Participation of responsive electrical consumers in load smoothing and reserve providing to optimize the schedule of a t
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Participation of responsive electrical consumers in load smoothing and reserve providing to optimize the schedule of a typical microgrid AA Nazari1 · Reza Keypour1 Received: 4 December 2018 / Accepted: 18 July 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract The task of energy management in electrical microgrids (MGs) is facing more difficulties with the integration of different schedulable components, e.g. responsive loads, energy storage systems (ESSs) and variety of generating units. In this paper the formulation of generation scheduling for a typical MG is done by the unit commitment problem (UCP) to minimize costs and emissions. Demand response program (DRP) is utilized to achieve two goals, i.e. to reshape and smooth the load profile, and also for providing reserve capacity along with dispatchable units. The aforementioned tasks are carried out by differential evolution (DE) algorithm which is a simple and powerful optimizer. In order to deal with multiple criteria decision making in the energy management problem, an algorithm called fuzzified modified (FM) ε-constraint is proposed as a non-Pareto based multi-objective solver. The optimal scheduling plan tends to benefit from different electricity prices in day-ahead market and also from the ESS to achieve optimal scheduling results. It is shown that in single objective cases, committing less generating units simultaneously is favorable, as opposed to multi-objective one in which more available units are tuned on at a lower generating power. Meanwhile in all cases, the responsive loads are mostly aggregated in off-peak periods to help peak load shaving. Finally it is verified that the proposed multi-objective approach is able to find an intermediate solution between the two conflicting functions so that as a trade-off each objective is optimized to some extent. Keywords Microgrid energy management · Demand response program · Reserve scheduling · Unit commitment problem
* Reza Keypour [email protected] AA Nazari [email protected] 1
Faculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran
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List of symbols Indices i DG index j Shiftable load index t Hourly interval index ( h) m Objective function index Parameters NDG Number of dispatchable units NSL Number of shiftable loads T Number of scheduling intervals ( h) Ndim Number of decision variables M Number of objective functions NPop Number of individuals in the population iterMax Number of maximum allowed iterations ri Cost of reserve provision for ith dispatchable unit ($/kW) scci Startup cost of ith dispatchable unit ($) ai , bi , ci Generation cost coefficients of ith dispatchable unit 𝛼i , 𝛽i , 𝛾i Generation emission coefficients of ith dispatchable unit seci Startup emission production of ith dispatchable unit (kg) Grt Day-ahead market price at tth interval ($/kW) gec Up-stream grid emission coefficient (kg/kW) bes BESS emission coefficient (kg/kW) 𝜂dis BESS discharge eff
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