Risk-Based Performance of Combined Heat and Power Based Microgrid Using Information Gap Decision Theory

Nojavan, Sayyad; Jermsittiparsert, Kittisak

doi:10.1109/access.2020.2995260

Cited by 12 publications

(3 citation statements)

References 36 publications

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“…By presenting reliability and opportunities functions, the authors provide both RA and RS strategies to the decision makers. Reference [14] optimizes the operation of a CHP-based MG under real-time and time-of-use pricing electricity tariffs. The IGDT is proposed to deal with load uncertainty considering both RA and RS strategies.…”

Section: Literature Reviewmentioning

confidence: 99%

Information Gap Decision Theory-Based Risk-Averse Scheduling of a Combined Heat and Power Hybrid Energy System

et al. 2023

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This research investigates the optimal management of electric and heat energies in a hybrid energy system (HES). In the studied HES, a pair of photovoltaic and battery storage devices is used to supply the electricity demand, and a boiler system to supply the heat demand directly. In addition, a modified cycle power plant acted as a combined heat and power (CHP) unit to increase the generation capacity and supply reliability. The HES is also able to connect to the electric grid to exchange power according to real-time energy prices. The uncertainty of renewable generation, demand levels, and energy prices challenge the decision-making process. To deal with the uncertainty of these overlapping parameters, a comprehensive information-gap decision theory (IGDT) approach is proposed in this paper that, despite other works, considers the uncertainties in an integrated framework and derives risk-averse and risk seeker strategies in different steps. The problem is modeled as mixed-integer linear programming and solved using the GAMS optimization package. Concerning simulation results, from the viewpoint of a risk-seeking decision maker, the increment of the uncertainty degree by 10.906% results in a reduced operating cost of 8.6%. From the viewpoint of a risk-averse decision maker, the increment of the uncertainty degree by 10.208% results in 8.6% more operating cost.

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Section: Literature Reviewmentioning

confidence: 99%

Information Gap Decision Theory-Based Risk-Averse Scheduling of a Combined Heat and Power Hybrid Energy System

et al. 2023

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“…The EV minimizes the weighted average value of the objective function over all the scenarios. Reference [23] takes the decision considering either risk‐neutral, ‐taker and ‐adverse strategies. Reference [37] considers uncertainty in the wind energy production, load and market price and solve the problem using GAMS.…”

Section: Problem Formulationmentioning

confidence: 99%

Optimal investment and operation of a microgrid to provide electricity and heat

Angarita

Jafari

Mohseni

et al. 2021

IET Renewable Power Gen

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This paper proposes a robust investment and operation model to attend the power and heat needs of a microgrid (MG) connected to the distribution system. The optimization algorithm decides on the best investment and operation of combined heat and power (CHP), boilers, PV power generation and battery energy storage systems (BESS). For the BESS, the algorithm estimates the optimal energy storage capacity (MWh) as well as the maximum hourly delivery capacity (MW). The non-linear and non-concave heat rate chart is recast by a mix-integer linear model to have a tractable and precise model. The model considers the uncertain in some parameters using probability density function (pdf) to portrait its behavior. Thus, the problem has been modeled using stochastic programming approach, and its objective function is the expected value of the annual operational cost. The model is tested using a real case where two adjacent consumers share the power and heat facilities to minimize the overall up to 17% depending on the gas price scenario. The results demonstrate the benefits of employing different technologies and the synergies of all technologies operating together.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…In this regard, Combined Heat and Power Economic Dispatch (CHPED) is considered an important optimization problem for determining the optimal output of power and the heat of each unit in order to minimize the production costs considering the system constraints. In other words, it can be said that the RMM uses CHPED to settle the leading day market [3]. On the other hand, increasing energy on the demand side increases the daily load curve, overloads transmission lines, causes unpredictable accidents, and leads to system instability and a sharp rise in electricity prices.…”

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confidence: 99%

Day-Ahead Scheduling for Economic Dispatch of Combined Heat and Power With Uncertain Demand Response

et al. 2022

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This paper presents an energy management method for the interconnected operation of power, heat, Combined Heat and Power (CHP) units to settle the Day-Ahead market in the presence of a demand response program (DRP). A major challenge in this regard is the price uncertainty for DRP participants. First, the definitive model of the problem is introduced from the perspective of the Regional Market Manager (RMM) in order to minimize the total supply cost in the presence of TOU program, which is a type of DRP. Furthermore, a market-oriented tensile model is presented in the form of a combination of over-lapping generations (OLG) and price elasticity (PE) formulations to determine the amount of electricity demand in the TOU program. Then, a price uncertainty model of the proposed problem is introduced according to the IGDT risk aversion and risk-taking strategies considering information gap decision theory (IGDT). The above problem is solved through the use of the co-evolutionary particle swarm optimization (C-PSO) algorithm and the proposed model is implemented on a standard seven-unit system for a period of 24 hours. INDEX TERMSCombined heat and power, time of use, diamond's OLG model, price uncertainty, information gap decision theory, co-evolutionary particle swarm optimization. NOMENCLATURE SETS AND INDEX t, i, j, k Index of time, power-only, CHP and heat-only units, respectively ϕ peak, ϕ flat, ϕ off −peak ϕ T Sets of peak load time, flat load time, off-peak load time and load time, respectively ϕ d Set of Power demand ϕ NP, ϕ NC, ϕ Nh Sets of power-only, CHP and heat-only units, respectively CONSTANTS b i , C i , d i , e i , f i cost coefficients for ith power-only unit N P , N C , N h Total number of power-only, CHP and heat-only units, respectivelyThe associate editor coordinating the review of this manuscript and approving it for publication was Frederico Guimarães .

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Risk-Based Performance of Combined Heat and Power Based Microgrid Using Information Gap Decision Theory

Cited by 12 publications

References 36 publications

Information Gap Decision Theory-Based Risk-Averse Scheduling of a Combined Heat and Power Hybrid Energy System

Information Gap Decision Theory-Based Risk-Averse Scheduling of a Combined Heat and Power Hybrid Energy System

Optimal investment and operation of a microgrid to provide electricity and heat

Day-Ahead Scheduling for Economic Dispatch of Combined Heat and Power With Uncertain Demand Response

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