Abstract
In the current study, the optimal performance of regional market management (RMM) is presented in one specific area of the market in order to determine the optimal demand aiming to minimize the costs of smoothing the load curve, and to implement the demand response program (DRP). In addition, the attempt has been made in this study to minimize the involuntary lost energy in terms of the initial price uncertainty and the technical constraints including the price fluctuation limits, demand ceilings and the relative risk limits. Furthermore, a market-based tensile model is presented in the form of a combination of the formulations of over lapping generations (OLG) and price elasticity (PEM) for determining demand levels in DRP. The information-gap decision theory (IGDT) is presented to model the initial price uncertainty in the above issue, according to different rates of time preference as well as the algorithm of the co-evolutionary particle swarm optimization (C-PSO). IGDT risk-aversion and risk-taking strategies help RMM to select the best strategy with the desired risk level for controlling the price uncertainty, improving the load curve, enhancing the reliability and reducing the costs.
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Abbreviations
- t :
-
Index of time
- φ peak,φ flat,φ off-peak and φ d :
-
Sets of peak load time, flat load time, off-peak load time and load
- ρ 0 (t) :
-
Initial energy price at time t ($/MWh)
- ρ 0 :
-
Initial energy price ($/MWh)
- d 0 (t) :
-
Initial demand at time t (MWh)
- d 0 :
-
Initial demand (MW)
- λ :
-
failure rate(Failure/year)
- r :
-
Average outage time (year)
- δ min,δ max :
-
Minimum and maximum value of Price fluctuation limit
- θ min,θ max :
-
Minimum and maximum value of relative risk aversion
- \(P_{grid}^{\min},P_{grid}^{\max }\) :
-
Minimum and maximum value of power purchased from the main grid
- π(t) :
-
Price purchased from the main grid at time t (MW)
- B 0 :
-
Loss coefficient parameter
- ρ 1, ρ 2 :
-
Rate of time preference after the implementation of DRP
- \(d_{peak}^0,d_{flat}^0 d_{off - peak}^0\) :
-
Energy consumption before implementing DRP during the peak, flat and off-peak hours (MWh)
- \(\begin{array}{l} {E_{peak}},{E_{flat}}\\ {E_{off - peak}} \end{array}\) :
-
Price Elasticity Matrix in the peak, flat and offpeak hours
- \(d_{peak}^0(t),d_{flat}^0(t)d_{off - peak}^0(t)\) :
-
Energy consumption before implementing DRP at time t during the peak, flat and off-peak hours (MWh)
- \({\tilde p_0}(t)\) :
-
Forecasted uncertainty variable at time t
- C b :
-
Minimum expected cost of RMM
- C r :
-
Critical cost for robustness function
- C o :
-
Critical cost for opportunity function
- μ :
-
Percentage increase in cost for RMM
- γ :
-
Percentage decrease in cost for RMM
- \(\begin{array}{l} {\rho _{peak}},{\rho _{flat}}\\ {\rho _{off - peak}} \end{array}\) :
-
Electricity price during the peak, flat and off-peak hours ($/MWh)
- ρ(t) :
-
Electricity price after implementing DRP at time t ($/MWh)
- d(t) :
-
Demand after implementing DRP at time t (MWh)
- d :
-
Demand after implementing DRP (MW)
- θ :
-
Relative risk aversion
- ENS(t) :
-
Energy not supplied at time t (MWh)
- VOLL(t) :
-
Value of the lost load at time t ($/MWh)
- A :
-
Annual outage
- Utility:
-
Utility function
- \({d_{peak}},{d_{flat}}{d_{off - peak}}\) :
-
Energy consumption after implementing DRP during the peak, flat and off-peak hours (MWh)
- P grid(t):
-
Power purchased from the main grid at time t (MW)
- P L(t) :
-
Power transmission loss at time t (MWh)
- \({B^/}\) :
-
Budget after the implementation of the DRP
- ζ:
-
Lagrange multiplier
- \(\ell\) :
-
Lagrange function
- \( \begin{gathered} \bar{\bar{d}}_{{peak}} ,\bar{\bar{d}}_{{flat}} \hfill \\ \bar{\bar{d}}_{{off - peak}} \hfill \\ \end{gathered} \) :
-
Load reduction after implementing DRP during the peak, flat and off-peak hours (MWh)
- α :
-
uncertainty radius
- \( \bar{p}_{0} (t)\) :
-
Actual uncertainty variable at time t
- C(d, p):
-
Total cost function of RMM per $
- \(\hat{\alpha }(C_{r} ) \) :
-
Robustness function
- \( \hat{\beta }(C_{o} ) \) :
-
Opportunity function
References
Yu D, Xu X, Dong M, Nojavan S, Jermsittiparsert K, Abdollahi A and Pashaei-Didani H 2020 Modeling and prioritizing dynamic demand response programs in the electricity markets. Sustain. Cities Soc. 53: 101921
Imani M H, Ghadi M J, Ghavidel S and Li L 2018 Demand response modeling in microgrid operation: a review and application for incentive-based and time-based programs. Renew. Sustain. Energy Rev. 94: 486–499
Li K, Liu L, Wang F, Wang T, Duić N, Shafie-khah M and Catalão J P 2019 Impact factors analysis on the probability characterized effects of time of use demand response tariffs using association rule mining method. Energy Convers. Manag. 197: 111891
Liu W, Huang Y, Li Z, Yang Y and Yi F 2020 Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response. Energy, 198: 117279
Nourollahi R, Nojavan S and Zare K 2020 Risk-Based Purchasing Energy for Electricity Consumers by Retailer Using Information Gap Decision Theory Considering Demand Response Exchange. Electr. Markets, pp. 135–168
Sharifi R, Anvari-Moghaddam A, Fathi S H, Guerrero J M and Vahidinasab V 2019 An optimal market-oriented demand response model for price-responsive residential consumers. Energy Efficiency 12(3): 803–815
Nwulu N I and Xia X 2015 Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs. Energy Convers. Manag. 89: 963–974
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Najafi, M., Hosseini, S.E. & Akhavein, A. Risk-based performance of regional-market management considering information gap decision theory and demand response program. Sādhanā 47, 37 (2022). https://doi.org/10.1007/s12046-021-01800-3
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DOI: https://doi.org/10.1007/s12046-021-01800-3