Simulation and optimization model for the construction of electrical substations

One of the most complex construction projects is electrical substations. An electrical substation is an auxiliary station of an electricity generation, transmission and distribution system where voltage is transformed from high to low or the reverse using transformers. Construction of electrical substation includes civil works and electromechanical works. The scope of civil works includes construction of several buildings/components divided into parallel and overlapped working phases that require variety of resources and are generally quite costly and consume a considerable amount of time. Therefore, construction of substations faces complicated time-cost-resource optimization problems. On another hand, the construction industry is turning out to be progressively competitive throughout the years, whereby the need to persistently discover approaches to enhance construction performance. To address the previously stated afflictions, this dissertation makes the underlying strides and introduces a simulation and optimization model for the execution processes of civil works for an electrical substation based on database excel file for input data entry. The input data include bill of quantities, maximum available resources, production rates, unit cost of resources and indirect cost. The model is built on Anylogic software using discrete event simulation method. The model is divided into three zones working in parallel to each other. Each zone includes a group of buildings related to the same construction area. Each zone-model describes the execution process schedule for each building in the zone, the time consumed, percentage of utilization of equipment and manpower crews, amount of materials consumed and total direct and indirect cost. The model is then optimized to mainly minimize the project duration using parameter variation experiment and genetic algorithm java code implemented using Anylogic platform. The model used allocated resource parameters as decision variables and available resources as constraints. The model is verified on real case studies in Egypt and sensitivity analysis studies are incorporated. The model is also validated using a real case study and proves its efficiency by attaining a reduction in model time units between simulation and optimization experiments of 10.25% and reduction in total cost of 4.7%. Also, by comparing the optimization results by the actual data of the case study, the model attains a reduction in time and cost by 13.6% and 6.3% respectively. An analysis to determine the effect of each resource on reduction in cost is also presented

Streamlining the Decision-Making Process on Tubular Rigid Busbar Selection During the Planning / Designing Stage by Utilizing 3D Substation BIM Design Software

For Utilities, each substation is regarded as an asset. Managing of assets is one of domains of Asset Management including Life Cycle Costing (LCC) as a decision-making criterion. However, LCC as a decision-making criterion should be applied on an entire substation taking into account all of the potential cost influences for the purpose of achieving of an effective substation management. Asset management as a decision-making process should be observed within a larger context and should be more focused on risk management, as all real decisions include an element of risk due to present uncertainties. Two promising avenues are explored in regards to more comprehensive and rigorous up-front planning through usage of Information Technology (IT). While up-front planning falls under the domain of Lean philosophy, Building Information Modeling (BIM) falls under the category of agile decisionsupport tools. Utilization of both is explored from a perspective of design-uncertainties under both product and process design. Standard specifications and standard designs are another form of applied Lean Philosophy that reduces design-uncertainty and variability. However, a range of technical solutions stemming out of the standardization can be quite wide. Customization involves specification and design of new / innovative designs with wide range of technical solutions as well. Due to external pressures focused on shortening of the project delivery time, there is a need for a faster project time throughput. This is reflected in the form of a requirement for more rapid engineering decision-making and faster decision cycles. Streamlining of a decision-making process related to the engineering is all about engineers’ awareness of the situation from the project level perspective coupled with utilization of decision-support tools for creation and reuse of knowledge. Plan – Do – Study – Orient (PDSO) cycle is a decisionmaking model that supports creation and reusability of knowledge along with providing an explanation in regards to the time dimension relating to decision-making, and as such is presented in this paper. The rigid busbar system design is an iterative process influenced by many factors, defined either as design variables or design constraints. As rigid busbars are gaining more popularity for both greenfield and brownfield investments, the rigid busbar system design is explored from a perspective of decision-making streamlining. The case of the rigid busbar system design of El Chaparral project in El Salvador is given

A two-stage stochastic programming model for electric substation flood mitigation prior to an imminent hurricane

We present a stochastic programming model for informing the deployment of temporary flood mitigation measures to protect electrical substations prior to an imminent and uncertain hurricane. The first stage captures the deployment of a fixed number of mitigation resources, and the second stage captures grid operation in response to a contingency. The primary objective is to minimize expected load shed. We develop methods for simulating flooding induced by extreme rainfall and construct two geographically realistic case studies, one based on Tropical Storm Imelda and the other on Hurricane Harvey. Applying our model to those case studies, we investigate the effect of the mitigation budget on the optimal objective value and solutions. Our results highlight the sensitivity of the optimal mitigation to the budget, a consequence of those decisions being discrete. We additionally assess the value of having better mitigation options and the spatial features of the optimal mitigation.Comment: 35 pages, 12 figure

Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

Maintenance Optimization and Inspection Planning of Wind Energy Assets: Models, Methods and Strategies

Designing cost-effective inspection and maintenance programmes for wind energy farms is a complex task involving a high degree of uncertainty due to diversity of assets and their corresponding damage mechanisms and failure modes, weather-dependent transport conditions, unpredictable spare parts demand, insufficient space or poor accessibility for maintenance and repair, limited availability of resources in terms of equipment and skilled manpower, etc. In recent years, maintenance optimization has attracted the attention of many researchers and practitioners from various sectors of the wind energy industry, including manufacturers, component suppliers, maintenance contractors and others. In this paper, we propose a conceptual classification framework for the available literature on maintenance policy optimization and inspection planning of wind energy systems and structures (turbines, foundations, power cables and electrical substations). The developed framework addresses a wide range of theoretical and practical issues, including the models, methods, and the strategies employed to optimise maintenance decisions and inspection procedures in wind farms. The literature published to date on the subject of this article is critically reviewed and several research gaps are identified. Moreover, the available studies are systematically classified using different criteria and some research directions of potential interest to operational researchers are highlighted

Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview

Wind energy is a fast evolving field that has attracted a lot of attention and investments in the last dec- ades. Being an increasingly competitive market, it is very important to minimize establishment costs and increase production profits already at the design phase of new wind parks. This paper is based on many years of collaboration with Vattenfall, a leading wind energy developer and wind power operator, and aims at giving an overview of the experience of using Mathematical Optimization in the field. The paper illustrates some of the practical needs defined by energy companies, showing how optimization can help the designers to increase production and reduce costs in the design of offshore parks. In particular, the study gives an overview of the individual phases of designing an offshore windfarm,andsomeoftheoptimizationproblemsinvolved. Finally it goes in depth with three of the most important optimization tasks: turbine location, electrical cable routing and foundation optimization. The paper is concluded with a discussion of future challenges

LIFECYCLE MANAGEMENT OF OFFSHORE AND ONSHORE WIND FARMS

Since the demand for renewable energy sources on a global scale has increased substantially over the past few years, a great number of businesses have made investments in this industry and are doing their utmost to make additional developments and discoveries in the field of wind energy. Wind farms, both onshore and offshore, are considered to be key contributors to the production of sustainable energy because they offer significant benefits, including a reduction in the negative effects on the environment and the production of harmful gases. The purpose of this thesis was to analyse and explore the lifecycle activities of a wind farm, in order to determine the failure modes, failure effects, and failure consequences of the critical components, as well as the strategies that can be used to counteract these failures. As many wind farms are reaching their end of life, so this thesis also focused on the techniques and strategies that can be done before dismantling, The thesis also includes a reliability analysis, failure mode effect and criticality analysis of generator and gearbox of wind turbine, and also lifecycle cost analysis of an offshore wind farm. These studies improved our knowledge of offshore windfarm operations, maintenance strategies and give a brief information about cost reduction techniques. Several steps from maintenance strategies based on NORSOK Z-008 and ISO-14224, as well as knowledge gained from research papers and interviews with engineers in moreld, were implemented to achieve the goals of this thesis

Decommissioning of offshore wind turbines

Decommissioning is a key process in the offshore wind industry because all substructures, bottom fixed or floating, have to be removed and completely dismantled at the end of their service life. There is still no experience of decommissioning a floating wind substructure and only two very small offshore wind farms with bottom fixed platforms have already been decommissioned. Devising save and effective processes to dismantle wind offshore substructures is a challenge that has to be faced in civil engineering in near future

Chance-Constrained Outage Scheduling using a Machine Learning Proxy

Outage scheduling aims at defining, over a horizon of several months to years, when different components needing maintenance should be taken out of operation. Its objective is to minimize operation-cost expectation while satisfying reliability-related constraints. We propose a distributed scenario-based chance-constrained optimization formulation for this problem. To tackle tractability issues arising in large networks, we use machine learning to build a proxy for predicting outcomes of power system operation processes in this context. On the IEEE-RTS79 and IEEE-RTS96 networks, our solution obtains cheaper and more reliable plans than other candidates