided to deal with intermittent behaviour of RESs while participating in arbitrage market. The real-time EMS manages the energy flow optimally according to the acquired real-time data and its deviation from the original schedule attained in the scheduling optimisation stage. The primary objective of the EMS module development is to maximise profit while improving the performance of the MEMGSs. Throughout this research, the MILP and MIQP optimisation approach is adopted to achieve a fast convergence while avoiding complexity and long computation time that would cause due to the nonlinear behaviour and complex interaction of the technologies. Finally, having a practical insight into the challenges and concerns with connection adjacent MGs in distribution networks, an efficient centralised EMS optimisation framework is proposed to cope with the limitations and optimise the performance of the system, considering power losses, voltage deviations and nonlinear degradation of the components. The primary objective of this section of research is to achieve the optimal techno-economic solution.