A Distributed Energy Resources Aggregation Model Based on Multi-Scenario and Multi-Objective Methodology

Aggregation technology can integrate distributed energy resources (DERs) into resource aggregation (RA) to achieve efficient utilization of resources. This paper studies a DERs aggregation model to construct a RA. Firstly, considering the uncertainty of the output of distributed generation (DG), the characteristics of DG are analyzed and the daily eigenvalues are extracted. The contour coefficient is introduced and the improved K-means algorithm is used to cluster the daily eigenvectors to get the multiple probability scenarios in a single season. Then, in order to obtain a RA with lower daily average cost, better power generation characteristics and higher regional aggregation degree, the DERs aggregation model based on multi-scenario and multi-objective is established considering multiple constraints. To obtain a compromise optimal solution, the cellular bat algorithm based on fuzzy membership degree (FMD-CBA) is used to solve the model. Finally, the validity of the multi-scenario and multi-objective model in a single season is verified by an example.

Optimal Model for Complementary Operation of a Photovoltaic-Wind-Pumped Storage System

An optimization model for the complementary operation of a photovoltaic-wind-pumped storage system is built to make full use of solar and wind energy. Apart from ensuring the maximum economic benefit which is normally used as the only objective, the stable objectives of minimizing the output fluctuation and variation of load and output difference are added to form the multiobjective problems because of lack of study on access capacity of photovoltaic and wind power. The model aims to increase the power benefit and reduce the output fluctuation and variation of load and output difference under the constraints of station, output balance, and transmission limitation. In a case study, four schemes including single-objective independent operation, single-objective complementary operation, and multiobjective complementary operation are compared to discuss the effect of pumped storage station on economic objective and stable objectives. Furthermore, the opposite trend of the two objectives is proved and a compromise optimal solution is given. The results indicate that the pumped storage station can effectively increase power benefit and access capacity of photovoltaic and wind power. The study can provide references to the complementary optimization of the pumped storage station and the intermittent renewable energy.

TOPSIS Based Algorithm for Solving Multi-objective Multi-level Programming Problem with Fuzzy Parameters

The paper proposes TOPSIS method for solving multi-objective multi-level programming problem (MO-MLPP) with fuzzy parameters via fuzzy goal programming (FGP). At first, - cut method is used to transform the fuzzily described MO-MLPP into deterministic MO-MLPP. Then, for specific , we construct the membership functions of distance functions from positive ideal solution (PIS) and negative ideal solution (NIS) of all level decision makers (DMs). Thereafter, FGP based multi-objective decision model is established for each level DM for obtaining individual optimal solution. A possible relaxation on decisions for all DMs is taken into account for satisfactory solution. Subsequently, two FGP models are developed and compromise optimal solutions are found by minimizing the sum of negative deviational variables. To recognize the better compromise optimal solution, the concept of distance functions is utilized. Finally, a novel algorithm for MO-MLPP involving fuzzy parameters is provided and an illustrative example is solved to verify the proposed procedure.