Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program

Nojavan, Sayyad; Aalami, Habib Allah

doi:10.1016/j.enconman.2015.07.018

Cited by 121 publications

(32 citation statements)

References 41 publications

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“…Previous studies have modeled players who procure electricity from multiple sources, such as load-serving entities [2,7], electric retailers [4,5,8,15] and large consumers [3,6]. We model such a player as a "procurement agency (PA)," without loss of generality.…”

Section: Procurement Agencymentioning

confidence: 99%

“…Many previous studies have addressed the energy procurement problem (EPP), with uncertainties, of different kinds of PAs in deregulated electricity markets [2][3][4][5][6][7][8], including studies that focus on single-period markets. In the case of electricity markets, there are two major approaches used to evaluate the impact of uncertainties: a scenario-based approach and a probabilistic approach.…”

Section: Introductionmentioning

confidence: 99%

“…In the case of electricity markets, there are two major approaches used to evaluate the impact of uncertainties: a scenario-based approach and a probabilistic approach. The advantage of a scenario-based approach is that the type of optimization problem is retained, resulting in it being employed in numerous studies [2][3][4][5][6]. However, the disadvantage of the approach is that the scale of a problem becomes much larger, based on the number of scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…This is why the number of scenarios is limited. As a result, several effective methods to reduce the number of scenarios have been proposed [5,6,9,10]. Of course, it is important to eliminate unnatural scenarios that are not based on actual historical data, but instead are generated by algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

Konishi

Takahashi

2018

Energies

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Abstract:In deregulated electricity markets, minimizing the procurement costs of electricity is a critical problem for procurement agencies (PAs). However, uncertainty is inevitable for PAs and includes multiple factors such as market prices, photovoltaic system (PV) output and demand. This study focuses on settlements in multi-period markets (a day-ahead market and a real-time market) and the installation of energy storage systems (ESSs). ESSs can be utilized for time arbitrage in the day-ahead market and to reduce the purchasing/selling of electricity in the real-time market. However, the high costs of an ESS mean the size of the system needs to be minimized. In addition, when determining the size of an ESS, it is important to identify the size appropriate for each role. Therefore, we employ the concept of a "slow" and a "fast" ESS to quantify the size of a system's role, based on the values associated with the various uncertainties. Because the problem includes nonlinearity and non-convexity, we solve it within a realistic computational burden by reformulating the problem using reasonable assumptions. Therefore, this study identifies the optimal sizes of ESSs and procurement, taking into account the uncertainties of prices in multi-period markets, PV output and demand.

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Section: Procurement Agencymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

Konishi

Takahashi

2018

Energies

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“…In [13], the state of art battery energy storage technology and the methods of assessing their economic viability and their impact on power system operation have been discussed. In [14], the effect of ESS on stochastic energy procurement problem for large electricity consumers has been investigated when the defined cost function decreases. In [15], the ability of ESS to increase the amount of wind energy accepted onto a network is assessed and an analysis is conducted to determine the cost of produced energy through the ESS for a number of scenarios.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective short-term scheduling of active distribution networks for benefit maximization of DisCos and DG owners considering demand response programs and energy storage system

Abapour

Nojavan

Abapour

2017

J. Mod. Power Syst. Clean Energy

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This paper proposes a multi-objective benefit function for operation of active distribution systems considering demand response program (DRP) and energy storage system (ESS). In the active distribution system, active network management (ANM) is applied so that the distribution system equipment is controlled in real-time status based on the real-time measurements of system parameters (voltages and currents). The multi-objective optimization problem is solved using e-constraint method, and a fuzzy satisfying approach has been employed to select the best compromise solution. Two different objective functions are considered as follows: benefit maximization of distribution company (DisCo); benefit maximization of distributed generation owner (DGO). To increase the benefits and efficient implementation of distributed generation (DG), DGO has installed battery as energy storage system (ESS) in parallel with DG unit. Consequently, DGO decides for the battery charging/discharging. DisCo has the ability to exchange energy with the upstream network and DGO. Also, DisCo focuses to study the effect of demand response program (DRP) on total benefit function and consequently its influence on the load profile has been discussed. This model is successfully applied to a 33-bus radial distribution network.

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Design and performance optimization of a tri‐generation energy hub considering demand response programs

Taheri

Foroud

Jabari

2022

Energy Science & Engineering

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The design and development of renewable energy resources-based polygeneration microgrids have recently increased to supply multiple demands such as cool, heat, and power as well as mitigate pollutants improving efficiency. This paper aims to develop a combined cooling, heating, and power production network integrating photovoltaic panels (PVs), wind and gas turbines, a battery, an ice bank tank, a heater, an electrical chiller, a thermal energy storage medium. In this tri-generation facility, natural gas is utilized for district heating and fueling the gas turbine power generation cycle. The local power distribution system in combination with the output powers of PVs, wind and gas turbines is used to directly supply the electrical appliances, ice maker process, and chiller as well as charge the battery storage unit. Moreover, the air/water-cooled chiller procures the cooling flux for a benchmark microgrid. Its heating energy requirement is also provided by the gas-fired heater, the flue gases of the gas turbine, and the thermal storage medium. A mixed integer linear programming problem is coded using a generalized algebraic modeling system (GAMS) to minimize daily operating costs and emissions. Simulations are examined and analyzed over a 24-h study horizon on a sample summer day. Time-of-use energy rates and RTPs are considered two strategic demand response schemes to investigate the costeffectiveness capability of the gas-power nexus model. The proposed approach is coded using a GAMS to confirm its effectiveness and cost-environ benefits in four cases with and without heat/cool/electrical storage units considering time-of-use energy rates and real-time prices. K E Y W O R D Scombined cooling heating and power, demand response, environmental pollutions, mixedinteger linear programming, real-time pricing, time-of-use

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Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program

Cited by 121 publications

References 41 publications

Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties

Multi-objective short-term scheduling of active distribution networks for benefit maximization of DisCos and DG owners considering demand response programs and energy storage system

Design and performance optimization of a tri‐generation energy hub considering demand response programs

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