Abstract
This two-part work presents a new multistage and stochastic mathematical model, developed to support the decision-making process of planning distribution network systems (DNS) for integrating large-scale "clean" energy sources. Part I is devoted to the theoretical aspects and mathematical formulations in a comprehensive manner. The proposed model, formulated from the system operator's viewpoint, determines the optimal sizing, timing, and placement of distributed energy technologies (particularly, renewables) in coordination with energy storage systems and reactive power sources. The ultimate goal of this optimization work is to maximize the size of renewable power absorbed by the system, while maintaining the required/standard levels of power quality and system stability at a minimum possible cost. From the methodological perspective, the entire problem is formulated as a mixed integer linear programming optimization, allowing one to obtain an exact solution within a finite simulation time. Moreover, it employs a linearized ac network model which captures the inherent characteristics of electric networks and balances well accuracy with computational burden. The IEEE 41-bus radial DNS is used to test validity and efficiency of the proposed model, and carry out the required analysis from the standpoint of the objectives set. Numerical results are presented and discussed in Part II of this paper to unequivocally demonstrate the merits of the model.

Abstract

Abstract
This work presents a new integrated multistage and stochastic mathematical model, which is developed to support the decision-making process related to the expansion planning of distribution network systems for integrating large-scale distributed "clean" energy sources. The developed model, formulated from the distribution system operator's point of view, determines the optimal sizing, time, and placement of distributed energy technologies (renewables, in particular) as well as that of energy storage systems (ESSs) and compensators in distribution networks. The ultimate goal of this optimization work is to maximize the size of distributed generation (DG) power absorbed by the system while maintaining the power quality and stability at the required/standard levels at a minimal cost possible. The model, formulated as a mixed-integer linear programming optimization, employs a linearized alternating current network model that captures well the inherent characteristics of power network systems, and balances accuracy with computational burden. The standard IEEE 41-bus distribution system is used to test the developed model and carry out the required analysis from the standpoint of the objectives set.The results of the case study show that the integration of ESS and compensators helps to significantly increase the size of variable generation (wind and solar) in the system. For the case study, a total of 10. MW demand wind and solar power has been added to the system. One can put this into perspective with the peak load 4.635. MW in the system. This means it has been possible to integrate renewable energy source (RES) power more than twice the peak demand in the base case. It has been demonstrated that the joint planning of DGs, compensators, and ESSs, proposed in this work, bring about significant improvements to the system, such as reduction of losses, cost of electricity and emissions, voltage support, and many more.The expansion planning model proposed here can be considered a major leap forward toward developing controllable grids, which support large-scale integration of RESs (as opposed to the conventional "fit and forget" approach). It can also be a handy tool to speed up the integration of more RESs until smart-grids are materialized in the future.

Abstract
This book chapter explores existing and emerging flexibility options that can facilitate the integration of large-scale variable renewable energy sources (vRESs) in next-gen electric distribution networks while minimizing their side-effects and associated risks. Nowadays, it is widely accepted that integrating vRESs is highly needed to solve a multitude of global concerns such as meeting an increasing demand for electricity, enhancing energy security, reducing heavy dependence on fossil fuels for energy production and the overall carbon footprint of power production. As a result, the scale of vRES development has been steadily increasing in many electric distribution networks. The favorable agreements of states to curb greenhouse gas emissions and mitigate climate change, along with other technical, socio-economic and structural factors, is expected to further accelerate the integration of renewables in electric distribution networks. Many states are now embarking on ambitious “clean” energy development targets. Distributed generations (DGs) are especially attracting a lot of attention nowadays, and planners and policy makers seem to favor more on a distributed power generation to meet the increasing demand for electricity in the future. And, the role of traditionally centralized power production regime is expected to slowly diminish in future grids. This means that existing electric distribution networks should be readied to effectively handle the increasing penetration of DGs, vRESs in particular, because such systems are not principally designed for this purpose. It is because of all this that regulators often set a maximum RES penetration limit (often in the order of 20%) which is one of the main factors that impede further development of the much-needed vRESs. The main challenge is posed by the high-level variability as well as partial unpredictability of vRESs which, along with traditional sources of uncertainty, leads to several technical problems and increases operational risk in the system. This is further exacerbated by the increased uncertainty posed by the continuously changing and new forms of energy consumption such as power-to-X and electric vehicles. All these make operation and planning of distribution networks more intricate. Therefore, there is a growing need to transform existing systems so that they are equipped with adequate flexibility mechanisms (options) that are capable of alleviating the aforementioned challenges and effectively managing inherent technical risk. To this end, the main focus of this chapter is on the optimal management of distribution networks featuring such flexibility options and vRESs. This analysis is supported by numerical results from a standard network system. For this, a reasonably accurate mathematical optimization model is developed, which is based on a linearized AC network model. The results and analysis in this book chapter have policy implications that are important to optimally design ad operate future grids, featuring large-scale variable energy resources. In general, based on the analysis results, distribution networks can go 100% renewable if various flexibility options are adequately deployed and operated in a more efficient manner. © 2018, Springer Nature Singapore Pte Ltd.

Abstract
As a result of the increased awareness of the dangers posed by global climate changes (mainly caused by growing global energy consumption needs), the quest for clean and sustainable energy future is becoming of paramount importance. This can be largely realized via a large-scale integration of variable renewable energy sources (RESs) such as wind and solar, which have relatively low carbon footprints. In many power systems, the level of integration of such resources is dramatically increasing. However, their intermittent nature poses significant challenges in the predominantly conventional power systems that currently exist. Among others, frequency and voltage regulation issues can, for example, arise because of improperly balanced and largely uncoordinated RES supply and demand. Generally, the higher the integration level of intermittent power sources is, the higher the flexibility needs are in the system under consideration. Flexibility, in a power systems context, refers to the ability of such a system to effectively cope with unforeseen changes in operational situations, which are mainly induced by the inherent uncertainty and variability arising from the supply side, demand side or any other external factors. In the absence of appropriate flexibility mechanisms, it is increasingly difficult to manage the imbalances between generation and demand as a result of their natural variations in real-time. This paper presents an extensive and critical review of the main existing and emerging flexibility options that can be deployed in power systems to support the integration of "carbon-free" and variable power production technologies. Starting from a broader definition of flexibility, we highlight the growing importance of such flexibility in renewable-rich energy systems, and provide insights into the challenges and opportunities associated with various flexibility options provided by different technologies.

Abstract
Dynamic distribution system reconfiguration (DDSR) is the process of dynamically changing the network's topology during the operational periods of the system. This process together with the integration of distributed renewable energy sources (DRES) and other enabling technologies allow a more efficient operation of such systems in technical and economic terms, facilitating a seamless integration of DRES in larger quantities. When performing such an optimization process, the stochastic nature of DRES (both variability and uncertainty) needs to be taken into consideration. In this paper, an improved dynamic system reconfiguration model is presented where the goal is to minimize the total cost in the system while satisfying various technical constraints so as to maintain the reliability and stability of the system at required levels. The computational tool is tested in a real system encompassing the distribution system of Lagoa (in Sao Miguel Island, Azores), and its effectiveness is properly validated. The numerical results demonstrate great benefits in economic terms, such as reduced losses and improved system reliability.