1,721,021 research outputs found
Renewable hosting capacity improvement with grid reinforcement optimization
No full textThe integration of renewable energy sources (RES) into power grids plays a crucial role in the transition towards sustainable power systems. However, the intermittent and unpredictable nature of RES introduces challenges that require a careful and effective strategy to enhance the hosting capacity for renewable energy while maintaining optimal power flows within the grid. This thesis proposes an innovative methodology that combines Particle Swarm Optimization (PSO) and Second-Order Cone Programming (SOCP) for the Distflow equation, aiming to maximize the Renewable Energy Hosting Capacity (REHC) without compromising operational limits.
Our approach leverages a PSO-based technique to optimize grid reinforcement parameters, including line current, resistance, and reactance. The optimization process considers the resistance, reactance, and rating of each line, with the objective of increasing the hosting capacity of renewable energy while minimizing investment costs.
To evaluate the effectiveness of the proposed methodology, we plan to implement and test it on a radial 33-bus distribution system. Our results demonstrate that the method effectively enhances the hosting capacity for RES while adhering to the given budget for grid reinforcement. This approach shows promise in assisting power system planners and operators in making strategic decisions related to grid reinforcement and the integration of renewable energy
Optimal Electric Vehicle Fleet Management through Integrated Charging Station Placement and Joint Optimal Allocation and Scheduling: A Combined Optimization Approach
No full textThe transition towards Electric Vehicles (EVs) worldwide highlights the need for effective charging infrastructure and its efficient utilization. This thesis introduces a novel combined optimization approach to optimize the management of EV fleets by integrating charging station placement, optimal allocation, and scheduling. In the first phase, the research builds upon the model proposed by Lam, Leung, and Chu to strategically determine charging station locations, taking into account factors such as coverage, EV driving range, and driver convenience. The second phase focuses on the joint optimal allocation and scheduling (JOAS) of electric buses, incorporating Vehicle-to-Grid (V2G) regulation signals, following the approach by Zhang and Leung [2]. By leveraging these approaches, this study aims to enhance the operational efficiency and performance of EV fleets, contributing to the advancement of sustainable transportation systems.
The findings of this research contribute to the field of electric vehicle infrastructure and fleet management, offering a comprehensive solution that benefits city planners, policymakers, and other stakeholders involved in EV implementation. The objective is to establish a cost-effective and efficient EV fleet management system that generates a healthy profit margin to offset costs. By providing a robust and sustainable framework, this combined optimization approach plays a crucial role in facilitating the transition toward green transportation fleet management and contributing significantly to the green transportation transition
Active Distribution Network Planning Considering Uncertainties of Renewable Generation and Load Growth
No full textIntegrated distribution system planning is a specific grid planning method to satisfy load growth and design objectives related to reliability, resilience, safety, and operational efficiency. The installation of distributed energy resources (DER) has transformed the traditional passive distribution network, where power flows from the main transformer to the loads, into an active distribution network that accommodates bidirectional power flows. This study proposes an active distribution network planning model that considers the uncertainties in the load growth prediction and outputs of renewable energy resources for future years. The model adopted in this study divides the energy roles in the distribution network into two players: the distribution system operator (DSO) and the prosumers. Prosumers can play the role of power producers and consumers. Using game theory, the interactions between these two players can be defined as an optimization problem to find the best strategies for each player and satisfy the goal of integrated resource planning. Each player has their respective investment strategies based on the constraints of resources and responsibility. In this study, the prosumer utilizes the Maximin Decision Criterion to select the optimal investment for selling electricity to the DSO. Considering these scenarios and constraints, both players can have a satisfying solution, which leads to the optimal location, equipment type, capacity size, investment time, and electricity price
Unit commitment considering regional PM2.5 concentration
No full textPM_2.5 poses a threat to the environment and ecology and has become an important issue in recent years. Reducing coal consumption is one of the ways to improve thermal power plants. At this stage, there is no precise criterion for coal reduction (especially for estimating the impact of emission reduction on specific affected objects, such as cities). The air dispersion model can quantify the regional impact of power plant emissions based on meteorological conditions. In this paper, the air dispersion model is added to unit commitment, which becomes a Multi-Objective Programming problem that considers the economy and the pollution concentration of major regions at various times. This paper uses AQI to set relevant pollution regulations. At this time, PM_2.5 forecast and load forecast are of the same importance. This paper studies the influence of forecast values with different accuracy on the scheduling results. The penalty factor is used to convert the concentration into economic valuation and included in the objective function. This paper uses the YALMIP toolbox to construct mathematical problems in the MATLAB and solves through the Gurobi optimizer. The IEEE 39-bus is used as the power grid model. Finally, the simulation results confirmed that with the help of the dispersion model, a more detailed unit commitment can be provided with consideration of regional PM_2.5 concentration can be provided. As the penalty factor changes, different costs and pollution concentration results in each region are produced. This relationship will be drawn into a trade-off curve to provide a preliminary basis
Effects of Load Characteristic on Frequency Response of Generator Outage and Fast Reserve Requirement
No full textThe renewable penetration continues to increase and causes system inertia reduction. Once a generator unit outage occurs under different energy mix, it can easily impact the power system operation and affect the frequency stability. To avoid rapid system frequency drop and trigger the underfrequency load shedding, this thesis proposes a scheme to determine the requirement of the fast response reserve. The generator governor response coefficient and load damping coefficient are inferred from historical generator incident data statistics, and the swing equation is used to calculate the fast response reserve requirement. Different years, seasons and time periods, would have different frequency response since the load composition and generator unit committed are different. Instead of using a single average value for all time, when calculating the demand for fast response reserve, the current situation of the system should be considered. The use of fast frequency reserve after unit outage is simulated with PSSE to verify the effectiveness of the proposed method to avoid rapid frequency drop, and over- or under-preparation of the fast response reserve to maintain frequency operational resilience
A methodology for hard-coupling Generation Expansion Problem with Unit-Commitment for flexibility and adequacy verification
No full textMost of the world's electric systems are undergoing major overhauls as renewable energy sources are being aggressively integrated into them. However, conventional generation expansion planning methodologies fail to capture the short-term intricacies of these technologies, leading to inadequate design of complementary technologies for ensuring grid stability. In this research, we present our designed power system planning methodology that interlinks conventional generation expansion planning and unit-commitment models. The hybrid model in our methodology enables us to find optimal expansion plans, considering both coarse- and fine-grained time horizon constraints. We have developed two major test cases: firstly, we created a benchmark test to compare our proposed methodology with the state-of-the-art approaches and successfully demonstrated that, despite a tradeoff in simulation time, our methodology produces superior quality and more cost-effective expansion plans. Secondly, we developed a stochastic real-use case scenario of a simplified Taiwanese power system as a proof of concept and validation of our methodology's applicability to real-world systems as evidence for further research to be implemented with mature power system planning software
A Research about Integrating Distributed Resources as Black Start Ancillary Services
No full textAfter blackout, generation units with self-start capability are started to provide required power to local generation station and energize remote non-black start units through transmission lines, and gradually extend the service restoration area. Due to the uncertainties of outputs from distributed energy resources (DER), they are not utilized in the system restart and service restoration operation. However, with the increase of renewables penetration and advanced control technology, inverter based resources (IBR) are being considered to provide black start service in ancillary service market. This study investigates the possibility of using IBR to start and build a distributed restart zone (DRZ) to provide emergency power for critical loads and crank power to remote non-black start generation units. This thesis discusses the challenges of building DRZ for these purposes and related control strategies to mitigate dynamic voltage and frequency problems during the process. Simulations of starting the DRZ, energizing the transformer, transmission line, and cranking remote generation units with various control schemes in each step of the process are described. A region with high integrated renewable capacity in conjunction with an energy storage system in the southern part of Taiwan is adopted to prove the concept of using DRZ to provide black start cranking power to an independent power producer after blackout. Simulink package in Matlab platform is used to simulate performance of the proposed control schemes. Simulations results are presented and discussions on the use of distributed energy resources to support power system black start are given
Resilient Scheduling of Control Software Updates in Radial Power Distribution Systems [Elektronisk resurs]
No full textIn response to newly found security vulnerabilities, or as part of a moving target defense, a fast and safe control software update scheme for networked control systems is highly desirable. We here develop such a scheme for intelligent electronic devices (IEDs) in power distribution systems, which is a solution to the so-called software update rollout problem. This problem seeks to minimize the makespan of the software rollout, while guaranteeing safety in voltage and current at all buses and lines despite possible worst-case update failure where malfunctioning IEDs may inject harmful amounts of power into the system. Based on the nonlinear DistFlow equations, we derive linear relations relating software update decisions to the worst-case voltages and currents, leading to a decision model both tractable and more accurate than previous models based on the popular linearized DistFlow equations. Under reasonable protection assumptions, the rollout problem can be formulated as a vector bin packing problem and instances can be built and solved using scalable computations. Using realistic benchmarks including one with 10,476 buses, we demonstrate that the proposed method can generate safe and effective rollout schedules in real-time.</p
Minimum equivalent precedence relation systems
No full textIn this paper two related simplification problems for systems of linear inequalities describing precedence relation systems are considered. Given a precedence relation system, the first problem seeks a minimum equivalent subset of the precedence relations (i.e., inequalities) which has the same solution set as that of the original system. The second problem is similar to the first one, but the minimum equivalent system need not be a subset of the original system. This paper shows that the first problem is NP-hard. However, a sufficient condition is derived under which the first problem is solvable in polynomial-time. In addition, a decomposition of the first problem into independent tractable and intractable subproblems is derived. The second problem is shown to be solvable in polynomial-time, with a full parameterization of all solutions described. The results in this paper generalize those in [Moyles and Thompson 1969, Aho, Garey, and Ullman 1972] for the minimum equivalent graph problem and transitive reduction problem, which are applicable to unweighted directed graphs
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