Power System Resource Expansion Planning
원문 초록
Power System Resource Planning is the recurrent process of studying and determining what facilities and procedures should be provided to satisfy and promote appropriate future demands for electricity. The electric power system as planned should meet or balance societal goals. These include availability of electricity to all potential users at lowest possible cost, minimum environmental damage, high levels of safety and reliability, etc. Plans should be technically and financially feasible. Plans also should achieve the objectives the entity doing the planning, including minimizing risk. The emergence of meta-heuristics has given robustness to the non-analytical methods, because of the rationale behind them. Besides, evolutionary algorithms have provided a higher degree of confidence in a stochastic convergence to optimum and have supported this confidence with a mathematical background explaining not only how they achieve convergence but also how to improve the convergence rate. The present work of analyses and implementation can be divided into: i) Transmission Constrained Generation Expansion Planning (TC GEP), ii) Composite Generation Expansion and Transmission Network Expansion Planning (GEP TNEP), iii) Transmission Network Expansion (TNEP) Planning using AC model, iv) Composite Transmission Network Expansion Planning (TNEP) and Reactive Power Expansion Planning (RPP) and v) Transmission Network Planning using Interior-Point Method (IP TNEP).
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback
Benchmarking MOEAs for solving continuous multi-objective RL problems
Mergenetic: a Simple Evolutionary Model Merging Library
Evolutionary thoughts: integration of large language models and evolutionary algorithms
RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search
토론
이 논문과 연결된 포럼 글이 아직 없습니다.