Energy Management System for Microgrid System using Improved Grey Wolf Optimization Algorithm

An Energy Management System (EMS) is indispensable to monitor the power flow and load matching inside a microgrid during grid-connected mode (GCM) and islanded modes (IM) of operation. Many conventional optimization algorithms show poor reliability for real time optimization problem solving where an objective function is non-linear. An optimization technique is necessary to reduce the cost of energy obtained from the grid, generated inside the grid, and consumed by the load. This article presents, an optimization scheme based on the improved Grey wolf optimization (GWO) algorithm that considers replacement of wounded/injured wolves of one pack by strong wolves of other pack for an EMS in micro-grid. The GWO optimization algorithm's effectiveness is demonstrated forGCM and IM operation. The proposed GWO shows fast, lost cost and precise optimization of the real time EMS for the grid connected and islanded micro-grid system

Residential Demand Side Management model, optimization and future perspective: A review

The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generations (DGs) and advancement of information and communication technology (ICT) even though handles the related issues and challenges up to some extent, till the flexibility, energy management and scheduling with better planning are necessary for the residential sector to achieve better grid stability and efficiency. To address these issues, it is indispensable to analyze the demand-side management (DSM) for the complex residential sector considering various operational constraints, objectives, identifying various factors that affect better planning, scheduling, and management, to project the key features of various approaches and possible future research directions. This review has been done based on the related literature to focus on modeling, optimization methods, major objectives, system operation constraints, dominating factors impacting overall system operation, and possible solutions enhancing residential DSM operation. Gaps in future research and possible prospects have been discussed briefly to give a proper insight into the current implementation of DSM. This extensive review of residential DSM will help all the researchers in this area to innovate better energy management strategies and reduce the effect of system uncertainties, variations, and constraints

Reviewing energy system modelling of decentralized energy autonomy

Research attention on decentralized autonomous energy systems has increased exponentially in the past three decades, as demonstrated by the absolute number of publications and the share of these studies in the corpus of energy system modelling literature. This paper shows the status quo and future modelling needs for research on local autonomous energy systems. A total of 359 studies are roughly investigated, of which a subset of 123 in detail. The studies are assessed with respect to the characteristics of their methodology and applications, in order to derive common trends and insights. Most case studies apply to middle-income countries and only focus on the supply of electricity in the residential sector. Furthermore, many of the studies are comparable regarding objectives and applied methods. Local energy autonomy is associated with high costs, leading to levelized costs of electricity of 0.41 $/kWh on average. By analysing the studies, many improvements for future studies could be identified: the studies lack an analysis of the impact of autonomous energy systems on surrounding energy systems. In addition, the robust design of autonomous energy systems requires higher time resolutions and extreme conditions. Future research should also develop methodologies to consider local stakeholders and their preferences for energy systems

Planning of power distribution systems with high penetration of renewable energy sources using stochastic optimization

Driven by techno-economic and environmental factors, there is a global drive to integrate more distributed energy resources in power systems, particularly at the distribution level. These typically include smart-grid enabling technologies, such as distributed generation (DG), energy storage systems and demand-side management. Especially, the scale of DG sources (mainly renewables) integrated in many distribution networks is steadily increasing. This trend is more likely to continue in the years to come due to the advent of emerging solutions, which are expected to alleviate existing technical limitations and facilitate smooth integration of DGs. The favorable agreements of countries to limit greenhouse gas (GHG) emissions and mitigate climate change are also expected to accelerate the integration of renewable energy sources (RESs). However, the intermittent and volatile nature of most of these RESs (particularly, wind and solar) makes their integration in distribution networks a more challenging task. This is because such resources introduce significant operational variability and uncertainty to the system. Hence, the development of novel methodologies and innovative computational tools is crucial to realize an optimal and cost-efficient integration of such DGs, minimizing also their side effects. Novel methodologies and innovative computational tools are developed in this thesis that take into account the operational variability and uncertainty associated with the RES power generation, along with the integration of smart-grid enabling technologies. The developed methodologies and computational tools are tested in real-life power systems, as well as in standard test systems, demonstrating their computational proficiency when compared with the current state-of-the-art. Due to the inherent uncertainty and variability of RESs, stochastic programming is used in this thesis. Moreover, to ensure convergence and to use efficient off-the-shelf solvers, the problems addressed in this thesis are formulated using a mixed integer linear programming (MILP) approach.Atualmente há um esforço global para integrar mais recursos energéticos distribuídos nas redes elétricas, impulsionado por fatores técnico-económicos e ambientais, particularmente ao nível da rede de distribuição. Estes recursos incluem tipicamente tecnologias facilitadoras das redes elétricas inteligentes, tais como geração distribuída, sistemas de armazenamento de energia, e gestão ativa da procura. A integração de fontes de geração distribuída (energias renováveis, principalmente) está a aumentar progressivamente em muitas redes de distribuição, e é provável que esta tendência continue nos próximos anos devido ao avanço de soluções emergentes, esperando-se assim que as limitações técnicas existentes sejam ultrapassadas e que facilitem a integração progressiva das fontes de geração distribuída. Espera-se também que os acordos feitos pelos países para limitar as emissões de gases de efeito de estufa e para mitigar as alterações climáticas acelerem a integração de fontes de energia renováveis. No entanto, a natureza intermitente e volátil da maioria das fontes de energia renováveis (em particular, eólica e solar) faz com que a sua integração nas redes de distribuição seja uma tarefa complexa. Isto porque tais recursos introduzem variabilidade operacional e incerteza no sistema. Assim, é essencial o desenvolvimento de novas metodologias e ferramentas computacionais inovadoras para beneficiar uma integração óptima da geração distribuída renovável e minimizar os possíveis efeitos colaterais. Nesta tese são desenvolvidas novas metodologias e ferramentas computacionais inovadoras que consideram a variabilidade operacional e a incerteza associadas à geração a partir de fontes de energia renováveis, juntamente com a integração de tecnologias facilitadoras das redes elétricas inteligentes. As metodologias e ferramentas computacionais desenvolvidas são testadas em casos de estudo reais, bem como em casos de estudo clássicos, demonstrando a sua proficiência computacional comparativamente ao atual estado-da-arte. Devido à inerente incerteza e variabilidade das fontes de energia renováveis, nesta tese utiliza-se programação estocástica. Ainda, para assegurar a convergência para soluções ótimas, o problema é formulado utilizando programação linear inteira-mista

Multiobjective optimisation of hybrid wind-PV-battery-fuel cell-electrolyser-diesel systems : An integrated configuration-size formulation approach

Acknowledgment The financial support by Energy Renewable UK Ltd through co-funding of REST4U project is gratefully acknowledged.Peer reviewedPostprin

Optimal generator placement in a distributed network

Since the industrial and residential huge demand for electricity, as well as higher requirements for the electricity reliability and power quality. Meanwhile, the world has been in the energy crisis, the power shortage, and a large area often experienced blackouts accident. All exposed the deficiencies of ‘centralized power’. Thus, the approaches of reducing active power loss in power systems have become increasingly important. Among them, the method of the optimal location and size of distribution generators in a distributed network is one of the most prospective approaches in the future. And it can use into practice to achieve the purpose of low-carbonate, less cost and flexible power generation power systems because install DGs at the optimal location and with optimal size in distributed network can dramatically reduce active power loss in power systems. There are several models and methods have been suggested for solving the optimal DG placement problem. This paper presents models and methods applied to solve the optimal DG placement problem, and especially propose a new approach that based on an exact solution method using the enumerative method to reduce the number of the combination by request of constraints. In this case, the proposed method firstly will be applied to the simple 6 buses system, and then applied to 14 buses real size distribution network model which is based on the 126 buses real size distribution system. It can be evaluated for active power loss reduction features by DGs installation and choose optimal location and size of distribution generation in distributed network considering actual use

Operational Planning and Optimisation in Active Distribution Systems for Flexible and Resilient Power

The electricity network is undergoing significant changes to cater to environmental-deterioration and fuel-depletion issues. Consequently, an increasing number of renewable resources in the form of distributed generation (DG) are being integrated into medium-voltage distribution networks. The DG integration has created several technical and economic challenges for distribution network operators. The main challenge is basically the problem of managing network voltage profile and congestion which is caused by increasing demand and intermittent DG operations. The result of all of these changes is a paradigm shift in the way distribution networks operate (from passive to active) and are managed that is not limited only to the distribution network operator but actively engages with network users such as demand aggregators, DG owners, and transmission-system operators. This thesis expands knowledge on the active distribution system in three specific areas and attempts to fill the gaps in existing approaches. A comprehensive active network management framework in active distribution systems is developed to allow studies on (i) the flexibility of network topology using modern power flow controllers, (ii) the benefits of centralised thermal electricity storage in achieving the required levels of flexibility and resiliency in an active distribution system, and (iii) system resiliency toward fault occurrence in hybrid AC/DC distribution systems. These works are implemented within the Advanced Interactive Multidimensional Modelling Systems (AIMMS) software to carry out optimisation procedure. Results demonstrate the benefit provided by a range of active distribution system solutions and can guide future distribution-system operators in making practical decisions to operate active distribution systems in cost-effective ways

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