Desain Pump Storage Power Plant (PSPP) dari Pembangkit Tenaga Surya dengan Studi Kasus Embung ITERA

Pump Storage Power Plant (PSPP) merupakan alternatif penyimpanan energi potensial yang dimanfaatkan kembali sesuai dengan kebutuhan. Aplikasinya dapat dilakukan pada waduk atau reservoir yang lebih tinggi dengan inputan air waduk yang lebih rendah ataupun sumber lain. Disain PSPP disesuaikan dengan kapasitas upper reservoir, daya desain dan waktu pembangkitan. Pompa untuk menaikkan air dari lower reservoir dapat dihidupkan menggunakan sumber energi terbarukan berupa Photo Voltaic (PV). Keluaran PV tetap disimpan di baterai untuk mendapatkan tegangan dan arus yang stabil sebagai input pompa. Rancangan PSPP pada Embung ITERA memiliki effisiensi pembangkitan 80%, sedangkan effisiensi PV sebesar 87 %

Computational and Near-Optimal Trade-Offs in Renewable Electricity System Modelling

In the decades to come, the European electricity system must undergo an unprecedented transformation to avert the devastating impacts of climate change. To devise various possibilities for achieving a sustainable yet cost-efficient system, in the thesis at hand, we solve large optimisation problems that coordinate the siting of generation, storage and transmission capacities. Thereby, it is critical to capture the weather-dependent variability of wind and solar power as well as transmission bottlenecks. In addition to modelling at high spatial and temporal resolution, this requires a detailed representation of the electricity grid. However, since the resulting computational challenges limit what can be investigated, compromises on model accuracy must be made, and methods from informatics become increasingly relevant to formulate models efficiently and to compute many scenarios. The first part of the thesis is concerned with justifying such trade-offs between model detail and solving times. The main research question is how to circumvent some of the challenging non-convexities introduced by transmission network representations in joint capacity expansion models while still capturing the core grid physics. We first examine tractable linear approximations of power flow and transmission losses. Subsequently, we develop an efficient reformulation of the discrete transmission expansion planning (TEP) problem based on a cycle decomposition of the network graph, which conveniently also accommodates grid synchronisation options. Because discrete investment decisions aggravate the problem\u27s complexity, we also cover simplifying heuristics that make use of sequential linear programming (SLP) and retrospective discretisation techniques. In the second half, we investigate other trade-offs, namely between least-cost and near-optimal solutions. We systematically explore broad ranges of technologically diverse system configurations that are viable without compromising the system\u27s overall cost-effectiveness. For example, we present solutions that avoid installing onshore wind turbines, bypass new overhead transmission lines, or feature a more regionally balanced distribution of generation capacities. Such alternative designs may be more widely socially accepted, and, thus, knowing about these degrees of freedom is highly policy-relevant. The method we employ to span the space of near-optimal solutions is related to modelling-to-generate-alternatives, a variant of multi-objective optimisation. The robustness of our results is further strengthened by considering technology cost uncertainties. To efficiently sweep the cost parameter space, we leverage multi-fidelity surrogate modelling techniques using sparse polynomial chaos expansion in combination with low-discrepancy sampling and extensive parallelisation on high-performance computing infrastructure

Electric Generation Expansion Analysis System a progress report on RPI 1529

The long and short term behavior of light water reactor stainless steel clad fuel has been investigated in order to establish more adequate or applicable operation/design criteria. The performance record of stainless steel clad fuel used in both the Connecticut Yankee and San Onofre 1 power stations has remained essentially unmarred until the recent past. While the San Onofre 1 plant has maintained this record, the Connecticut Yankee station has experienced a number of fuel element failures since 1977. Consequently, emphasis has been placed on cladding behavior for anomalous operation experienced by the Connecticut Yankee reactor prior to its first observed coolant activity increase.In order to predict cladding behavior, a fuel performance code (STRESS) has been developed with the capabilities of analyzing long term cladding creepdown behavior, cladding conditioning, and behavior during up-power ramping and power maneuvers. The effects of varied fill gas pressure and cladding creep rate on the stress/deformation behavior of stainless steel cladding for these performance areas have been investigated. Similar calculations are also performed for Zircaloy clad fuel so that a comparison can be made between these materials. Code limitations are discussed and some methods which compensate for insufficient modeling are reviewed.Fuel element design and reactor operation recommendations are made for Connecticut Yankee (and San Onofre 1) stainless steel clad fuel. These include fill gas pressurization level, up-power ramp rate limitations, and possible cladding material preference. These recommendations are based on the results of the STRESS code and the trends which may be inferred from them

A review of co-optimization approaches for operational and planning problems in the energy sector

This paper contributes to a comprehensive perspective on the application of co-optimization in the energy sector – tracking the frontiers and trends in the field and identifying possible research gaps – based on a systematic literature review of 211 related studies. The use of co-optimization is addressed from a variety of perspectives by splitting the studies into ten key categories. Research has consistently shown that co-optimization approaches can be technically challenging and it is usually a data-intensive procedure. Overall, a set of techniques such as relaxation, decomposition and linear approaches have been proposed for reducing the inherent nonlinear model's complexities. The need to coordinate the necessary data from multiples actors might increase the complexity of the problem since security and confidentiality issues would also be put on the table. The evidence from our review seems to suggest a pertinent role for addressing real-case systems in future models instead of using theoretical test cases as considered by most studies. The identified challenges for future co-optimization models include (i) dealing with the treatment of uncertainties and (ii) take into account the trade-offs among modelling fidelity, spatial granularity and geographical coverage. Although there is also a growing body of literature that recognizes the importance of co-optimization focused on integrating supply and demand-side options, there has been little work in the development of co-optimization models for long-term decision-making, intending to recognize the impact of short-term variability of both demand and RES supply and well suited to systems with a high share of RES and under different demand flexibility conditions. The research results represent a further step towards the importance of developing more comprehensive approaches for integrating short-term constraints in future co-optimized planning models. The findings provide a solid evidence base for the multi-dimensionality of the co-optimization problems and contriThis work is supported by the National Council for Scientific and Technological Development (CNPq), Brazil. This work has been supported by FCT – Fundaça˜o para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Power System Planning in Disparate Systems: Modeling Sustainability and Electricity Access

Electricity goals around the world tend to focus on increasing social benefit through one of two avenues: (1) increasing overall system sustainability or (2) increasing access to electricity. These goals guide the transition of the power system. In pursuit of these goals decision makers will need modeling tools that can inform decisions, in a way that is flexible enough to include a wide range of preferences and goals. It is clear that the future generation mix of the power system will change, but the most sustainable solution, will change based on a country\u27s goals. This dissertation will explore the various options for power grid expansion in disparate electricity systems. We present three essays that focus on evaluating the sustainability of different electricity futures to allow decision makers to understand impacts and trade-offs between various combinations of power generating technologies. The first two essays are focused on evaluating the sustainability of generation mixes for New England. In the first essay we take a multi-model approach, first determining the reliability of the system overall, then evaluating different generation portfolios based on seven sustainability criteria. In the second essay we expand this work by implementing pumped hydro storage into the model. The sustainability of the system with and without storage capabilities is presented and evaluated. The third essay focuses on the UN Sustainable Development Goals, and electricity access in developing countries. Here we present a model that can be used by decision makers in developing countries to determine the best method of grid expansion to meet electricity access goal

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods

系統電力の安定化と炭素排出削減に焦点を当てた分散型エネルギーシステムの多基準評価に関する研究

Distributed energy systems can save energy cost, reduce environmental impact and improve the reliability of the power grid. However, its high investment and improper capacity caused poor economic benefits. Moreover, the current evaluation method with a single criterion is relatively simple and one-sided, which cannot reflect the comprehensive benefits of the DES. Therefore, this research proposed a distributed energy system (DES) composed of photovoltaic, energy storage and gas engine, and its grid stabilization and carbon reduction potentials were analyzed. Focusing on these advantages, a multi-criteria evaluation method was established to optimize the system. Finally, different case study scenarios of the DES utilization were demonstrated. It is hoped to improve the core competitiveness of the DES and promote its development.北九州市立大