Probability-Interval based Optimal Planning of Integrated Energy System with Uncertain Wind Power

Li, Zhe; Wang, Chengfu; Li, Bowen; Wang, Jinyu; Zhao, Penghui; Wen-li, Zhu; Yang, Ming; Ding, Ying

doi:10.1109/icps.2019.8733343

Cited by 10 publications

(9 citation statements)

References 29 publications

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“…The PHES unis can provide sufficient ramp-capability reserves with the advantage of short start-up/shut-down times and no minimum up/downtimes. As formulated in (16), the generating-pumping mutual exclusion constraint ensures that PHES units cannot be in the generating and pumping status simultaneously. The power output of PHES units is limited by constraints (17) and (18).…”

Section: Phes Units Operation Constraintsmentioning

confidence: 99%

“…The conditional value-at-risk (CVaR) method as an effective method to cope with the uncertainty of renewable energy has been applied to the power system optimization problem [15][16][17][18]. In [15], the flexible look-ahead dispatch model based on the CVaR method was proposed, and an index CVaR-WP was introduced to evaluate the risk of wind power accommodation.…”

Section: Introductionmentioning

confidence: 99%

“…The results indicated that the CVaR method could avoid the over‐conservativeness of traditional RO. In [16], the CVaR method was used to express the uncertainties of wind power in an IES planning model and transformed the stochastic probability model of wind power to a determinate expression. Compared with the SO approach, the CVaR method did not require an accurate forecast power value and reduced the computational burden.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

CVaR‐based generation expansion planning of cascaded hydro‐photovoltaic‐pumped storage system with uncertain solar power considering flexibility constraints

Huang

Liu

et al. 2021

IET Generation Trans & Dist

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The development of a high solar energy penetrated power system requires considerable flexibility to hedge the risk of solar power curtailment and power shortage. This paper explores how the generation portfolio of cascaded hydro-photovoltaic-pumped storage (CH-PV-PS) generation system will be appropriately designed to balance the overall planning costs and operational flexibility constraints. The proposed study relies on the generation expansion planning (GEP) model of the CH-PV-PS system, considering a full set of flexibility constraints. An index designated ramp-capability reserve shortage (RCRS) based on the conditional value at risk (CVaR) method is introduced to quantify the risk of solar power and load uncertainty. The piecewise linearization method and triangle method are developed to accommodate the non-linear terms in the proposed model. Finally, the case studies are conducted to demonstrate the applicability and effectiveness of the proposed model.

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Section: Phes Units Operation Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

CVaR‐based generation expansion planning of cascaded hydro‐photovoltaic‐pumped storage system with uncertain solar power considering flexibility constraints

Huang

Liu

et al. 2021

IET Generation Trans & Dist

View full text Add to dashboard Cite

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“…The increasing penetration of renewable energy sources is leading to major changes in power and energy systems all around the world [1]. The importance of consumers is increasing in this context, as they provide the potential to balance the variation of renewable-based generation through consumption, or demand-side flexibility, e.g.…”

Section: Introductionmentioning

confidence: 99%

Consumer Flexibility Aggregation Using Partition Function Games With Non-Transferable Utility

2021

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This paper explores the aggregation of electricity consumers flexibility. A novel coalitional game theory model for partition function games with non-transferable utility is proposed. This model is used to formalize a game in which electricity consumers find coalitions among themselves in order to trade their consumption flexibility in the electricity market. Utility functions are defined to enable measuring the players preferences. Two case studies are presented, including a simple illustrative case, which assesses and explains the model in detail; and a large-scale scenario based on real data, comprising more than 20,000 consumers. Results show that the proposed model is able to reach solutions that are more suitable for the consumers when compared to the solutions achieved by traditional aggregation techniques in power and energy systems, such as clustering-based methodologies. The solutions found by the proposed model consider the perspectives from all players involved in the game and thus are able to reflect the rational behaviour of the involved players, rather than imposing an aggregation solution that is only beneficial from the perspective of the aggregator.

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“…Energy industry is looking for an energy system, to realize low‐carbon, safe and efficient energy production and consumption mode. In this respect, integrated energy system (IES) has received extensive attention, which can effectively improve energy utilization efficiency, reduce energy cost, and promote energy market competition 3‐5 . IES, as a common carrier in Energy Internet, equips various energy stations for meeting multi‐energy demand of initial consumers, such as CCHP (combined cooling, heating, and power) station, gas boiler station.…”

Section: Introductionmentioning

confidence: 99%

A stackelberg game approach for heterogeneous energy market in integrated energy system

2020

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With the increasing demand of energy and the growing intensity of energy crisis, various smart energy systems are developed on the distribution level, such as integrated energy system (IES). In this article, a trading mechanism among various energy retailers and consumers is designed under the open market environment. The trading problem is formulated as a multi‐leader and multi‐follower Stackelberg game, which is built with the strategy set of energy bidding price and purchasing pattern. In particular, consumer's demand is described with the price elasticity property of demand, and non‐cooperative competition behavior among retailers is analyzed mathematically. To implement the proposed game approach, a distributed algorithm is presented by combining particle swarm optimization (PSO) and interior point method (IPM). Finally, simulation results show that the proposed trading mechanism will contribute to the development of heterogeneous energy market and the overall profit of retailers in the traditional trading mechanism is 37.8% lower than the profit in the proposed mechanism.

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Probability-Interval based Optimal Planning of Integrated Energy System with Uncertain Wind Power

Cited by 10 publications

References 29 publications

CVaR‐based generation expansion planning of cascaded hydro‐photovoltaic‐pumped storage system with uncertain solar power considering flexibility constraints

CVaR‐based generation expansion planning of cascaded hydro‐photovoltaic‐pumped storage system with uncertain solar power considering flexibility constraints

Consumer Flexibility Aggregation Using Partition Function Games With Non-Transferable Utility

A stackelberg game approach for heterogeneous energy market in integrated energy system

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