Proceedings of the Eleventh ACM International Conference on Future Energy Systems最新文献_第8页

Long-term electricity market agent based model validation using genetic algorithm based optimization 基于长期电力市场代理的模型验证，采用基于遗传算法的优化

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-05-17 DOI: 10.1145/3396851.3397682

Alexander J. M. Kell, M. Forshaw, S. McGough

{"title":"Long-term electricity market agent based model validation using genetic algorithm based optimization","authors":"Alexander J. M. Kell, M. Forshaw, S. McGough","doi":"10.1145/3396851.3397682","DOIUrl":"https://doi.org/10.1145/3396851.3397682","url":null,"abstract":"Electricity market modelling is often used by governments, industry and agencies to explore the development of scenarios over differing timeframes. For example, how would the reduction in cost of renewable energy impact investments in gas power plants or what would be an optimum strategy for carbon tax or subsidies? Cost optimization based solutions are the dominant approach for understanding different long-term energy scenarios. However, these types of models have certain limitations such as the need to be interpreted in a normative manner, and the assumption that the electricity market remains in equilibrium throughout. Through this work, we show that agent-based models are a viable technique to simulate decentralised electricity markets. The aim of this paper is to validate an agent-based modelling framework to increase confidence in its ability to be used in policy and decision making. Our framework can model heterogeneous agents with imperfect information. The model uses a rules-based approach to approximate the underlying dynamics of a real world, decentralised electricity market. We use the UK as a case study, however, our framework is generalisable to other countries. We increase the temporal granularity of the model by selecting representative days of electricity demand and weather using a k-means clustering approach. We show that our framework can model the transition from coal to gas observed in the UK between 2013 and 2018. We are also able to simulate a future scenario to 2035 which is similar to the UK Government, Department for Business and Industrial Strategy (BEIS) projections. We show a more realistic increase in nuclear power over this time period. This is due to the fact that with current nuclear technology, electricity is generated almost instantaneously and has a low short-run marginal cost [13].","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123662311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Energy Storage as Public Asset 作为公共资产的能源储存

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-05-04 DOI: 10.1145/3396851.3397760

Jiasheng Zhang, Nan Gu, Chenye Wu

引用次数: 3

A Flexible Storage Model for Power Network Optimization 电网优化中的柔性存储模型

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-04-29 DOI: 10.1145/3396851.3402121

F. Geth, Carleton Coffrin, D. Fobes

引用次数: 6

Energy Storage Optimization for Grid Reliability 电网可靠性的储能优化

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-04-19 DOI: 10.1145/3396851.3402123

Md Umar Hashmi, Deepjyoti Deka, Lucas Pereira, A. Bušić

{"title":"Energy Storage Optimization for Grid Reliability","authors":"Md Umar Hashmi, Deepjyoti Deka, Lucas Pereira, A. Bušić","doi":"10.1145/3396851.3402123","DOIUrl":"https://doi.org/10.1145/3396851.3402123","url":null,"abstract":"Large scale renewable energy source (RES) integration planned for multiple power grids around the world will require additional resources/reserves to achieve secure and stable grid operations to mitigate the inherent intermittency of RES. In this paper, we present formulations to understand the effect of fast storage reserves in improving grid reliability under different cost functions. Our formulations not only aim to minimize imbalance but also maintain state-of-charge (SoC) of storage. The proposed approaches rely on a macroscopic supply-demand model of the grid with total power output of energy storage as the control variable. We show that accounting for system response due to inertia and local governor response enables a more realistic quantification of storage requirements for damping net load fluctuations. Simulation case studies are embedded in the paper by using datasets from the Elia TSO in Belgium and BPA in the USA. The numerical results benchmark the marginal effect on reliability due to increasing storage size under different system responses and associated cost functions. Further we observe myopic control of batteries proposed approximates deterministic control of batteries for faster time scale reserve operation.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115944641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transmission Expansion Planning Using Cycle Flows 使用循环流的输电扩展规划

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-04-18 DOI: 10.1145/3396851.3397688

Fabian Neumann, T. Brown

{"title":"Transmission Expansion Planning Using Cycle Flows","authors":"Fabian Neumann, T. Brown","doi":"10.1145/3396851.3397688","DOIUrl":"https://doi.org/10.1145/3396851.3397688","url":null,"abstract":"The common linear optimal power flow (LOPF) formulation that underlies most transmission expansion planning (TEP) formulations uses bus voltage angles as auxiliary optimization variables to describe Kirchhoff's voltage law. As well as introducing a large number of auxiliary variables, the angle-based formulation has the disadvantage that it is not well-suited to considering the connection of multiple disconnected networks. It is, however, possible to circumvent these variables and reduce the required number of constraints by expressing Kirchhoff's voltage law directly in terms of the power flows, based on a cycle decomposition of the network graph. For generation capacity expansion with multi-period LOPF, this equivalent reformulation was shown to reduce solving times by an order of magnitude. Allowing line capacity to be co-optimized in a discrete TEP problem makes it a non-convex mixed-integer problem. This paper develops a novel cycle-based reformulation for the TEP problem with LOPF and compares it to the standard angle-based formulation. The combinatorics of the connection of multiple disconnected networks is formalized for both formulations, a topic which has not received attention in the literature. The cycle-based formulation is shown to conveniently accommodate synchronization options. Since both formulations use the big-M disjunctive relaxation, useful derivations for suitable big-M values are provided. The competing formulations are benchmarked on a realistic generation and transmission expansion model of the European transmission system at varying spatial and temporal resolutions. The cycle-based formulation solves up to 31 times faster for particular cases, while averaging at a speed-up of factor 4.","PeriodicalId":442966,"journal":{"name":"Proceedings of the Eleventh ACM International Conference on Future Energy Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115510593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Market Power in Convex Hull Pricing 凸包定价中的市场力量

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2020-02-15 DOI: 10.1145/3396851.3403510

Jian Sun, Chenye Wu

引用次数: 1

Optimal Storage Control for Dynamic Pricing 动态定价的最优存储控制

Proceedings of the Eleventh ACM International Conference on Future Energy Systems Pub Date : 2019-11-16 DOI: 10.1145/3396851.3403507

Jiaman Wu, Zhiqi Wang, Yang Yu, Chenye Wu

引用次数: 3