{ "cells": [ { "cell_type": "markdown", "id": "7b46932b-0457-4480-9fea-3d17013c0fd6", "metadata": {}, "source": [ "# Unit Commitment\n", "\n", "The Unit Commitment problem is a fundamental problem in power systems. It is the scheduling of generators, in other words the decision if a unit is on or off for any given time in the planning horizon. The Unit Commitment includes constraints like capacity limits, ramping limitations, minimum runtimes, and minimum downtimes. The Security Constraint Unit Commitment also includes the system reserve requirements and network constraints." ] }, { "cell_type": "markdown", "id": "180c15cd-2425-48c1-a4f1-000711a98a49", "metadata": {}, "source": [ "**1. Load packages and useful definitions**\n", " - We are using the gurobipy package to formulate a mathematical model and solve it. " ] }, { "cell_type": "code", "execution_count": 4, "id": "971ac546-2b06-4b5b-b94b-14d9a5bd160a", "metadata": {}, "outputs": [], "source": [ "# import required packages\n", "\n", "import pandas as pd\n", "import numpy as np\n", "import math\n", "\n", "import gurobipy as gp\n", "from gurobipy import GRB\n", "\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 5, "id": "5738bd6c-0616-4a10-b4be-471c331bb6b5", "metadata": {}, "outputs": [], "source": [ "# some helpful definitions\n", "\n", "gen_colors = {\n", " \"Hydro\": \"#1f78b4\", # Deep Blue\n", " \"Nuclear\": \"#e31a1c\", # Red\n", " \"Coal\": \"#8b4513\", # Dark Brown\n", " \"Gas CC\": \"#8e44ad\", # Medium Purple\n", " \"Gas CT\": \"#a569bd\", # Light Purple\n", " \"Oil CT\": \"#4d4d4d\", # Dark Gray\n", " \"Wind\": \"#6baed6\", # Light Sky Blue\n", " \"PV\": \"#ff7f00\", # Bright Orange\n", " \"Storage\": \"#33a02c\" # Green\n", "}\n", "\n", "def print_gp_status(m):\n", " status = m.Status\n", " if status == GRB.OPTIMAL:\n", " print(\"The model is optimal.\")\n", " elif status == GRB.INFEASIBLE:\n", " print(\"The model is infeasible.\")\n", " elif status == GRB.UNBOUNDED:\n", " print(\"The model is unbounded.\")\n", " else:\n", " print(f\"Optimization ended with status {status}.\")\n", " print()\n", " return status" ] }, { "cell_type": "markdown", "id": "1fd2d996-30ee-415b-886e-fc65b8f2b866", "metadata": {}, "source": [ "**2. Read and prepare data**\n", "- The data we have are the various generator units.\n", "- It includes the unit type and the corresponding cost, startup cost and variable cost.\n", "- It also includes technical limitations like the installed amount, minimum generation levels, ramping rates, minimum down time and minimum up time (minimum run time). " ] }, { "cell_type": "code", "execution_count": 6, "id": "b41aa009-d7fb-4034-87e7-ea6da2f46552", "metadata": {}, "outputs": [], "source": [ "# read the data\n", "data_file = \"ts_and_gen_scuc.xlsx\"\n", "load_and_res_data = pd.read_excel(data_file, sheet_name=0)\n", "gen_data = pd.read_excel(data_file, sheet_name=1)" ] }, { "cell_type": "code", "execution_count": 7, "id": "4b21208e-1f61-4a56-8e6e-59485292ebe3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Gen IDUnit TypeSU cost $Variable Cost USD/MWhInstalled in MWPMin in MWRamp Rate in MW /hrMin Down Time HrMin Up Time HrSR eligible
0N1Nuclear70.0340030030048240
1N2Nuclear70.0340030030048240
2O1Oil CT0.550401050111
3O2Oil CT0.550401050111
4O3Oil CT0.550401050111
\n", "
" ], "text/plain": [ " Gen ID Unit Type SU cost $ Variable Cost USD/MWh Installed in MW \\\n", "0 N1 Nuclear 70.0 3 400 \n", "1 N2 Nuclear 70.0 3 400 \n", "2 O1 Oil CT 0.5 50 40 \n", "3 O2 Oil CT 0.5 50 40 \n", "4 O3 Oil CT 0.5 50 40 \n", "\n", " PMin in MW Ramp Rate in MW /hr Min Down Time Hr Min Up Time Hr \\\n", "0 300 300 48 24 \n", "1 300 300 48 24 \n", "2 10 50 1 1 \n", "3 10 50 1 1 \n", "4 10 50 1 1 \n", "\n", " SR eligible \n", "0 0 \n", "1 0 \n", "2 1 \n", "3 1 \n", "4 1 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspect the data\n", "gen_data.head()" ] }, { "cell_type": "code", "execution_count": 8, "id": "b74c1af3-6b04-450a-b295-83074006ddaf", "metadata": {}, "outputs": [], "source": [ "# prepare data for scuc\n", "\n", "# generator data\n", "gen_id = gen_data['Gen ID'].to_numpy()\n", "gen_type = gen_data['Unit Type'].to_numpy()\n", "mc = gen_data['Variable Cost USD/MWh'].to_numpy()\n", "Pmax = gen_data['Installed in MW'].to_numpy()\n", "R60 = gen_data['Ramp Rate in MW /hr'].to_numpy()\n", "# new:\n", "su_cost = gen_data['SU cost $'].to_numpy()\n", "Pmin = gen_data['PMin in MW'].to_numpy()\n", "min_uptime = gen_data['Min Up Time Hr'].to_numpy()\n", "min_downtime = gen_data['Min Down Time Hr'].to_numpy()\n", "sr_elig = gen_data['SR eligible'].to_numpy()\n", "\n", "n_gen = len(gen_id)\n", "\n", "# load data\n", "load = load_and_res_data['Load MW'].to_numpy()\n", "wind = load_and_res_data['Wind MW'].to_numpy()\n", "pv = load_and_res_data['PV MW'].to_numpy()\n", "n_t = len(load)" ] }, { "cell_type": "markdown", "id": "2e119698-9e73-49ae-b870-9e83b9e299ca", "metadata": {}, "source": [ "**3. Inspect data**\n", "- We can see the very typical duck curve (area between load and net-load looks like a duck). The net load is the load subtracted by RES production (in this case Wind and PV)." ] }, { "cell_type": "code", "execution_count": 9, "id": "e9e10360-2a14-411a-9c9d-0a5d5b549bdd", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# inspect the data\n", "\n", "fig, ax = plt.subplots(1,1)\n", "ax.plot(load, label=\"load\", color=\"black\")\n", "ax.plot(wind, label=\"wind\", color=\"blue\")\n", "ax.plot(pv, label=\"pv\", color=\"orange\")\n", "ax.plot(load-wind-pv, label=\"net load\", color=\"black\", ls=\"--\")\n", "ax.set_ylabel(\"Power [MW]\")\n", "ax.set_xlabel(\"Hour\")\n", "ax.legend(ncols=2);" ] }, { "cell_type": "markdown", "id": "230ebce9-aeff-487c-bb7a-c603dad83039", "metadata": {}, "source": [ "**4. Define mathematical model (SCUC with reserves)**\n", "\n", "**Objective function:**\n", "- Minimize the sum of cost of generation _$C_t^{\\text{gen}}$_ and unit commitment _$C_t^{\\text{uc}}$_ over time _T_.\n", "\n", "**Sets:**\n", "- _$\\mathcal{G}^{\\rm S}$_ Set of generators with spinning reserve eligibility.\n", " \n", "**Decision variables:**\n", "- _$p_{i,t}^{\\text{c}}$_ production of conventional generator _i_ in _t_.\n", "- _$p_{i,t}^{\\text{w}}$_ production of wind generator _i_ in _t_.\n", "- _$p_{i,t}^{\\text{pv}}$_ production of PV _i_ in _t_.\n", "- _$r^{\\rm s}_{i,t}$_ spinning reserve of _i_ in _t_.\n", "- _$r^{\\rm ns}_{i,t}$_ non-spinning reserve in _i_ in _t_.\n", "\n", "**Binary decision variables:**\n", "- _$u_{i,t}$_ on/off status indicator of unit _i_ in _t_.\n", "- _$v_{i,t}$_ start-up indicator of unit _i_ in _t_ ( can be relaxed to be bound between 0 and 1 as long as _$u_{i,t}$_ is binary).\n", "- _$w_{i,t}$_ shut-down indicator of unit _i_ in _t_ ( can be relaxed to be bound between 0 and 1 as long as _$u_{i,t}$_ is binary).\n", "\n", "**SCUC Constraints:**\n", "- Generation cost _$C_t^{\\text{gen}}$_ is equal to the cost function _$c_i(p^{\\text{c}}_{i,t})$_ \n", "- Unit commitment cost _$C_t^{\\text{curt}}$_ occur for each start-up event indicated by _$v_{i,t}$_ with cost _$c^{\\rm su}_i$_ and for each shut-down event indicated by _$w_{i,t}$_ with cost _$c^{\\rm sd}_i$_.\n", "- Energy balance constraint: The sum of generation needs to equal the demand _$D_t$_ in each _t_.\n", "- Generator capacity constraint: Each generators output needs to be within their respective lower and upper limits if the unit is on, whcih is indicated by _$u_{i,t} = 1$_.\n", "- Minimum up and run time constraints: After a startup or shutdown event the generator is required to stay on/off given by the _DT_ and _UT_.\n", "- Ramping constraints: Conventional generators have ramping constraints, which limit how much their generation _$p_{i,t}^{\\text{c}}$_ can change up or down from one time step to the next. It is limit by _$R_i^{\\text{60}}$_ and it includes the required ramping limits for startup and shutdown events.\n", "\n", "\\begin{align}\n", "\\min \\quad \n", " & \\sum_{t=1}^T \\big(C_t^{\\rm gen} + C_t^{\\rm uc} \\big)\\\\\n", "\\text{s.t.} \\quad \n", " & C_t^{\\rm gen} = \\sum_{i\\in[G]} c_i(p^{\\rm c}_{i,t}) && \\forall t \\in [T] \\\\\n", " & C_t^{\\rm uc} = \\sum_{i\\in[G]}\\big(c^{\\rm su}_i v_{i,t} + c^{\\rm sd}_i w_{i,t} \\big) && \\forall t \\in [T] \\\\\n", " & \\sum_{i\\in[G]} p_{i,t}^{\\rm c} + \\sum_{i\\in[W]} p_{i,t}^{\\rm w} + \\sum_{i\\in[PV]} p_{i,t}^{\\rm pv} = D_t && \\forall t \\in [T] \\\\\n", " & \\underline{P}_{i}u_{i,t} \\le p_{i,t}^{\\rm c} \\le \\overline{P}_{i}u_{i,t} && \\forall i \\in [G],t \\in [T] \\\\\n", " & \\sum_{s=t-(UT_i-1)}^t v_{i,s} \\leq u_{i,t} && \\forall i \\in [G],t \\in [T] \\\\\n", " & \\sum_{s=t-(DT_i-1)}^t w_{i,s} \\leq 1-u_{i,t} && \\forall i \\in [G],t \\in [T] \\\\\n", " & v_{i,t} - w_{i,t} = u_{i,t} - u_{i,t-1} && \\forall i \\in [G],t \\in [T] \\\\\n", " & p_{i,t}^{\\rm c} - p_{i,t-1}^{\\rm c} \\le R_i^{\\rm 60} + v_{i,t}\\underline{P}_i && \\forall i \\in [G],t \\in [T] \\\\\n", " & p_{i,t-1}^{\\rm c} - p_{i,t}^{\\rm c} \\le R_i^{\\rm 60} + w_{i,t}\\underline{P}_i && \\forall i \\in [G],t \\in [T] \\\\\n", " & u_{i,t}\\in\\{0,1\\} && \\forall i \\in [G],t \\in [T] \\\\\n", " & 0 \\le v_{i,t}, w_{i,t} \\le 1 && \\forall i \\in [G], t \\in [T] \n", "\\end{align}\n", "**Reserve constraints:**\n", "- Generators cannot offer reserves beyond their output levels.\n", "- Only some generators are eligible to offer spinning reserves.\n", "- Reserves need to be greater or eqaul to the largest contributing generator.\n", "- Reserves need to be greater or equal to the reserve requirements level _$r^{\\rm req}_t$_.\n", "- Half of reserve requirement _$r^{\\rm req}_t$_ needs to be covered by at least 50\\% spinning reserves.\n", "\n", "\\begin{align}\n", " & p_{i,t} + r^{\\rm s}_{i,t} \\le \\overline{P}_i u_{i,t} && \\forall i \\in [G],t \\in [T] \\\\\n", " & p_{i,t} + r^{\\rm s}_{i,t} + r^{\\rm ns}_{i,t} \\le \\overline{P}_i && \\forall i \\in [G],t \\in [T] \\\\\n", " & r_{i,t}^{\\rm s} = 0 && \\forall i \\in [G]\\setminus \\mathcal{G}^{\\rm S}, t \\in [T] \\\\\n", " & r^{\\rm req}_t \\ge p_{i,t} && \\forall t \\in [T] \\\\\n", " & \\sum_{i\\in[G]} (r^{\\rm s}_{i,t} + r^{\\rm ns}_{i,t}) \\ge r^{\\rm req}_t && \\forall t \\in [T] \\\\\n", " & \\sum_{i\\in[G]} r^{\\rm s}_{i,t} \\ge 0.5 r^{\\rm req}_t && \\forall t \\in [T] \n", "\\end{align}\n" ] }, { "cell_type": "code", "execution_count": 18, "id": "66212b53-943b-4487-80c8-35132439e3c1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The model is optimal.\n", "\n", "Objective value 188.18 k$.\n", "\n", "A total of 1475.71 MWh wind were curtailed.\n", "A total of 2866.40 MWh PV were curtailed.\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# SCUC Model\n", "\n", "# some additonal parameters\n", "wind_curt_pen = 0 # $/MWh\n", "pv_curt_pen = 0 # $/MWh\n", "\n", "# write the SCUC model\n", "m = gp.Model()\n", "m.setParam(\"OutputFlag\", 0)\n", "\n", "# add variables\n", "p = m.addVars(n_gen, n_t, lb=0, ub=GRB.INFINITY, name=\"p\")\n", "u = m.addVars(n_gen, n_t, vtype=GRB.BINARY, name=\"u\") # commitment indicator\n", "v = m.addVars(n_gen, n_t, lb=0, ub=1, name=\"v\") # start-up indicator\n", "w = m.addVars(n_gen, n_t, lb=0, ub=1, name=\"w\") # shut-down indicator\n", "p_wind = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"p_wind\")\n", "p_pv = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"p_pv\")\n", "r_req = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"r_req\")\n", "p_rs = m.addVars(n_gen, n_t, lb=0, ub=GRB.INFINITY, name=\"p_rs\") # spinning reserve\n", "p_rns = m.addVars(n_gen, n_t, lb=0, ub=GRB.INFINITY, name=\"p_rns\") # non-spinning reserve\n", "\n", "\n", "# energy balance\n", "m.addConstrs((sum(p[i,t] for i in range(n_gen)) + p_wind[t] + p_pv[t] == load[t] for t in range(n_t)), name=\"energy_balance\")\n", "\n", "# generator constraints\n", "for t in range(n_t):\n", " for i in range(n_gen):\n", " # maximum generation\n", " m.addConstr(p[i,t] + p_rs[i,t] <= Pmax[i]*u[i,t]) # spinning reserve can be provided only from \"on\" generators\n", " m.addConstr(p[i,t] + p_rs[i,t] + p_rns[i,t] <= Pmax[i]) # non-spiining reserve can be provided also from \"off\" generators\n", " m.addConstr(p[i,t] >= Pmin[i]*u[i,t])\n", " # reserve eligibility\n", " if sr_elig[i]==0:\n", " m.addConstr(p_rs[i,t] == 0)\n", " # ramping\n", " if t>0:\n", " # when generators are switching on or off the output change may be larger than the ramp\n", " # limit if the ramp limit is smaller than the minimum production\n", " m.addConstr(p[i,t] - p[i,t-1] <= R60[i] + v[i,t]*Pmin[i])\n", " m.addConstr(p[i,t-1] - p[i,t] <= R60[i] + w[i,t]*Pmin[i])\n", " # unit commitment constraints\n", " # constraints on minimum up and downtime\n", " ut = max(t-(math.ceil(min_uptime[i])-1), 0) \n", " dt = max(t-(math.ceil(min_downtime[i])-1), 0)\n", " m.addConstr(sum(v[i, s] for s in range(ut,t)) <= u[i,t])\n", " m.addConstr(sum(w[i, s] for s in range(dt,t)) <= 1 - u[i,t])\n", " # start-up and shut-down constraints\n", " if t>0:\n", " m.addConstr(v[i,t] - w[i,t] == u[i,t] - u[i,t-1])\n", " else:\n", " # First timestep has no ramping constraints, i.e. system can jump-start\n", " m.addConstr(v[t,i] - w[t,i] == u[t,i])\n", "\n", "# RES constraints\n", "for t in range(n_t):\n", " m.addConstr(p_wind[t] <= wind[t])\n", " m.addConstr(p_pv[t] <= pv[t])\n", "\n", "# reserve constraints\n", "for t in range(n_t):\n", " # reserve must cover at least the largest production of a single generator\n", " m.addConstrs(r_req[t] >= p[i,t] for i in range(n_gen))\n", " m.addConstr(sum(p_rs[i,t] + p_rns[i,t] for i in range(n_gen)) >= r_req[t])\n", " # at least 50% of reserve must be spinning reserve\n", " m.addConstr(sum(p_rs[i,t]for i in range(n_gen)) >= 0.5*r_req[t])\n", "\n", "# objective\n", "gen_cost = sum(sum(mc[i]*p[i,t] for i in range(n_gen)) for t in range(n_t))\n", "curt_cost = sum((pv[t]-p_pv[t])*pv_curt_pen + (wind[t]-p_wind[t])*wind_curt_pen for t in range(n_t))\n", "startup_cost = sum(v[i,t]*su_cost[i] for i in range(n_gen) for t in range(n_t))\n", "m.setObjective(\n", " gen_cost + curt_cost + startup_cost, GRB.MINIMIZE\n", ")\n", "\n", "# run\n", "m.optimize()\n", "\n", "# Check the status of the solver\n", "print_gp_status(m)\n", "\n", "# Objective value\n", "objective = m.ObjVal\n", "print(f\"Objective value {objective/1e3:.2f} k$.\\n\")\n", "\n", "# production plot\n", "p_res = {type: np.array([m.getVarByName(f\"p[{i},{t}]\").X for t in range(n_t)]) for (i,type) in enumerate(gen_id)}\n", "p_res['Wind'] = np.array([m.getVarByName(f\"p_wind[{t}]\").X for t in range(n_t)])\n", "p_res['PV'] = np.array([m.getVarByName(f\"p_pv[{t}]\").X for t in range(n_t)])\n", "\n", "#curtailment\n", "wind_curt_res = wind - np.array(p_res['Wind'])\n", "pv_curt_res = pv - np.array(p_res['PV'])\n", "print(f\"A total of {sum(wind_curt_res):.2f} MWh wind were curtailed.\")\n", "print(f\"A total of {sum(pv_curt_res):.2f} MWh PV were curtailed.\")\n", "\n", "# let's aggregate generator production by generator type\n", "\n", "# list of unique generator types\n", "gen_type_unique = np.unique(gen_type)\n", "# map of generator types to generators\n", "gens_per_type = {gtu: [i for i,gt in enumerate(gen_type) if gt==gtu] for gtu in gen_type_unique}\n", "# sum the respective production\n", "p_res_type = {gtu: sum([p_res[gi] for i,gi in enumerate(gen_id) if i in genst]) for gtu,genst in gens_per_type.items()}\n", "# add wind and PV results\n", "p_res_type['Wind'] = np.array([m.getVarByName(f\"p_wind[{t}]\").X for t in range(n_t)])\n", "p_res_type['PV'] = np.array([m.getVarByName(f\"p_pv[{t}]\").X for t in range(n_t)])\n", "\n", "\n", "# plot of aggregated production\n", "fig, ax = plt.subplots(1,1)\n", "fig.set_size_inches(10,6)\n", "x = np.arange(24)\n", "color_list = [gen_colors[g] for g in list(p_res_type.keys())]\n", "ax.stackplot(x, list(p_res_type.values()), labels=list(p_res_type.keys()), colors=color_list);\n", "ax.plot(load, linewidth=3, color='black', label='Load')\n", "ax.set_xlabel(\"Hour\")\n", "ax.set_ylabel(\"Generation [MW]\")\n", "ax.legend(ncols=5, loc=\"lower center\", bbox_to_anchor=(0.5, -0.23));" ] }, { "cell_type": "markdown", "id": "6ca01031-518f-4dc6-9845-d25c6ebcc2cd", "metadata": {}, "source": [ "**5. Prices from SCUC**\n", "- In a Economic Dispatch (ED) problem, prices can be drawn by taking the dual variable of the energy balance constraint.\n", "- In the case of a SCUC computing the dual of the energy balance will fail because the model is a Mixed-Integer Problem (MIP).\n", "- This means the following block will return a error message:" ] }, { "cell_type": "code", "execution_count": 17, "id": "8aeea08e-848d-4b15-8fa1-7d982435e138", "metadata": {}, "outputs": [ { "ename": "AttributeError", "evalue": "Unable to retrieve attribute 'Pi'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[17], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# computing the dual of the energy balance will faill because m is a MIP \u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;66;03m# NOTE: We used addConstrs for the energy balance and there is an energy balance for each t=0,...,23\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# This means we need to retrieve constraints using the name \"energy_balance[{t}]\"!!\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m system_price \u001b[38;5;241m=\u001b[39m \u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgetConstrByName\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43menergy_balance[\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m]\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPi\u001b[49m\n", "File \u001b[0;32msrc/gurobipy/constr.pxi:67\u001b[0m, in \u001b[0;36mgurobipy.Constr.__getattr__\u001b[0;34m()\u001b[0m\n", "File \u001b[0;32msrc/gurobipy/constr.pxi:95\u001b[0m, in \u001b[0;36mgurobipy.Constr.getAttr\u001b[0;34m()\u001b[0m\n", "File \u001b[0;32msrc/gurobipy/attrutil.pxi:103\u001b[0m, in \u001b[0;36mgurobipy._getattr\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mAttributeError\u001b[0m: Unable to retrieve attribute 'Pi'" ] } ], "source": [ "\n", "system_price = m.getConstrByName(f\"energy_balance[{1}]\").Pi" ] }, { "cell_type": "markdown", "id": "287347ee-4a4c-4156-aff1-eb9a4cccd47c", "metadata": {}, "source": [ "**A workaround is to first retrieve the unit commitmennt decisions and fix them in the SCUC model, turning it into a Linear Programming (LP) problem**" ] }, { "cell_type": "code", "execution_count": 19, "id": "5b5c2368-6736-4d2e-a0c9-760448a2ff85", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# let's retrieve and save the unit commitment decisions and plot them\n", "\n", "u_opt = np.array([[u[i,t].X for t in range(n_t)] for i in range(n_gen)])\n", "\n", "# Plot the grid\n", "plt.imshow(u_opt, cmap='gray_r', interpolation='nearest', origin='lower')\n", "plt.xticks(ticks=np.arange(u_opt.shape[1]), labels=np.arange(u_opt.shape[1]))\n", "plt.yticks(ticks=np.arange(u_opt.shape[0]), labels=np.arange(u_opt.shape[0]))\n", "plt.grid(color='gray', linestyle='-', linewidth=1)\n", "plt.ylabel(\"Generator index\")\n", "plt.xlabel(\"Time step t\")\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "92b884f0-fd77-4aa2-97cb-9bc9ca277b3f", "metadata": {}, "source": [ "**Now re-run the model with the commitment-decisions fixed:**" ] }, { "cell_type": "code", "execution_count": null, "id": "1e9f1900-b04f-4d63-a07f-a8d619fb95d4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The model is optimal.\n", "\n", "Objective value 188.16 k$.\n", "\n", "A total of 2454.41 MWh wind were curtailed.\n", "A total of 1887.70 MWh PV were curtailed.\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# create a version of the model with fixed integer variables\n", "\n", "m_fixed = m.fixed() # requires m to contain an optimal solution\n", "\n", "# run the fixed version\n", "m_fixed.optimize()\n", "\n", "# Check the status of the solver\n", "print_gp_status(m)\n", "\n", "# Objective value\n", "objective = m_fixed.ObjVal\n", "print(f\"Objective value {objective/1e3:.2f} k$.\\n\")\n", "\n", "# production plot\n", "p_res = {type: np.array([m_fixed.getVarByName(f\"p[{i},{t}]\").X for t in range(n_t)]) for (i,type) in enumerate(gen_id)}\n", "p_res['Wind'] = np.array([m_fixed.getVarByName(f\"p_wind[{t}]\").X for t in range(n_t)])\n", "p_res['PV'] = np.array([m_fixed.getVarByName(f\"p_pv[{t}]\").X for t in range(n_t)])\n", "\n", "#curtailment\n", "wind_curt_res = wind - np.array(p_res['Wind'])\n", "pv_curt_res = pv - np.array(p_res['PV'])\n", "print(f\"A total of {sum(wind_curt_res):.2f} MWh wind were curtailed.\")\n", "print(f\"A total of {sum(pv_curt_res):.2f} MWh PV were curtailed.\")\n", "\n", "# let's aggregate generator production by generator type\n", "\n", "# list of unique generator types\n", "gen_type_unique = np.unique(gen_type)\n", "# map of generator types to generators\n", "gens_per_type = {gtu: [i for i,gt in enumerate(gen_type) if gt==gtu] for gtu in gen_type_unique}\n", "# sum the respective production\n", "p_res_type = {gtu: sum([p_res[gi] for i,gi in enumerate(gen_id) if i in genst]) for gtu,genst in gens_per_type.items()}\n", "# add wind and PV results\n", "p_res_type['Wind'] = np.array([m_fixed.getVarByName(f\"p_wind[{t}]\").X for t in range(n_t)])\n", "p_res_type['PV'] = np.array([m_fixed.getVarByName(f\"p_pv[{t}]\").X for t in range(n_t)])\n", "\n", "\n", "# plot of aggregated production\n", "fig, ax = plt.subplots(1,1)\n", "fig.set_size_inches(10,6)\n", "x = np.arange(24)\n", "color_list = [gen_colors[g] for g in list(p_res_type.keys())]\n", "ax.stackplot(x, list(p_res_type.values()), labels=list(p_res_type.keys()), colors=color_list);\n", "ax.plot(load, linewidth=3, color='black', label='Load')\n", "ax.set_xlabel(\"Hour\")\n", "ax.set_ylabel(\"Generation [MW]\")\n", "ax.legend(ncols=5, loc=\"lower center\", bbox_to_anchor=(0.5, -0.23));" ] }, { "cell_type": "markdown", "id": "6ef9a8d1-8852-4129-b184-3e4855ace1dd", "metadata": {}, "source": [ "**Now lets get prices:**" ] }, { "cell_type": "code", "execution_count": 21, "id": "8e6c908d-dd30-442e-97fe-001fb89926be", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[25.0, 14.0, 14.0, 14.0, 12.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 10.0, 14.0, 14.0, 12.0, 10.0, 10.0, 10.0]\n" ] } ], "source": [ "system_price = [m.getConstrByName(f\"energy_balance[{t}]\").Pi for t in range(n_t)]\n", "print(system_price)" ] }, { "cell_type": "code", "execution_count": 22, "id": "ea56543f-57cf-4b31-ac41-ba4bdd0ca4b7", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot production with price\n", "\n", "fig, ax = plt.subplots(1,1)\n", "fig.set_size_inches(10,6)\n", "x = np.arange(24)\n", "color_list = [gen_colors[g] for g in list(p_res_type.keys())]\n", "ax.stackplot(x, list(p_res_type.values()), labels=list(p_res_type.keys()), colors=color_list);\n", "ax.plot(load, linewidth=3, color='black', label='Load')\n", "ax2 = ax.twinx() \n", "ax2.plot(system_price, color='blue', linewidth=3, ls=\"--\", label=\"Price\")\n", "ax2.set_ylim(0)\n", "ax2.set_ylabel(\"System price [$]\", color=\"blue\")\n", "ax.set_xlabel(\"Hour\")\n", "ax.set_ylabel(\"Generation [MW]\")\n", "ax.legend(ncols=5, loc=\"lower center\", bbox_to_anchor=(0.5, -0.23));" ] }, { "cell_type": "markdown", "id": "743c5e9e-2f06-4af1-99c6-31961189c27f", "metadata": {}, "source": [ "**6. Let us add an ideal storage to the SCUC model**\n", "- An ideal storage does not consider charging and discharging efficiencies.\n", "\n", "**Added decision variables:**\n", "- _$p_t^{\\rm ch}$_ charging in _t_.\n", "- _$p_t^{\\rm dis}$_ discharging in _t_.\n", "- _$e_t$_ State of Charge (SoC) in _t_.\n", "\n", "**Battery constraints:**\n", "- Battery energy balance constraint: battery SoC is equal to previous SoC including all charging and discharging activities.\n", "- Storage capacity constraint: battery SoC is limited by lower and upper bounds.\n", "- Power capacity constraint: charging and discharging is limited by the power capacity.\n", "- Bilinear feasibility constraint: disallowing charging and discharging in the same time _t_.\n", "\n", "\\begin{align}\n", " &e_t = e_{t-1} + p_t^{\\rm ch} \\eta^{\\rm ch} - p_t^{\\rm dis} \\frac{1}{\\eta^{\\rm dis}} \\\\\n", " & \\underline{E} \\le e_t \\le \\overline{E} && \\forall t \\in [T] \\\\\n", " & 0 \\leq p_t^{\\rm ch} \\le \\overline{P}^{\\rm ess} && \\forall t \\in [T] \\\\\n", " & 0 \\leq p_t^{\\rm dis} \\le \\overline{P}^{\\rm ess} && \\forall t \\in [T] \\\\\n", " & p_t^{\\rm ch} p_t^{\\rm dis} = 0 && \\forall t \\in [T]\n", "\\end{align}\n", "\n", "The bilinear feasibility constraint can reformulated using a binary variable indicating charging status:\n", "\n", "\\begin{align}\n", " & p_t^{\\rm ch} \\le \\overline{P}^{\\rm ess}u^{\\rm ch} && \\forall t \\in [T] \\\\\n", " & p_t^{\\rm dis} \\le \\overline{P}^{\\rm ess}(1-u^{\\rm ch}) && \\forall t \\in [T] \\\\\n", " & u^{\\rm ch} \\in \\{0,1\\} && \\forall t \\in [T]\n", "\\end{align}\n" ] }, { "cell_type": "code", "execution_count": null, "id": "7e64679a-4da0-4aa0-9f66-b1fd1f7ea369", "metadata": {}, "outputs": [], "source": [ "\n", "# some additonal parameters\n", "wind_curt_pen = 0 # $/MWh\n", "pv_curt_pen = 0 # $/MWh\n", "\n", "# define the storage\n", "ess_Emin = 0\n", "ess_Emax = 1000 # MWh\n", "ess_E0 = 250 # assume storage is half full at start of day\n", "ess_Etarget = ess_E0 # assume at end of day storage should be half full again for next day\n", "ess_pmax = 200 # MW\n", "\n", "# write the SCUC model\n", "m = gp.Model()\n", "m.setParam(\"OutputFlag\", 0)\n", "\n", "# add variables\n", "p = m.addVars(n_gen, n_t, lb=0, ub=GRB.INFINITY, name=\"p\")\n", "u = m.addVars(n_gen, n_t, vtype=GRB.BINARY, name=\"u\") # commitment indicator\n", "v = m.addVars(n_gen, n_t, lb=0, ub=1, name=\"v\") # start-up indicator\n", "w = m.addVars(n_gen, n_t, lb=0, ub=1, name=\"w\") # shut-down indicator\n", "p_wind = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"p_wind\")\n", "p_pv = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"p_pv\")\n", "r_req = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"r_req\")\n", "p_rs = m.addVars(n_gen, n_t, lb=0, ub=GRB.INFINITY, name=\"p_rs\") # spinning reserve\n", "p_rns = m.addVars(n_gen, n_t, lb=0, ub=GRB.INFINITY, name=\"p_rns\") # non-spinning reserve\n", "p_charge = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"p_charge\") # storage charging\n", "p_disch = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"p_disch\") # storage discharging\n", "e = m.addVars(n_t, lb=0, ub=GRB.INFINITY, name=\"e\") # energy in storage\n", "\n", "# energy balance\n", "m.addConstrs((sum(p[i,t] for i in range(n_gen)) + p_wind[t] + p_pv[t] + p_disch[t] - p_charge[t] == load[t] for t in range(n_t)), name=\"energy_balance\")\n", "\n", "# generator constraints\n", "for t in range(n_t):\n", " for i in range(n_gen):\n", " # maximum generation\n", " m.addConstr(p[i,t] + p_rs[i,t] <= Pmax[i]*u[i,t]) # spinning reserve can be provided only from \"on\" generators\n", " m.addConstr(p[i,t] + p_rs[i,t] + p_rns[i,t] <= Pmax[i]) # non-spinning reserve can be provided also from \"off\" generators\n", " m.addConstr(p[i,t] >= Pmin[i]*u[i,t])\n", " # reserve eligibility\n", " if sr_elig[i]==0:\n", " m.addConstr(p_rs[i,t] == 0)\n", " # ramping\n", " if t>0:\n", " # when generators are switching on or off the output change may be larger than the ramp\n", " # limit if the ramp limit is smaller than the minimum production\n", " m.addConstr(p[i,t] - p[i,t-1] <= R60[i] + v[i,t]*Pmin[i])\n", " m.addConstr(p[i,t-1] - p[i,t] <= R60[i] + w[i,t]*Pmin[i])\n", " # unit commitment constraints\n", " # constraints on minimum up and downtime\n", " ut = max(t-(math.ceil(min_uptime[i])-1), 0) \n", " dt = max(t-(math.ceil(min_downtime[i])-1), 0)\n", " m.addConstr(sum(v[i, s] for s in range(ut,t)) <= u[i,t])\n", " m.addConstr(sum(w[i, s] for s in range(dt,t)) <= 1 - u[i,t])\n", " # start-up and shut-down constraints\n", " if t>0:\n", " m.addConstr(v[i,t] - w[i,t] == u[i,t] - u[i,t-1])\n", " else:\n", " # First timestep has no ramping constraints, i.e. system can jump-start\n", " m.addConstr(v[t,i] - w[t,i] == u[t,i])\n", "\n", "# storage constraints\n", "for t in range(n_t):\n", " m.addConstr(p_charge[t] <= ess_pmax)\n", " m.addConstr(p_disch[t] <= ess_pmax)\n", " m.addConstr(e[t] >= ess_Emin)\n", " m.addConstr(e[t] <= ess_Emax)\n", " if t>0:\n", " m.addConstr(e[t] == e[t-1] + p_charge[t] - p_disch[t])\n", "m.addConstr(e[0] == ess_E0)\n", "m.addConstr(e[n_t-1] == ess_Etarget)\n", " \n", "# RES constraints\n", "for t in range(n_t):\n", " m.addConstr(p_wind[t] <= wind[t])\n", " m.addConstr(p_pv[t] <= pv[t])\n", "\n", "# reserve constraints\n", "for t in range(n_t):\n", " # reserve must cover at least the largest production of a single generator\n", " m.addConstrs(r_req[t] >= p[i,t] for i in range(n_gen))\n", " m.addConstr(sum(p_rs[i,t] + p_rns[i,t] for i in range(n_gen)) >= r_req[t])\n", " # at least 50% of reserve must be spinning reserve\n", " m.addConstr(sum(p_rs[i,t]for i in range(n_gen)) >= 0.5*r_req[t])\n", "\n", "# objective\n", "gen_cost = sum(sum(mc[i]*p[i,t] for i in range(n_gen)) for t in range(n_t))\n", "curt_cost = sum((pv[t]-p_pv[t])*pv_curt_pen + (wind[t]-p_wind[t])*wind_curt_pen for t in range(n_t))\n", "startup_cost = sum(v[i,t]*su_cost[i] for i in range(n_gen) for t in range(n_t))\n", "m.setObjective(\n", " gen_cost + curt_cost + startup_cost, GRB.MINIMIZE\n", ")\n", "\n", "# run\n", "m.optimize()\n", "\n", "# Check the status of the solver\n", "print_gp_status(m)\n", "\n", "# Objective value\n", "objective = m.ObjVal\n", "print(f\"Objective value {objective/1e3:.2f} k$.\\n\")\n", "\n", "# prodcution plot\n", "p_res = {type: np.array([m.getVarByName(f\"p[{i},{t}]\").X for t in range(n_t)]) for (i,type) in enumerate(gen_id)}\n", "p_res['Wind'] = np.array([m.getVarByName(f\"p_wind[{t}]\").X for t in range(n_t)])\n", "p_res['PV'] = np.array([m.getVarByName(f\"p_pv[{t}]\").X for t in range(n_t)])\n", "\n", "#curtailment\n", "wind_curt_res = wind - np.array(p_res['Wind'])\n", "pv_curt_res = pv - np.array(p_res['PV'])\n", "print(f\"A total of {sum(wind_curt_res):.2f} MWh wind were curtailed.\")\n", "print(f\"A total of {sum(pv_curt_res):.2f} MWh PV were curtailed.\")\n", "\n", "# let's aggregate generator production by generator type\n", "\n", "# list of unique generator types\n", "gen_type_unique = np.unique(gen_type)\n", "# map of generator types to generators\n", "gens_per_type = {gtu: [i for i,gt in enumerate(gen_type) if gt==gtu] for gtu in gen_type_unique}\n", "# sum the respective production\n", "p_res_type = {gtu: sum([p_res[gi] for i,gi in enumerate(gen_id) if i in genst]) for gtu,genst in gens_per_type.items()}\n", "# add wind and PV results\n", "p_res_type['Wind'] = np.array([m.getVarByName(f\"p_wind[{t}]\").X for t in range(n_t)])\n", "p_res_type['PV'] = np.array([m.getVarByName(f\"p_pv[{t}]\").X for t in range(n_t)])\n", "# add storage results\n", "p_res_type['Storage'] = np.array([m.getVarByName(f\"p_disch[{t}]\").X for t in range(n_t)]) - np.array([m.getVarByName(f\"p_charge[{t}]\").X for t in range(n_t)])\n", "\n", "# plot of aggregated production\n", "fig, ax = plt.subplots(1,1)\n", "fig.set_size_inches(10,6)\n", "x = np.arange(24)\n", "color_list = [gen_colors[g] for g in list(p_res_type.keys())]\n", "ax.stackplot(x, list(p_res_type.values()), labels=list(p_res_type.keys()), colors=color_list);\n", "ax.plot(load, linewidth=3, color='black', label='Load')\n", "ax.set_xlabel(\"Hour\")\n", "ax.set_ylabel(\"Generation [MW]\")\n", "ax.legend(ncols=5, loc=\"lower center\", bbox_to_anchor=(0.5, -0.23));" ] }, { "cell_type": "code", "execution_count": null, "id": "a257dd1b-0bf3-429b-8a59-bc45495f1c75", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.6" } }, "nbformat": 4, "nbformat_minor": 5 }