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⛳ 座右铭：行百里者，半于九十。

📋 📋 📋 本文目录如下： 🎁 🎁 🎁
目录
💥1 概述
📚2 运行结果
🎉3 参考文献
🌈4 Matlab代码实现

💥1 概述

能源管理系统（EMS）有助于优化微电网中分布式能源（DER）的使用，特别是在涉及可变定价和发电时。本文使用预测定价和负荷条件来优化存储/销售来自电网规模电池系统的能量。演示了两种方法：启发式状态机策略和基于线性程序的优化方法。

📚2 运行结果

for i = 1:numSim
    if i <= numOffset*numel(pvDataSet)
        heuristicCost(end+1) = out(i).logsout{1}.Values.Data(end);
    else
        optCost(end+1)= out(i).logsout{1}.Values.Data(end);
    end
end
histogram(heuristicCost); hold on;
histogram(optCost);
legend('Heuristic','Optimization');
xlabel('Cost per Day ($)'); hold off;

部分代码：

function [Pgrid,Pbatt,Ebatt] = battSolarOptimize(N,dt,Ppv,Pload,Einit,Cost,FinalWeight,batteryMinMax)

% Minimize the cost of power from the grid while meeting load with power

% from PV, battery and grid

prob = optimproblem;

% Decision variables

PgridV = optimvar('PgridV',N);

PbattV = optimvar('PbattV',N,'LowerBound',batteryMinMax.Pmin,'UpperBound',batteryMinMax.Pmax);

EbattV = optimvar('EbattV',N,'LowerBound',batteryMinMax.Emin,'UpperBound',batteryMinMax.Emax);

% Minimize cost of electricity from the grid

prob.ObjectiveSense = 'minimize';

prob.Objective = dt*Cost'*PgridV - FinalWeight*EbattV(N);

% Power input/output to battery

prob.Constraints.energyBalance = optimconstr(N);

prob.Constraints.energyBalance(1) = EbattV(1) == Einit;

prob.Constraints.energyBalance(2:N) = EbattV(2:N) == EbattV(1:N-1) - PbattV(1:N-1)*dt;

% Satisfy power load with power from PV, grid and battery

prob.Constraints.loadBalance = Ppv + PgridV + PbattV == Pload;

% Solve the linear program

options = optimoptions(prob.optimoptions,'Display','none');

[values,~,exitflag] = solve(prob,'Options',options);

% Parse optmization results

if exitflag <= 0

Pgrid = zeros(N,1);

Pbatt = zeros(N,1);

Ebatt = zeros(N,1);

else

Pgrid = values.PgridV;

Pbatt = values.PbattV;

Ebatt = values.EbattV;

end

🎉3 参考文献

部分理论来源于网络，如有侵权请联系删除。

[1]Jonathan LeSage (2023). Microgrid Energy Management System (EMS) using Optimization.

🌈4 Matlab代码实现