Abstract
Recently, demand response programmes (DRPs) have captured great attention in electric power systems. DRPs such as time-of-use (ToU) programme can be efficiently employed in the power system planning to reform the long-term behaviour of the load demands. The composite generation expansion planning (GEP) and transmission expansion planning (TEP) known as composite GEP–TEP is of high significance in power systems to meet the future load demand of the system and also integrate renewable energy sources (RESs). In this regard, this study presents a dynamic optimisation framework for the composite GEP–TEP problem taking into consideration the ToU programme and also, the incentive-based and supportive programmes. Accordingly, the performances of the capacity payment and feed-in tariff mechanisms and the ToU programme in integrating RESs and reducing the total cost have been evaluated in this study. The problem has been formulated and solved as a standard two-stage mixed-integer linear programming model aimed at minimising the total costs. In this model, the ToU programme is applied and the results are fed into the expansion planning problem as the input. The proposed framework is simulated on the IEEE Reliability Test System to verify the effectiveness of the model and discuss the results obtained from implementing the mentioned mechanisms to support the RESs integration.

Abstract

Abstract
A multi-objective wind farm integration framework is proposed in this paper which considers the composite generation and reliability assessment and annualized operating and investment cost evaluation. An emission-controlled policy is adopted such that the amount of SOx and NOx decreases in line with renewable resource planning. Since the incorporation of large-scale distant wind farms is a problem of the multi-objective mixed-integer type with nonlinearities and non-convexities, this paper utilizes a fast elicit multi-objective Non-dominated Sorting Genetic Algorithm II (NSGA II) by probabilistic indices. It is noted that the impacts of the unavailability of the transmission system are modeled employing DC Optimal Power Flow (OPF) based on the incidence matrix together with the static security evaluation. Furthermore, in order to assess the performance of the suggested approach, the model is implemented on the Roy Billinton Test System (RBTS). Afterwards, distant wind farms integration into Iran's South-West Regional Grid (ISWRG) is studied. © 2019

Abstract
There is a growing need for increased flexibility in modern power systems. Traditionally, this flexibility has been provided by supply-side technologies. There has been an increase in the research surrounding flexibility services provided by demand-side actors and technologies, especially flexibility services provided by prosumers (those customers who both produce and consume electricity). This work gathers 1183 peer-reviewed journal articles concerning the topic and uses them to identify the current state of the art. This body of literature was analysed with two leading textual and scientometric analysis tools, SAS (c) Visual Text Analytics and VOSviewer, in order to provide a detailed understanding of the current state-of-the-art research on prosumer flexibility. Trends, key ideas, opportunities and challenges were identified and discussed.

Abstract
The integrated use of electricity and natural gas has captured great attention over recent years, mainly due to the high efficiency and economic considerations. According to the energy hub design and operation, which allows using different energy carriers, it has turned into a critical topic. This paper develops a two-stage stochastic model for energy hub planning and operation. The uncertainties of the problem have arisen from the electric, heating, and cooling load demand forecasts, besides the intermittent output of the solar photovoltaic (PV) system. The scenarios of the uncertain parameters are generated using the Monte-Carlo simulation (MCS), and the backward scenario reduction technique is used to alleviate the number of generated scenarios. Furthermore, this paper investigates the effectiveness of demand response programs (DRPs). The presented model includes two stages, where at the first stage, the optimal energy hub design is carried out utilizing the particle swarm optimization (PSO) algorithm. In this respect, the capacity of the candidate assets has been considered continuous, enabling the planning entity to precisely design the energy hub. The problem of the optimal energy hub operation is introduced at the second stage of the model formulated as mixed-integer non-linear programming (MINLP). The proposed framework is simulated using a typical energy hub to verify its effectiveness and efficiency.

Abstract
A highly versatile optimal task scheduling algorithm is proposed, inspired by Dijkstra's shortest path algorithm. The proposed algorithm is named "Dijkstra Optimal Tasking" (DOT) and is implemented in a generic manner allowing it to be applicable on a plethora of tasking problems In this study, the application of the proposed DOT algorithm is demonstrated for industrial setting in which a set of tasks must be performed by a mobile agent transiting between charging stations. The DOT algorithm is demonstrated by determining the optimal task schedule for the mobile agent which maximizes the speed of task achievement while minimizing the movement, and thereby energy consumption, cost. A discussion into the anticipated plethora of applications of this algorithm in different sectors is examined.