Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects

Somma, Marialaura Di; Graditi, Giorgio; Heydarian‐Forushani, Ehsan; Shafie‐khah, Miadreza; Siano, Pierluigi

doi:10.1016/j.renene.2017.09.074

Cited by 216 publications

(102 citation statements)

References 50 publications

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“…Moreover, authors also discuss the implementation of proposed algorithms and challenges related to its implementation. Di Somma et al in [22], present stochastic programming model for the optimal scheduling of distributed energy resources system. The main aim of the study is to reduce energy cost and CO 2 emission while, satisfying time-varying user demand.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

Hussain¹,

et al. 2018

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Abstract:The traditional power grid is inadequate to overcome modern day challenges. As the modern era demands the traditional power grid to be more reliable, resilient, and cost-effective, the concept of smart grid evolves and various methods have been developed to overcome these demands which make the smart grid superior over the traditional power grid. One of the essential components of the smart grid, home energy management system (HEMS) enhances the energy efficiency of electricity infrastructure in a residential area. In this aspect, we propose an efficient home energy management controller (EHEMC) based on genetic harmony search algorithm (GHSA) to reduce electricity expense, peak to average ratio (PAR), and maximize user comfort. We consider EHEMC for a single home and multiple homes with real-time electricity pricing (RTEP) and critical peak pricing (CPP) tariffs. In particular, for multiple homes, we classify modes of operation for the appliances according to their energy consumption with varying operation time slots. The constrained optimization problem is solved using heuristic algorithms: wind-driven optimization (WDO), harmony search algorithm (HSA), genetic algorithm (GA), and proposed algorithm GHSA. The proposed algorithm GHSA shows higher search efficiency and dynamic capability to attain optimal solutions as compared to existing algorithms. Simulation results also show that the proposed algorithm GHSA outperforms the existing algorithms in terms of reduction in electricity cost, PAR, and maximize user comfort.

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Section: Introductionmentioning

confidence: 99%

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

Hussain¹,

et al. 2018

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“…Energy networks, where energy providers and consumers with diverse patterns are mixed, have significant variability and fluctuation. This indicates uncertainty of demand and supply [25]. The ideal energy network needs to balance demand and supply, and has low uncertainty and complexity.…”

Section: Introductionmentioning

confidence: 99%

Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home

et al. 2018

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Abstract:As energy issues are emerging around the world, a variety of smart home technologies aimed at realizing zero energy houses are being introduced. Energy storage system (ESS) for smart home energy independence is increasingly gaining interest. However, limitations exist in that most of them are controlled according to time schedules or used in conjunction with photovoltaic (PV) generation systems. In consideration of load usage patterns and PV generation of smart home, this study proposes an ESS control algorithm that uses constant energy of energy network while making maximum use of ESS. Constant energy means that the load consumes a certain amount of power under all conditions, which translates to low variability. The proposed algorithm makes a smart home a load of energy network with low uncertainty and complexity. The simulation results show that the optimal ESS operating target power not only makes the smart home use power constantly from the energy network, but also maximizes utilization of the ESS. In addition, since the smart home is a load that uses constant energy, it has the advantage of being able to operate an efficient energy network from the viewpoint of energy providers.

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“…In ref. [30], the uncertainties both of the demand side and the supply side are considered in the optimal operation scheduling of a comprehensive distributed energy resources system. On the other hand, with the development of renewable energy output forecasting technology, the convenience of dispatch is also significantly increased.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

et al. 2018

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Abstract:In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM) and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP), and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL), are still imperfect, which make it difficult for the active distribution network (ADN) to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

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Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects

Cited by 216 publications

References 50 publications

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

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