Optimal location and capacity planning for distributed generation with independent power production and self-generation

Abstract

10This paper proposes a planning model for power distribution companies (DISCOs) 11 to maximize profit. The model determines optimal network location and capacity for 12 renewable energy source, which are categorized as independent power production (IPP) 13 and self-generation (SG). IPP refers to generators owned by third-party investors and 14 linked to a quota obligation mechanism. SG encompasses smaller generators, supported 15 by feed-in tariffs, that produce energy for local consumption, exporting any surplus 16 generation to the distribution network. The obtained optimal planning model is able 17 to evaluate network capacity to maximize profit when the DISCO is obliged to provide 18 network access to SG and IPP. Distinct parts of the objective function, owing to the 19 definition of SG, are revenue erosion, recovery as well as the cost of excess energy. 20Together with the quota mechanism for IPP, the combination of all profit components 21 creates a connection trade-off between IPP and SG for networks with limited capacity. 22The effectiveness of the model is tested on 33-and 69-bus test distribution systems 23 and compared to standard models that maximize generation capacity with predefined 24 capacity diffusion. Simulation results demonstrate the model outperforms the standard 25 models in satisfying the following binding constraints: minimum IPP capacity and SG 26 net energy. It is further revealed that integrating SG and IPP with the proposed model 27 increases profit by up to 23.7%, adding an improvement of 8% over a feasible standard

Optimal distributed generation planning in active distribution networks considering integration of energy storage

“…However, extensive penetration of DGs greatly increases the risks of safe and economic operation of distribution networks since renewable DGs have inherently intermittent nature [5,6], which makes the planning more challenging than ever before. The traditional distribution network planning options, such as the addition or expansion of substations and lines, are unable to meet the needs of modern complex ADNs facing all alternatives together with generation and load uncertainties [6,8,9]. Therefore, it is necessary to deal with such key challenges in the issue of optimal DG placement.…”

A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems

“…Through such frameworks and processes, organisations would possess a platform that supports coherence and repeatability of analysis, irrespective of whom As impressive as the tremendous growth in the recognition of industrial CBM seems, the guidelines of the recently launched asset management standards -ISO 55000 series (initially a publicly available specification published by the British Standards Institution in 2004) in 2014 makes it crystal clear that asset performance and condition data alone are no longer sufficient for making robust MAM engineering decisions in capital intensive sectors such as power [24]. This is based on the premise that the role of MAM is changing from the classical "problem-fixer" to a very important aspect of asset life cycle management through the incorporation of the following key themes [24]: Unfortunately, despite widespread consensus that MAM is a necessity for the cost-effectiveness of any plant, some decision-makers within several organisations still view the maintenance function as a mere cost centre or necessary evil [23,24], which is perhaps why maintenance as a function has struggled to attain the same level of recognition attributed to other vital plant functions such as finance [25][26][27][28][29][30][31][32], production planning [33][34][35][36][37][38][39][40], marketing [41][42][43][44], etc. Searches within several top percentile energy-related journals clearly show a contrariety between the scanty number of academic publications advocating MAM optimisation and the abundant resources on topics such as energy policy and finance.…”

Power System Expansion Planning Incorporating Renewable Energy Technologies with Reliability Consideration: A State of Art Literature

“…The objective function is expressed in terms of costs associated with new technologies, transmission lines added and reliability subjected to mandatory and optional constraints. The analysis of GEP and are extensively done by taking various aspects into consideration [45].…”