An Optimized and Decentralized Energy Provision System for Smart Cities

Swain, Ayusee; Salkuti, Surender Reddy; Swain, K. P.

doi:10.3390/en14051451

Cited by 22 publications

(12 citation statements)

References 46 publications

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“…The mathematical formulation of ACTEP is a mixed-integer non-linear problem, and it is solved using the genetic algorithm (GA) solver. As a metaheuristic optimization technique, genetic algorithms are of great interest for solving the TEP and many other problems [4,27,[55][56][57][58]. In this study, the main problem for GA is the investment optimization that minimizes the total investment cost subject to probabilistic line loading and voltage constraints and the number of invested lines.…”

Section: Flowchart Of the Actep Problemmentioning

confidence: 99%

Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Mir

Karatepe

2022

IEEE Access

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Integrating more renewable energy sources into the grid leads to a more vulnerable power system and presents challenges for power system planners. This paper proposes a probabilistic overload constraint based AC transmission expansion planning model. In terms of economic dispatch, generation adequacy and network constraints are assessed using a probabilistic participation factor power flow. Generation participation factors, which are handled in the AC power flow equations, are used to manage mismatch power that comes from uncertainties as well as transmission loss of the system in a distributed slack bus concept. Combinations of load, wind and N-1 contingency uncertainties are evaluated with Monte Carlo Simulation and the loading limits for the existing and candidate lines and violations on bus voltages are enforced as probabilistic constraints using chance constraint programming. The investment decisions taken under various operating conditions are re-evaluated under a new set of wind power uncertainty that differs from those utilized in the optimization process, and the resulting TEP decisions are analyzed from a risk perspective. The proposed method allows for the uncertain operating conditions to be easily and accurately adapted to the ACTEP optimization. The optimization results show that the participation factor power flow is a promising tool for evaluating probabilistic operating conditions, which can be used to explore the possibility of violations under different uncertainty conditions. INDEX TERMSChance constrained programming, distributed slack bus, participation factor, transmission expansion planning, wind power. NOMENCLATURE 𝑖, 𝑘 Bus no 𝑐 Contingency 𝛽 Not overload probability 𝑁 Total number of buses Ω Total set of candidate lines Ω 𝐶 Total set of contingency 𝑃 𝐺𝑖 Real power output of a generator at bus i 𝑃 𝐷𝑖 Load at bus i 𝑃 𝐼𝑀𝐵 Imbalance power 𝐶 𝑖 Quadratic cost function of generator at bus i 𝐶 𝑖 (𝑃 𝐺𝑖 ) Total generation cost 𝑎 𝑖 , 𝑏 𝑖 , 𝑐 𝑖 Cost coefficients of generator at bus i 𝑃 𝐺𝑖_𝑠𝑐ℎ Scheduled real power output of a generator at bus i 𝑃 𝐺𝑖_𝑢𝑝𝑑 Updated real power output of a generator at bus i 𝑃𝑓 𝑖 Participation factor of generator at bus i 𝑃 𝑖 Injected active power at bus i 𝑄 𝑖 Injected reactive power at bus i 𝑃 𝑠𝑝,𝑖 Specified (known) active power at bus i 𝑄 𝑠𝑝,𝑖 Specified (known) reactive power at bus i ∆𝑃 Mismatch active power vector ∆𝑄 Mismatch reactive power vector 𝑉 𝑖 Voltage magnitude at bus i 𝜃 𝑖 Voltage angle at bus i 𝑉 𝑖 𝑐 Voltage magnitude at bus i at contingency operating condition c 𝜃 𝑖 𝑐 Voltage angle at bus i at contingency operating condition c 𝑔 𝑖𝑘 Conductance of line i-k 𝑏 𝑖𝑘 Susceptance of line i-k 𝑏 𝑖𝑘 𝑠ℎ

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Section: Flowchart Of the Actep Problemmentioning

confidence: 99%

Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Mir

Karatepe

2022

IEEE Access

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“…These problems lead to increase the overall energy of the network. Due to consumed energies in nodes and long communication distances, the network lifespan, and energy consumption and maximization; it has been a critical issue and it increases the overall energy of the network [27]. Hence, these generic schemes are not much energy efficient also do not address optimizing network and storage cost.…”

Section: Literature Surveymentioning

confidence: 99%

“…Despite, all good blockchain systems are facing scalability issues. Due to a number of scalability issues and limited on-chain storage capacity, the feasibility of such a blockchain-based data network is restricted [27]. A variety of methods have been suggested to increase scalability while maintaining decentralization and security in this regard.…”

Section: Literature Surveymentioning

confidence: 99%

Blockchain-based green big data visualization: BGbV

Shahzad

Maqbool

Rana

et al. 2021

Complex Intell. Syst.

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The progression of Internet of Things (IoT) has resulted in generation of huge amount of data. Effective handling and analysis of such big volumes of data proposes a crucial challenge. Existing cloud-based frameworks of Big Data visualization are rising costs for servers, equipment, and energy consumption. There is a need for a green solution targeting lesser cost and energy consumption with tamper-proof record-keeping, storage, and interactive visualization with only demanded data. We have proposed a Blockchain-based Green big data Visualization (BGbV) solution using Hyperledger Sawtooth for optimum utilization of organization resources. BGbV will support current distributed data visualization platforms and guarantee benefits like security and data availability with lesser storage costs. It helps reduce costs by utilizing small resources that are already available and consume less energy, making it an environmentally friendly solution.

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“…One of the major power girds that adopts this strategy is the Home microgrid (H-MG). This SG has a significant role in reducing pollution besides supporting load demand supply, specifically during peak consumption periods [1]. Usually, the generated power in the H-MGs is supplied to the consumers, if the amount of the power demand is more than the generated power, the rest of the required power could be bought from the main grid.…”

Section: Introductionmentioning

confidence: 99%

Home-Microgrid Energy Management Strategy Considering EV’s Participation in DR

et al. 2021

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Electric vehicles (EVs) have a lot of potential to play an essential role in the smart power grid. EVs not only can reduce the amount of emission yielded from fossil fuels but also can be considered as an energy storage system (ES) and a backup system. EVs could support the demand response (DR) strategy that is considered as utmost importance to shift electricity demand in peak hours. This article aims to assess the impact of the presence of EV on DR strategy in a home-microgrid (H-MG). In order to reach the optimal set point, our energy management system (EMS) has been merged with differential evolution (DE) method. The results were auspicious and showed that the proposed method could decrease market clearing price (MCP) by 26% and increase the performance of DR by 17%.

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An Optimized and Decentralized Energy Provision System for Smart Cities

Cited by 22 publications

References 46 publications

Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Stochastic AC Transmission Expansion Planning: A Chance Constrained Distributed Slack Bus Approach With Wind Uncertainty

Blockchain-based green big data visualization: BGbV

Home-Microgrid Energy Management Strategy Considering EV’s Participation in DR

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