The shift towards an energy Grid dominated by prosumers (consumers and producers of energy) will inevitably have repercussions on the distribution infrastructure. Today it is a hierarchical one designed to deliver energy from large scale facilities to end-users. Tomorrow it will be a capillary infrastructure at the Medium and Low Voltage levels that will support local energy trading among prosumers. In [74], we analyzed the Dutch Power Grid and made an initial analysis of the economic impact topological properties have on decentralized energy trading. In this paper, we go one step further and investigate how dierent networks topologies and growth models facilitate the emergence of a decentralized market. In particular, we show how the connectivity plays an important role in improving the properties of reliability and pathcost reduction. From the economic point of view, we estimate how the topological evolutions facilitate local electricity distribution, taking into account the main cost ingredient required for increasing network connectivity, i.e., the price of cabling.
The works mentioned so far take into account mainly the end of the while not least important is the Distribution especially in the vision of the future electrical system as proposed in this work where the end-user plays a vital role. The integrated planning of networks is tackled by Paiva al @cite_61 who emphasize the need of considering the two networks together to obtain a sensible optimal planning. The problem is modeled as a mixed integer-linear programming one considering an objective function for investment, maintenance, operation and losses costs that need to be minimized satisfying the constraints of energy balance and equipment physical limits.
@cite_61
2154788877 2016038157 2281797688 2048599615
Important research effort has been devoted to the topic of optimal planning of distribution systems. However, in general it has been mostly referred to the design of the primary network, with very modest considerations to the effect of the secondary network in the planning and future operation of the complete grid. Relatively little attention has been paid to the optimization of the secondary grid and to its effect on the optimality of the design of the complete electrical system, although the investment and operation costs of the secondary grid represent an important portion of the total costs. Appropriate design procedures have been proposed separately for both the primary and the secondary grid; however, in general, both planning problems have been presented and treated as different-almost isolated-problems, setting aside with this approximation some important factors that couple both problems, such as the fact that they may share the right of way, use the same poles, etc., among other factors that strongly affect the calculation of the investment costs. The main purpose of this work is the development and initial testing of a model for the optimal planning of a distribution system that includes both the primary and the secondary grids, so that a single optimization problem is stated for the design of the integral primary-secondary distribution system that overcomes these simplifications. The mathematical model incorporates the variables that define both the primary as well as the secondary planning problems and consists of a mixed integer-linear programming problem that may be solved by means of any suitable algorithm. Results are presented of the application of the proposed integral design procedure using conventional mixed integer-linear programming techniques to a real case of a residential primary-secondary distribution system consisting of 75 electrical nodes. Efficient and reliable demand side management techniques for community charging of plug-in hybrid electrical vehicles (PHEVs) and plug-in electrical vehicles (PEVs) are needed, as large numbers of these vehicles are being introduced to the power grid. To avoid overloads and maximize customer preferences in terms of time and cost of charging, a constrained nonlinear optimization problem can be formulated. In this paper, we have developed a novel cooperative distributed algorithm for charging control of PHEVs PEVs that solves the constrained nonlinear optimization problem using Karush-Kuhn-Tucker (KKT) conditions and consensus networks in a distributed fashion. In our design, the global optimal power allocation under all local and global constraints is reached through peer-to-peer coordination of charging stations. Therefore, the need for a central control unit is eliminated. In this way, single-node congestion is avoided when the size of the problem is increased and the system gains robustness against single-link node failures. Furthermore, via Monte Carlo simulations, we have demonstrated that the proposed distributed method is scalable with the number of charging points and returns solutions, which are comparable to centralized optimization algorithms with a maximum of 2 sub-optimality. Thus, the main advantages of our approach are eliminating the need for a central energy management coordination unit, gaining robustness against single-link node failures, and being scalable in terms of single-node computations. The planning of today's telecommunication networks is a very complex task, because the users and the demanded services as well as the costs to deploy and operate the network are evolving over time. Because of this reason, forecasts are made, which are inaccurate in nature. The dynamic and uncertain character of the input parameters needs to be taken into account during the network planning process. This PhD dissertation studies some important techno-economic aspects of the planning process, focusing on optical telecommunication networks, which form the basis of a lot of core networks of important telecom operators. Concerning the dynamic character of network traffic and equipment costs, our research compares the use of single period planning, anticipated planning and multi-period planning and their relation with investment selection techniques. Concerning the uncertain character of traffic demand and equipment costs, the well-known techniques using safety margins is evaluated and the use of Real Options thinking (originating from a stock option valuation technique) is illustrated. Furthermore, a lot of attention is given to the development of a cost model for a network operator, paying special attention to operational expenses. An activity-based cost model allows to quantify the operational expenses of the network operator. Therefore, different operational processes like maintenance, repair, service provisioning and pricing billing are distinguished. The process-based operational expenditures together with the continuous costs of infrastructure (costs for floor space rental, energy consumption, etc.) constitute the total operational expenditures for the telecom operator. Finally, we indicate how the suggested cost models can be applied in a liberalized telecom market. Recent data confirm that the power consumption of the information and communications technologies (ICT) and of the Internet itself can no longer be ignored, considering the increasing pervasiveness and the importance of the sector on productivity and economic growth. Although the traffic load of communication networks varies greatly over time and rarely reaches capacity limits, its energy consumption is almost constant. Based on this observation, energy management strategies are being considered with the goal of minimizing the energy consumption, so that consumption becomes proportional to the traffic load either at the individual-device level or for the whole network. The focus of this paper is to minimize the energy consumption of the network through a management strategy that selectively switches off devices according to the traffic level. We consider a set of traffic scenarios and jointly optimize their energy consumption assuming a per-flow routing. We propose a traffic engineering mathematical programming formulation based on integer linear programming that includes constraints on the changes of the device states and routing paths to limit the impact on quality of service and the signaling overhead. We show a set of numerical results obtained using the energy consumption of real routers and study the impact of the different parameters and constraints on the optimal energy management strategy. We also present heuristic results to compare the optimal operational planning with online energy management operation .