TECHNICAL FIELD

The present disclosure relates to an energy management system, a power demand plan optimization method, and a power demand plan optimization program.

Priority is claimed on Japanese Patent Application No. 2017-223103, filed Nov. 20, 2017, the content of which is incorporated herein by reference.

BACKGROUND ART

As renewable energy power-generation systems such as photovoltaic power generation and hydroelectric power generation systems have become widespread, research on stabilization of power supply systems and reduction of costs incurred for supply of electricity by appropriately controlling energy storage devices such as storage batteries has been conducted. For example, in the field of research on charging/discharging plan optimization for an energy storage device using an energy management system (EMS) for a microgrid, there are many proposed methods in which a period from a current time point to a specific future time point is divided into a plurality of fixed time intervals, power demand from loads and an amount of renewable energy generation are each predicted for the fixed time intervals, the output and capacity of an energy storage device, the presence or absence of a reverse flow, contracted electricity, and the like are set as restricting conditions, and finally, a charging/discharging plan that is likely to minimize costs for operating the microgrid in every given period based on differences in electricity fees is obtained using a mathematical optimization method.

However, it is generally known that accurate prediction of electricity demand and an amount of renewable energy generation is inherently difficult. In particular, renewable energy is a source of electricity bearing high uncertainty in that amounts of energy generation are heavily affected by weather conditions. In photovoltaic power generation, for example, even a few clouds covering the sun can significantly change an amount of power generation.

Due to such uncertainty in prediction, executing charging and discharging as indicated by a charging/discharging plan that is obtained using the mathematical optimization method does not necessarily lead to minimized operation costs for a microgrid. In some cases, there is a possibility of the restricting conditions being breached, such as depletion of a remaining charge of an energy storage device, and an excess of contracted electricity, occurring due to uncertainty in prediction. For this reason, there is demand for development of a charging/discharging plan optimization technique that enables restricting conditions to be reliably met and operation costs for a microgrid to be lowered taking such uncertainty in prediction into account.

As related art for making an operation plan for an energy storage device taking uncertainty in prediction into account, for example, there is the technology disclosed in Patent Document 1. The decentralized energy system disclosed in Patent Document 1 assumes in advance a plurality of cases including not only a case in which prediction is correct but also a case of a prediction deviation in which a prediction deviates more than a certain degree at some point. In addition, the decentralized energy system disclosed in Patent Document 1 carries out a control operation simulation after the occurrence of a case of a prediction deviation to evaluate operation costs whenever a case of a prediction deviation occurs, and decides an operation plan that can minimize the weighted sum of the operation costs of each case (the weight of an occurrence probability of each case).

Document of Related Art

Patent Document[Patent Document 1] Japanese Patent No. 4245583

SUMMARY OF INVENTION

Technical Problem

However, since a simulation needs to be performed whenever a case of a prediction deviation occurs in the technology disclosed in Patent Document 1, a lot of calculation time is needed to perform the simulation, which is a problem. For example, an operation plan for an energy storage device is frequently modified on a day when the weather often changes, a simulation is performed each time, and thus an enormous calculation time is required. In addition, if the operation plan for the energy storage device is frequently modified, performing a simulation may fail to keep up with the rate of change in weather, and thus it is difficult to modify the operation plan. As a result, the technology disclosed in Patent Document 1 has a problem of not being able to follow electricity charging and discharging to an optimum level to respond to a case in which electricity demand of loads or an amount of renewable energy generation rapidly change.

The present disclosure is made in view of the above-described circumstances, and an object is to provide an energy management system, a power demand plan optimization method, and a power demand plan optimization program that can make an operation plan in consideration of uncertainty in prediction in a shorter calculation time.

Solution to Problem

In order to solve the above problems, an energy management system of a first aspect of the present disclosure is an energy management system for a microgrid including at least either one of an electrical load and a renewable energy power-generation system, and an energy storage device, the energy management system including: a prediction unit that predicts, at a fixed time interval, at least either one of an electricity demand and an amount of electricity generated from renewable energy, and an electricity fee, within a predetermined period; and an optimization unit that performs optimization for an optimum charging/discharging plan for the energy storage device by using a prediction result from the prediction unit and in consideration of uncertainty in prediction.

In addition, in the energy management system of the first aspect of the present disclosure, the optimization unit may be configured to derive, at the fixed time interval through the optimization, the charging/discharging plan indicating an optimum amount of charged/discharged electricity for the energy storage device.

In addition, in the energy management system of the first aspect of the present disclosure, the optimization unit may be configured to derive, at the fixed time interval through the optimization, a predicted/actual difference compensation plan indicating a proportion of a predicted/actual difference in charging/discharging to be compensated in charging/discharging of the energy storage device.

In addition, a power demand plan optimization method of a second aspect of the present disclosure is a power demand plan optimization method performed by a computer for a microgrid including at least either one of an electrical load and a renewable energy power-generation system, and an energy storage device, the power demand plan optimization method including: a prediction step of predicting, at a fixed time interval, at least either one of an electricity demand and an amount of electricity generated from renewable energy, and an electricity fee, within a predetermined period; and an optimization step of performing optimization for an optimum charging/discharging plan for the energy storage device by using a prediction result from the prediction step and in consideration of uncertainty in prediction.

In addition, a power demand plan optimization program of a third aspect of the present disclosure is for a microgrid including at least either one of an electrical load and a renewable energy power-generation system, and an energy storage device, to cause a computer to execute: a prediction step of predicting, at a fixed time interval, at least either one of an electricity demand and an amount of electricity generated from renewable energy, and an electricity fee, within a predetermined period; and an optimization step of performing optimization for an optimum charging/discharging plan for the energy storage device by using a prediction result from the prediction step and in consideration of uncertainty in prediction.

Effects

According to the present disclosure, it is possible to make an operation plan in consideration of uncertainty in prediction in a shorter calculation time.

